It’s been around 2 years since my 1st startup was incorporated and slightly over 1 year since it became a standalone company with full-time employees and dedicated labs. A bit funny to say myself, but I thought that I am pretty good at hardworking and multi-tasking reflecting on my productivity in academia. Well, the last year of my startup journey and commercialization-oriented medical device development taught me hard lessons that I am not enough. Every week has been an intense learning experience with numerous ups and downs, making me more capable and humbler than before. Seeing lots of challenges that could have been avoided if I had been better informed/trained on real-world engineering and the intense educational value of this journey, I thought sharing this experience with younger engineers might be useful. Yes, still, I am kind of academic in my mindset (who knows I will return to university once I redeem myself as a true engineer).

I had a chance to share some of my experience and lessons learned by teaching part of a course at one university where I currently serve as an adjunct faculty member. I wish to share the lecture notes here in case useful for a broader audience.

1. Introduction of Medical Device Development - What Are Medical Devices and Regulations for Them?
2. What’s Difference Between Academic and Industrial R&D? - Chasing 3Ps: Publications, Patents, and Products
3. Regulation-Informed Medical Device R&D - Lessons Learned: From Academic Projects to Commercialization
4. From Basic Science Research to University Spinoff Startup - Bring Research from University Laboratory to Real World

​​Disclaimer. The contents are my personal opinion and do not represent the view of any institution or company I am affiliated/employed. If you find any incorrect information, please feel free to let me know via my email.

As the startup that I co-founded, SanaHeal, Inc., was incorporated at the end of October 2021, it recently hit its first 6-months of the journey. I left MIT to work full-time in the startup from April 2022, it’s almost 3rd month in my full-time startup journey. It has been a busy 6 months with a long list of items that have been check-marked as groundworks for starting any self-standing and functioning company. Yes, it’s still really early days – but it has been a strikingly enjoyable and refreshing experience for me, so I think it’s worth writing down my first impressions.

Answering the same question – Why not become a professor?
In the first few months after deciding to transit on the startup journey, I got the same questions from my colleagues and friends – why not become a professor at university? It was a bit silly question, but an understandable one as my career seemed geared toward an academic career to be a faculty in research-focused universities. Frankly, I don’t think that I have an answer since I am not sure whether the startup journey is a brief digression from my academic career or something permanent departure from academia for now. But I had a few questions that I asked myself to decide to go for the startup journey instead of finding a faculty job for now.

• Which environment is better if I want to absorb actual knowledge and experience about making a real-world impact instead of pretending to do so?
• Do I want to continue competitive paper publication? Or more fundamentally, would such competitive paper publication yield real-world impact instead of pretending to do so?
• Which environment has a higher chance of working with people with whom I can share visions and goals?
• Which environment better appreciate my full capability and merit?

My answers were all pointing to the startup journey rather than a faculty job in academic institutions at least for the time I considered. Who knows it may change later but it really was at that time. We have seen lots of things during the COVID pandemic, and it did affect a lot. We have seen the gap between industry and academia broaden ever larger than before in many regards (especially financial and work-life balance metrics). We have seen a rapidly deteriorating academic publication system overall (poor quality control, hyper-competition, inflation of papers, etc). We have seen a big shift in PhD workforces toward industry. We have seen outright and shameless sabotage against fair evaluation and meritocracy in academic hirings. It has been a hard time for everyone.

Fundraising – Pitch, pitch, and pitch
Fundraising in pre-seed and seed rounds was so much fun but an entirely new type of activity that I had never experienced. Basically, it was a series of pitches to many potential investors with a rate to have the follow-up meeting less than 30 %. Unlike almost an hour-long seminar presentation, a startup investment pitch was typically at most 30 min based on presentations with around 15 slides. We had a very experienced CEO to lead the fundraising, but I felt pretty stressed initially as most of the shots were missing or going nowhere. Also, the short pitch format made me anxious as I was so familiar with lengthy academic presentations and discussions with endless and super crowded slides full of scientific and technical details. Whenever I gave a pitch with our CEO, I felt half-finished (5 years of research projects in 15 slides!). It took a long time and many tries to get used to this new type of communication.

Eventually, after 6 months of countless pitches, some hit well and now we completed our pre-seed and seed fundraising. It was a pretty interesting experience for me. It’s like meeting a person for a date and developing a relationship. Discussing lots of detailed points during the due diligence process with the investors developed some personal fondness for each other, culminating in the signing term sheet. It was a completely different yet likable experience compared to the anonymous, document-based, extremely slow-paced, and mostly single-sided communication and decision process in academic grants.

Industry experts – Lovable tribe of PhDs
When I worked mainly on academic projects, it was rare to meet and discuss industry experts deeply. In the startup journey, my world is flipped – I have to meet and discuss mostly with experts in the industry, many of them with PhDs. I worried a bit about this transition, but it was a really pointless concern. I rapidly developed a deep love for industry experts and PhDs in the industry. They are professional in what they are working on. They are well-compensated to their work with a solid work-life balance. Communications are straightforward and do not require reading between the lines. Alas, it felt like finding an oasis as these qualities were often missing and the lack of such qualities was a major driving factor that made me frustrated and tired in academia. Maybe there would be another set of problems in the industry, but at least industry experts and PhDs in industry were lovable folks and it was encouraging for me.

As I was deeply in academia and still so in some sense, I can blow some whistles loud. We often face unprofessional attitudes, mostly due to distorted personalities by hyper-competition in an academic environment. We know most academic folks, especially in their early career, are horribly under-compensated for their works (while eye-popping amount of F&A cost to beef up administrative bureaucracy). We often face awkward communications that require careful reading between the lines to uncover underlying politics and hidden conflicts of interests.

Grants and R&D – Gray areas between industry and academia
Interestingly, unlike big corporations, the startup journey has gray area with academia - R&D and federal grants. While it may depend on different fields, early-stage R&D of a new concept in BME/biotech is quite similar to that of academic projects. In some sense, they are almost identical up to proof-of-concept pre-clinical studies. Furthermore, there are lots of federal/state grant opportunities available for startups that work almost the same as grants in academic institutions (except no need to assign crazy high F&A costs!). Also, tech startups in BME/biotech areas are keen to publish papers to increase the credibility of their technologies and scientific findings. So, good or bad, the early days of the startup journey require me to do pretty the same activities that I did in the academic world – chasing & writing federal grants, developing ideas and performing R&D to materialize the idea into workable prototypes and validations, and paper publications.

Overall impression
Overall, the first 6-months have been an exciting journey out of familiar academia. I don’t know whether this uplifting experience would continue in the next 6 months, but I am hopeful.

​​Disclaimer. The contents are my personal opinion and do not represent the view of any institution or company I am affiliated/employed. If you find any incorrect information, please feel free to let me know via my email.

Every researcher was once a newcomer to academic research. We all learn from various resources in many forms including personal mentoring, research group protocols, published articles and data, friends' help, and so on. Essentially, these resources built and shared by others are true enablers that make all of us be part of the exciting academic journey either in academia or industry and will be for the future generations of researchers as they were to us.

Research papers are for communications of our ideas, academic achievements to our peers, to our society, and to the knowledge basis of humankind in the largest sense. As the dominant forms of communications have evolved – from written/printed texts in the paper publications to include images and videos in the recent digital publications – the necessary resources to help the growing researchers to absorb necessary skills have evolved too. Writing skills have been firmly part of the traditional academic training either by personal mentoring or institutional curriculum. However, more recent forms of communications, especially visual communications by images, illustrations, etc have been less formalized in terms of training of the growing researchers. One of the most conspicuous issues in this rather lagging demand-education chasm is that it is hard to find resources on visual communication skills in academic research except through exclusive mentor-mentee training.

Well, this is a big problem, so no single individual can solve it. Of course, I am far short of doing so. However, reflecting on my struggles to self-educate lots of things without good resources, I want to find ways to contribute. So, I wish to share some of the schematic illustrations of my previously written papers in the original Adobe Illustrator files with my small wish that these might be helpful for my colleagues and peers. I hope that I can catch up with my ever-delaying plan to provide more detailed tips on these topics too, but I think it would be worthy to share these first.

So, the following list provides the bibliographic information of the paper with links to the selected original Adobe Illustrator files for figure schematics that I made before. To avoid potential issues other than serving the main purpose of sharing resources, all selected schematic figures were prepared by myself & before-copyediting versions (so copyright belongs to me) and I have removed all data plots and images other than schematic figures. Please note that the reproduction/reuse of these resources would require appropriate procedures (citation, permission, etc) per the publisher’s policy of the paper to which each figure belongs.

Selected list of my papers with schematic illustration files

• Tough bonding of hydrogels to diverse non-porous surfaces, Nature Materials 15, 190-196 (2016) [link to files]
• Skin-inspired hydrogel-elastomer hybrids with robust interfaces and functional microstructures, Nature Communications 7, 12028 (2016) [link to files]
• Hydraulic hydrogel actuators and robots optically and sonically camouflaged in water, Nature Communications 8, 14230 (2017) [link to files]
• Stretchable living materials and devices with hydrogel-elastomer hybrids hosting programmed cells, Proceedings of National Academy of Science 114, 2200-2205 (2017) [link to files]
• A new 3D printing strategy by harnessing deformation, instability, and fracture of viscoelastic inks, Advanced Materials 30, 1704028 (2018) [link to files]
• Printing ferromagnetic domains for untethered fast-transforming soft materials, Nature 558, 274-279 (2018) [link to files]
• Multifunctional hydrogel skins on diverse polymers with arbitrary shapes, Advanced Materials 31, 1807101 (2019) [link to files]
• Pure PEDOT:PSS hydrogels, Nature Communications 10, 1043 (2019) [link to files]
• Hydrogel bioelectronics, Chemical Society Reviews 48, 1642-1667 (2019) [link to files]
• Dry double-sided tape for adhesion of wet tissues and devices, Nature 575, 169-174 (2019) [link to files]
• Strong adhesion of wet conducting polymers on diverse substrates, Science Advances 6, eaay5394 (2020) [link to files]
• 3D printing of conducting polymers, Nature Communications 11, 1604 (2020) [link to files]
• Instant tough bioadhesive with triggerable benign detachment, Proceedings of National Academy of Science 117, 15497-15503 (2020) [link to files]
• Electrical bioadhesive interface for bioelectronics, Nature Materials 20, 229-236 (2021) [link to files]
• Rapid and coagulation-independent haemostatic sealing by a paste inspired by barnacle glue, Nature Biomedical Engineering 5, 1131-1142 (2021) [link to files]
• An off-the-shelf bioadhesive patch for sutureless repair of gastrointestinal defects, Science Translational Medicine 14, eabh2857 (2022) [link to files]

​​Disclaimer. The contents are my personal opinion and do not represent the view of any institution or company I am affiliated/employed. If you find any incorrect information, please feel free to let me know via my email.

In graphic design, color is one of the most important considerations. For scientific figures, color is an important part of the data visualization to provide aid in visual clarity and effective delivery of the presented data. Also, the right use of color might be important depending on a certain data type in the paper. While the aesthetic quality of scientific figures is not a primary focus of scientific research and paper, figures with poorly selected colors can substantially harm the reader’s experience and clarity of the presented data. In this tip post, I wish to cover the basics of color in graphic design and provide several tips and resources for further in-depth learning on the use of color for data visualization.

RGB vs. CMYK
In graphic design, there are two major color models: RGB and CMYK models.

RGB stands for Red, Green, and Blue and it is majorly used for screen-based (or web-based) images. The RGB model is an additive color model based on the mixing of visual light (meaning the color becomes brighter with more mixing). Since the RGB model is based on the color space for visual light, digital images from measurement devices (e.g., camera, microscope, scanner) are also generated in the RGB color mode as the image sensor reads the intensity of red, green, and blue signals from the input.

CMYK stands for Cyan, Magenta, Yellow, and Key (black) and it is majorly used for printed images. CMYK model is a subtractive color model based on the painting of color (meaning the color becomes darker with more mixing). Since the CMYK model is based on printed/painted colors, it is the standard color model for printing-based publication including academic journals and magazines (except online-only journals).

While it is not common to distinguish RGB and CMYK color models in scientific research and figure preparation, it is often an important consideration for a certain type of image data. For example, a fluorescent microscope takes all original images in the RGB color models. However, because of the difference in RGB and CMYK color spaces, the same image becomes slightly different in color when it is being saved in the CMYK color model (which is the standard for most printed paper figures) as shown in the above image (confocal microscope images of rat tissue with green and blue fluorescent channels). Hence, it would need the care to keep the original color model for image data in analysis and use the consistent color model in figures to avoid visual confusion and/or misrepresentation of data.

Tip 1 – Use resources for in-depth learning
The use of color in data visualization is a very important technique in various research fields where the graphical representation of a large amount of data is required. Given the depth of the topic, I wish to introduce several very useful resources instead of diving too much in this tip post:

• Ten Simple Rules for Better Figures by Rougier et al.
• Your Friendly Guide to Colors in Data Visualization by Lisa Charlotte Muth
• Simple Tools for Mastering Color in Scientific Figures by Patrícia Chrzanová Pečnerová

Tip 2 – Make a color code for each paper
Inconsistent use of colors in figures is one of the most common sources of bad data visualization and reader experience. Hence, it is very useful to build a color code for each paper before preparing figures based on which you can ensure consistent use of colors in all figures in the paper. There is no strict rule for color codes but there are several points to consider. I also provide various example color codes with a downloadable Illustrator file below.

• Do not overuse different colors.
• Light to dark gradient based on few color choices (or theme colors) can give the feeling of consistency and orderliness.
• Avoid the use of saturated colors.
• Use complementary colors wisely.

Various color codes (AI file)

​As a more practical example, I provide the color code (with a downloadable Illustrator file) that I used for this paper.

Example color code (AI file)

Tip 3 – Use color wisely
Colors in scientific figures can be very effective tools to aid understanding and delivery of information to the readers. For example, different colors can be used to highlight an important step or part in your experiment/data as shown in the below examples. With right and smart use, colors can be one of the most effective tools in our scientific communications.

Example 1 – Highlights in chemical schemes

​Tip 4 – Be mindful of color-vision deficiency & color-blindness
The main purpose of scientific figures and colors in them is to aid communications of our scientific findings. Hence, it is important to be mindful of the inclusive use of colors for our colleagues with color-vision deficiency and color-blindness. Thankfully, this topic has been well studied with scientifically derived guidelines and suggestions to learn such as this paper (this is a must-read article!).

​​Disclaimer. The contents are my personal opinion and do not represent the view of any institution or company I am affiliated/employed. If you find any incorrect information, please feel free to let me know via my email.

​The capability to use tools has given humankind enormous power to enable many things. It’s not a very different story for scientific figure preparation! While there is simple software like Microsoft Painter (my first digital drawing software) and Microsoft PowerPoint (which is surprisingly popular among researchers to “draw” things not just for presentation slides), more dedicated professional graphic design software can definitely be a great help. In this tip post, I wish to introduce several common and popular design software for 2D and 3D graphics.

2D Graphics
In scientific figures, 2D graphical elements (schematic illustrations, plots) are the most common type of graphics. 2D graphic design software can be divided into two categories: vector and raster design software (for more information on vector vs raster formats, please check this tip post).

Let’s start with 2D vector design software. Despite being commercial with a relatively high price (although cheaper with academic discount), Adobe Illustrator has become a dominant software for 2D vector design in scientific figure preparation due to its ready compatibility with other commonly used Adobe software packages (Photoshop, Acrobat, InDesign, etc) as well as broad adoption in the publishing industry. I also use Adobe Illustrator for most of my 2D graphic design for scientific figures, so the upcoming tip posts will be mostly based on Adobe Illustrator.

However, there are open-source alternatives that are freely available with comparable functionality. Among them, Inkscape is one of the most popular and powerful alternatives to Adobe Illustrator. Note that many standard vector graphic formats (.eps, .svg, .pdf) are compatible across different software, so the choice of software can be made based on the availability (often through university/institute software volume licensing) and personal preference.

Next is 2D raster design software. Unlike non-scientific purposes, raster graphic design has very limited use in scientific figure preparation. The main reason is that inappropriate manipulation of raw image data (commonly in raster formats) is a major concern regarding research ethics and integrity. Hence, it is strongly recommended to familiarize with the guideline for scientific digital image manipulation before using these 2D raster design software (some good reading materials like this and this).

Adobe Photoshop is arguably the most well-known 2D raster graphic design software due to its long history and powerful functions (even photoshopping is in the dictionary). However, Adobe Photoshop is a relatively expensive commercial software package (unless provided by university/institute through volume licensing) and its powerful functionalities are often not really relevant to scientific figure preparation as scientific digital image data mostly need only minimal edits (like cropping, etc). Hence, very simple built-in functions of Microsoft PowerPoint (or Keynote if you use Mac) can be enough for many occasions. If you may need open-source alternatives to Adobe Photoshop, I find GIMP (GNU Image Manipulation Program) can be a great option as a free alternative with comparable functionality.

3D Graphics
While 2D graphics are the most common type in scientific figures, 3D graphics are often useful to describe complicated structures or ideas. 3D graphics are typically prepared by computer-aided design (CAD) software. While the division is not very clear, I roughly divide commonly used 3D CAD software into two categories: engineering CAD and general CAD.

Engineering CAD software is a dedicated program for engineering design & validation that are often incorporated in the curriculum of undergrad/grad programs. While engineering CAD software is not mainly used to make scientific figures, their capability to build 3D models of complicated structures with specific dimensions and design parameters together with photo-realistic rendering function fits perfectly for 3D graphics for scientific figures. There is many engineering CAD software, but I am most familiar with Solidworks and Autodesk Inventor (probably because I am a mechanical engineer). While the upcoming tip posts will focus more on 2D graphics, I will use Solidworks for 3D graphics although the general approach should be similar in different CAD software.

Apart from engineering CAD software, there is a range of general CAD software for more general design purposes including animation, games, etc. One key difference between engineering and general CAD software is the extensive design validation functionality. General CAD software focuses mostly on building 3D models and their photo-realistic rendered images. Among many general CAD software, SketchUp (popular in architecture design) and Autodesk 3DS Max are pretty commonly used for various purposes. Note that these engineering and general CAD software are commercial and very expensive (unless provided by university/institute through volume licensing). Blender is a great open-source free alternative for commercial CAD software for 3D model building and rendering.

​Disclaimer. The contents are my personal opinion and do not represent the view of any institution or company I am affiliated/employed. If you find any incorrect information, please feel free to let me know via my email.

In the era of digital publishing, scientific figures are prepared and published in digital graphics. Hence, it is useful to know the basics on digital graphics relevant to scientific figure preparations. In this tip post, I wish to introduce the most basic concepts about digital graphics including 1) vector vs. raster images, 2) image resolution, and 3) digital image formats. I also find that this guide document from Nature also provides good information regarding the basics of digital graphics.

Vector vs. Raster Images
Although there are tons of different file formats for digital images, there are two big categories of digital images: vector and raster images.

Vector images are digital images whose geometry is defined by points on a Cartesian plane (2D) connected by lines and curves to form polygons (the name vector comes from the fact that it is made of many vector lines to form polygons). The key benefit/feature of vector images is their capability to being magnified without losing detail/resolution – because vector image is defined by the points on a Cartesian plane that can be easily transformed in the same plane without losing information. It’s linear algebra in action! Because of this capability to keep high resolution regardless of image manipulations (magnification, etc) and easiness in edits without losing details, vector images are the most preferred type for scientific figure preparation for schematic illustrations, plots, and other graphical elements other than raster image-based data.

Raster or bitmap images are digital images based on color information on a predefined grid of dots or pixels (the name raster comes from the fact that it is made of dots in a raster or grid). Raster images are the most common type of digital images because image sensors in measurement devices (camera, microscope, CCD, or photodiode), as well as screen capture, mostly generate raster images due to their straightforwardness (just converting pixel information in sensor/screen into raster image). The key disadvantage of raster images is that their resolution is predefined and degrade by magnifications contrary to vector images (see the above image for example).

Image Resolution
Since the major purpose of scientific figures is the delivery of information, high enough resolution in digital images to clearly convey the needed information is a critical requirement for scientific figures. Vector images have an obvious advantage in terms of image resolution as their resolution is independent of magnification. While some journals adopt vector graphics in their PDF version of papers, still the majority of paper figures are published in raster images (in such cases, original vector images are rasterized). Furthermore, many scientific image data are only collected in raster images. Hence, image resolution is an important consideration in scientific figure preparation.

The most common unit of image resolution in publishing is dpi (dots per inch). Dpi is a pretty straightforward unit – higher dots per inch, higher resolution. The above image shows an example of the difference between different dpi for the same image. 300 dpi is the most common resolution for printing (and therefore, for publishing-quality paper figures), giving high resolution where individual dots are not visible in the human eye. 72 dpi is a common choice of resolution for web-based content, but you can see a bit grainy texture due to the low resolution.

Digital Image Formats
There are a lot of digital image formats, but there are a handful of commonly used formats in scientific publishing. For vector images, EPS and PDF formats are commonly used. AI and postscript (SVG) formats are also used widely. For raster images, TIFF format is the most commonly used one for publishing while JPEG, PNG, and GIF are widely used too. Note that vector formats have a lot higher editability as they conserve individual editable elements instead of making the whole figure into a flattened raster image. Therefore, I recommend using vector format until the figure reaches the final version before rasterizing (if needed). Some journals require the submission of vector format figures to allow appropriate copyediting.

​Academic research papers consist of two main items: Texts and figures. As we call ourselves authors, scientific writing to prepare the texts in academic papers has been familiar ground for generations of researchers old and young, and a well-integrated part of research training in most universities. However, another half of the academic paper – scientific figures – has undergone notable changes in the recent decades. Powered by the technological advances in digital and online publication platforms and computer-aided design software, the scientific figures have seen dramatic changes in style and format from black and white lined schematics with simple plots to magazine-quality color schematics with modernistic charts. As a young early career researcher who has spent a whole research career throughout this trend so far, I have rather complex opinions on this trend with its light and shadow.

On the bright side, the scientific figures might be one of the most benefited parts of an academic paper by the digital and online transformation in the paper publication. Advances in consumer graphical software (such as Adobe Illustrator and Photoshop) have allowed academic researchers with limited design training to generate high-quality and aesthetically attractive graphical elements at ease with their personal computers. Broad dissemination of digital and online platforms in academic journals has allowed the publishers to support the larger and bigger color figures in a more reader-friendly format at much lower or no cost to the authors. More complicated, colorful, information-rich, and attractive graphics in scientific figures have appealed to not only academic audiences but also the general public as visual aids to help them better understand sophisticated academic contents, partly helping the broader outreach of academic outcomes as well as democratization of scientific and technical findings with help of journalists and popular media (including social network services such as Twitter, Facebook, LinkedIn).

On the darker side, the changing trend in scientific figures has been somehow too fast compared to the corresponding adaptation in academic research training and curriculum. As there are clear financial (larger revenue from the higher number of viewers/subscribers – especially from the general public) and non-financial (more citations and media attention) benefits of publishing papers with figures with aesthetically attractive visuals for the academic publishers, the trend of favoring visually elaborated scientific figures have quickly become conspicuous in many research disciplines, particularly in highly popular/prestigious journals. However, the necessary set of graphical skills and training to catch up with this trend was not part of the traditional academic training for graduate students and postdocs, generating a substantial curriculum/training vacuum for the skills that might critically affect their academic career even for the most recently trained PhDs.

Despite many advantages on the brighter side, the sobering curriculum/training vacuum in the current academic system to deal with the trend of fancy scientific figures has generated several problems. First of all, the lack of established training to help researchers to learn and practice the needed graphical skills in the combination of the recent trend of the ever-increasing importance of high-quality and attractive figures in academic paper publications creates a worrisome disparity between researchers/institutes/research groups. Researchers with graphical training experience or research groups/institutes with plenty of resources to get professional graphical help can enjoy significant advantages over researchers/research groups that do not have access to such resources. Second, the scarcity of good graphical skills to follow the trend somehow strengthens the favoritism on graphically attractive scientific figures, rendering it more like merit of academic work on top of the traditional qualities of good science (such as a novel idea, rigorous data and analyses, insightful discussion, etc) – which might be most conspicuous in highly competitive journals not surprisingly following supply & demand rules as like all other human activities – that is a particularly worrisome aspect to me. Third, researchers face significant burdens to learn the needed graphical skills under pressure from the ever-stronger trend in recent years but in a highly inefficient manner due to the lack of readily accessible curriculum, training resources, and guidance.

What can we do to make this better? One might argue that the recent trend in scientific figures is just wrong, and we have to revert to the old good simpler days. I personally like the idea, but it is also true that such regressive change might not likely given that there is a good number of advantages and strong merit to participants in the system (including scientific publishers) to continue or even fostering the current trend. As an early career researcher who self-learned many graphical skills to follow the trend, I think that the more realistic and practical way would be gradually building training strategies, curriculums, and accessible resources for the current and future generations of researchers to catch up with the trend on the academic side of the world.

So, I plan to cover tip posts focusing on various aspects of scientific figure preparation to share my experience and skills. Since I got most of the graphical skills that I use daily basis in more or less self-learning mode, the tip posts on this topic might be a bit less organized and eclectic (so I may not put part numbers and organize posts on Table of Contents page dynamically). In rough categories, I will cover the following items:

Tools and techniques

• Graphical design software (with particular focus on Adobe Illustrator)
• Useful skills for schematics (2D and 3D)
• Useful skills for plots
• Photo/videography

Graphical design basics

• Basics on digital graphics
• Basics on color
• Basics on layout

Examples

• Step-by-step examples for published figures I drew before

I will try to accompany each tip post with downloadable and editable example files to aid the readers (and hopefully short screen-recorded videos too if applicable). While it would be a limited resource reflecting limitations of my own experience and skills, but I wish the upcoming tip posts can be useful for fellow researchers.

Disclaimer. The contents are my personal opinion and do not represent the view of any institution or company I am affiliated/employed. If you find any incorrect information, please feel free to let me know via my email.

Finally, this is the last post on a journey to publish a paper. Let’s assume that you just hear the good news that you have waited for so long time – the editorial decision of acceptance! Well, what should be the first thing to say? Congratulations and congratulations! It’s the moment that you can forget all the ups and downs during the publication process and just celebrate. I sometimes think that I can endure all those hard and lengthy publication processes in every paper just to enjoy the short burst of joy when I see the acceptance decision. We should not be addicted to it as our driving enthusiasm to do research is doing good science and make a positive impact on our society, not publishing papers, but we still can sometimes be less serious on our scientific mind when we have to celebrate time to time.

While varying in different journals, the following items/steps would be a list of things you can expect after acceptance to the publication of your paper:

• Editorial requests to follow the house-style of each journal
• Copy-editing of your manuscript
• Administrative documents (licensing agreement, third-party copyright documents, etc)
• Proof-read of your copy-edited paper

This post is very short because there are not many things left once you finally reached the acceptance of your paper through all the hard journey toward publication. However, there are several post-acceptance activities you can consider.

Cover image suggestion
Many journals ask/allow the suggestion of potential cover images from the authors along with their acceptance decision. While it is completely optional, sometimes you may have really cool ideas on potential cover images. Cover image selection by the journal may reflect more on artistic aspects than scientific aspects but it is still a very nice way to publicly introduce your research work in a more graphically visible way. Typically, you can consider a cover image suggestion based on illustration (for example, left one below) or photography (for example, right one below).

In my opinion, both illustration and photography have their merit, and probably the suitability of each approach may depend a lot on the characteristics of your research. To prepare potential cover image candidate(s), you can do it yourself if you are familiar with illustration/photography, but you can seek some professional help/service as well. There are several very helpful books and resources on scientific photography and other techniques (for example, book and MIT OCW lecture from Felice Frankel). There are several scientific illustration service companies out there (for example, this company I sometimes use; just as an example & not advertisement purpose). Also, your school/department media offices might have professional illustrators or photographs to whom you can ask for help.

Press release (PR)
While publicity endeavors in the form of a press release (or more commonly called PR) and media coverages are not a major goal of research as well as publication, they are kind of nice by-products. I think that the rapid rise of active PR of academic research in the recent decade is rather controversial considering it brings both positive and negative aspects. So, I wish to be cautious on this subject, strictly limiting to my personal views from experience which should not be generalizable. Given that we do not chase publicity via PR and media highlights as the primary/major goal of our research, I see them as nice outreach opportunities for researchers to disseminate their work beyond the traditional academic audiences (which can be very narrow for certain fields) as positive by-products of good science. Since the majority of research projects are somehow funded by the general public (via taxpayers’ money in the form of governmental or public grants), it might probably make sense to give some effort to share our good and hard-done science to the general public with help of the journalists.

There are two major ways for PR or medial highlight of the accepted papers upon or soon after their publication. The first way does not involve your effort as journalists who are interested in your work cover it themselves. Many journals post the accepted paper near its publication in the journalist-accessible platform with the paper, associated media resources, and embargo information (the date/time after which the press release can happen – typically on the same day of the publication). In this case, some journalists might find your paper interesting and cover it in their media outlet themselves (potentially with a request for a short explanation or interview with you if they have questions about your work). The second way may need your active input – asking your school/department news office to cover it. Many schools have their own media office and news outlet to cover various things happening on their campus including research activities (for example, MIT News website in the below image which I have worked with many times during my time there). PR through your school/department’s media office can have various benefits as they

• Might be local with availability for in-person interactions.
• May be able to help you to prepare various other media elements (photo, video, animation, etc) along with the PR to better explain your work to the public.
• May have a broader range of media outlets to circulate your work (social media channels, etc).
• May be able to provide closer and more interactive communications to ensure your good science is delivered in right and accurate way to the public (which is often very challenging for complicated scientific subjects).

Archiving of project/paper
The last tip but probably the most helpful in the long-term is archiving your finished project/paper in a well-organized form. Like many things in our life, our memory on each paper would eventually face fading and erosion of time. However, many things involved in the research project and paper such as lab notes, raw and analyzed experimental data, experimental setup and parameters, and original figure files should stay organized and preserved for the sake of good science and their continued value in your research group or beyond. In my experience, right after the acceptance of a paper is the best time to do this due diligence for archiving and organizing stuff on each research project/paper as your memory and understanding are the freshest & you may have some room and willingness to do after enduring all the hard processes of publication journey so far. But, because it is the moment of releasing our accumulated stress and pressure on each project/paper, it is also the most vulnerable moment to ignore the job too. Despite all those tempting laziness, I STRONGLY RECOMMEND giving some time to do good archiving of your finished project/paper right after the acceptance – I am sure that you will be thankful for yourself in the long-term.

With this, the tip posts on the publication journey are done. I may continue with more tip posts on other topics.

Part I: Overview 
Part II: Presubmission Inquiry & Initial Submission
Part III: Desk Rejected, What Can be Next Step?
Part IV: Revision, Art of Rebuttal
Part V: Rejected After Review, End of World?
Part VI: Acceptance & Post-Acceptance Jobs (this post)

Disclaimer. The contents are my personal opinion and do not represent the view of any institution or company I am affiliated/employed. If you find any incorrect information, please feel free to let me know via my email.

​If one situation can be selected as the most dreaded moment during a journal to publish a paper, it should be the editorial decision of rejection after review(s). I can easily recall the traumatic feeling of the rejection emails after many months or even over a year for the peer review process and rounds of revisions. Especially for papers you particularly loved and dedicated to, the feeling can be called the end-of-world moment. But it’s common even for the brightest minds in science - Nobel laureates can have their paper rejected (for example, see this article)! Well, the fact your paper was rejected after review does not mean your work will give you Nobel Prize, but it might give some solace to our sour hearts.

Before talking more about how to deal with this tragic event, I wish to share my opinion/experience on why papers got rejected after review(s)?

Why papers got rejected after review(s)?
As with all editorial decisions, the rejection after review(s) is the result of various considerations that the editor has to take into account. Hence, it is not always clear to learn the reasons behind the rejection (although some kind editors provide a brief basis of their decision in the decision letter/email). However, it may still be useful to share my personal opinion/thought based on my experience:

Insufficient novelty. When your paper is sent out for external review, it generally means that the editor found your paper’s topic interesting and potentially fit with their journal for publication. However, the editor relies on external expert reviewers for detailed assessments of your work, based on which the editor can make a more informed decision. In most journals, novelty is one of the most critical requirements for publication and when the reviewer(s) provide well-supported critiques on the insufficient novelty of your work, it might be enough to turn our paper down from the editor’s consideration. This is probably one of the most common reasons for the rejection after review(s). How to make sure your work is novel? You need to do a good job on the literature review (this tip post might be helpful).

Marginal advances over existing works. The reviewer(s) might agree that your work is novel/new at least in part, but they still can give substantial critiques on the impact and significance of your work based on the marginal advances made in your work compared to existing works. While the assessment of significance is more within a subjective domain than the assessment of novelty and technical soundness, the strong and well-supported criticism on marginal advances can still be formidable enough to kill interest in your work from the editor’s mind. This is probably a more common reason in high-profile journals (for example, flagship journals like Nature, Science, Cell, etc) where typically both novelty and impact (or significance/breakthrough) are emphasized.

Insufficient supports for claims. The reviewer(s) might agree that your work is novel and significant. But they still can give substantial criticism on the technical soundness/completeness of your data/method/analysis in support of your major claims in the paper. This is more technical critiques than that on novelty and significance, but strong and well-supported criticism on insufficient supports for claims/hypotheses in the paper can be sufficient reason for the editor to decide not to continue further external peer-review or consideration for publication.

Is the rejection after review(s) the end and you must swallow the bitter taste and look for another journal to submit restarting all the tough journey again? Probably (and sadly) the answer is yes mostly, but also sometimes no in some cases. However, this is not generalizable as each paper has its unique situation. So, I am quite cautious to call these as tips but more wish to share my personal experiences on rejection after review(s) in rough categories and how I dealt with them. Hope it would still be helpful.

Category I – Rejection with fundamental & well-supported critiques
This type of rejection is often a result of strong and well-supported criticism from the reviewer(s) on fundamental aspects of the work such as novelty and significance. Good and professional reviewers might support their critiques on novelty and significance based on the relevant literature references accompanied by their expert opinions and assessments. In my opinion/experience, this type of rejection generally means the end of the process and requires searching for a new place to try. It is tempting to appeal as an assessment on fundamental quality of the paper such as novelty and significance can be subjectively affected by the reviewer(s) personal view. However, it is important to respect the reviewers’ professional assessment and the editor’s decision based on it when they provided well-supported criticism.

But we still can take lessons from the reviewers’ comments and the rejection decision to improve the work for the upcoming refreshing journey. Sometimes, most difficult critiques to shallow might shed light on the best ways to improve our paper. You can carefully check from the reviewers’ and the editor’s comments on:

• Were any obvious prior work(s) missed in the literature review that renders the work not novel?
• Was the claimed significance in the paper relevant and well-supported?
• Did data and analyses in the paper well-support the claimed novelty and significance?
• Was the choice of journal appropriate to get your paper properly evaluated (contents-reviewer pool matching)?

Category II – Rejection with technical & well-supported critiques
This case of rejection is often the result of strong and well-supported criticism from reviewer(s) on more technical issues of the paper such as insufficient supports for claims. In my experience, strong and well-supported criticism on technical insufficiency or incompleteness to support the major claims/findings in the paper can result in both major revision or rejection – while the rejection might come when the editor finds the degree of insufficiency/incompleteness of presented data/analyses is beyond the level addressable by revision(s). While this case of rejection would have much clearer paths to address the concerns of the reviewers and the editor, it would still likely require you to search for a new journal to try. Rarely, the editor might re-consider the significantly revised manuscript where all the reviewers’ and the editor’s concerns and comments are fully addressed in the form of (unsolicited) resubmission, but it would be completely dependent upon the editor. So, I think the default path is finding a new journal to submit, but it would still be possible to ask the original handling editor’s opinion if you would like.

However, there is one important thing to note for this type of rejection. This type of rejection is probably the most informative as the reviewers’ and the editor’s comments and critiques may clearly indicate the parts of your paper to be improved with additional experiments, analyses, and so on. I STRONGLY RECOMMEND taking those comments seriously to address and improve your paper BEFORE you submit to another journal. It is often common to find that the authors submit the rejected paper after review(s) to other journal(s) without any change, hoping more naïve reviewers would pass it easily. It is understandable, but I believe that it is not a good practice for making our science healthy and strong. As a reviewer, we all share our valuable time for free to review other papers to value and maintain our scientific community thriving with rigor, integrity, and excellence. As an author, we should keep improving our work and science based on the valued communications and feedbacks from the peers in return.

Category III – Rejection with erroneous critiques
Alas, this is a nightmare to any paper, but it does happen sometimes although rare. This type of rejection is mostly the result of strong and erroneous critiques from reviewer(s). Here the word erroneous is important – the erroneous critiques are criticism 1) without reasonable and scientifically justifiable support such as reference, 2) based on excessively subjective or unprofessional opinions, and/or 3) based on a misunderstanding of the presented data/analyses in the paper (either intentional or mistaken). How and why do erroneous critiques happen? Probably a myriad of reasons. In a good case, the reviewer(s) might be busy or not very familiar with the topic than they originally expected based on the title & abstract (typically the only information before accepting the review invitation), so inadvertently rely more on subjective opinion than objective scientific expertise; miss or misunderstand data/analyses in the paper. In a bad case, the reviewer(s) might have a conflict of interest such as competing groups – even though this should not be the case as researchers with conflict of interest must decline the review invitation by the most journals’ policy (but lamentably, it is the reality that some people do not keep this simple rule for various deplorable reasons).

This is the case where you can consider appealing to the editor for reconsideration. Different journals might have specific policies on appeal process. But it typically requires the cover letter to the handling editor together with the revised manuscript (where you addressed non-erroneous critiques in full as like typical revisions). In the cover letter, you should be very clear on (yet in concise format) on:

• List of erroneous critiques you identified and brief explanation on why they are erroneous (with detailed rebuttal based on scientifically justifiable supports not your personal objection in the rebuttal/response letter).
• Other revisions you made to fully address other non-erroneous comments.
• Request for potential reconsideration of the decision.

It should be noted that the appeal may or may not change the editorial decision. Experienced editors might notice the errors in the reviewers’ comments and already considered them in their editorial decision. In such a case, your appeal to point out the erroneous critique might not change/affect the editor’s decision. Also, the appealing process is somehow scientifically not productive or rewarding as it is closer to more personalized arguments than scientific discussion (although the fault would be on the reviewers who made erroneous critiques sadly). Hence, I do not highly recommend appeal in general. Considering the devastating and destructive consequences of erroneous reviews and resultant rejection of papers, I think that it is of utmost importance for all of us to do our best to serve our role in the scientific peer-review process with rigor, accuracy, integrity, and honor.

The next is the last tip post on a journey to publish a paper – Acceptance & Post-Acceptance Jobs.

Part I: Overview 
Part II: Presubmission Inquiry & Initial Submission
Part III: Desk Rejected, What Can be Next Step?
Part IV: Revision, Art of Rebuttal
Part V: Rejected After Review, End of World? (this post)
Part VI: Acceptance & Post-Acceptance Jobs

Disclaimer. The contents are my personal opinion and do not represent the view of any institution or company I am affiliated/employed. If you find any incorrect information, please feel free to let me know via my email.

​After your paper is sent out for external review, the upcoming weeks to months are long waiting for the peer review comments and the next editorial decision. When I only had waiting experience, it was sometimes hard to understand why the peer review takes so long time while most journals say their recommended period to solicit comments from reviewers is 2-4 weeks. The closest experience to waiting for the peer review reports and the editorial decision in my life outside of academia is waiting for items purchased from the opposite side of the planet during the Christmas season. But, as I am in the shoe of a reviewer more and more, I gradually understand the agonizing slowness of the review process (but not for all cases though). It’s basically goodwill-based voluntary free service to the community and career researchers are often flooded with routine works to flush every day, often pushing peer review tasks down to the priority in their to-do list (if not completely forget about it). While I have tried to meet the review deadlines as faithfully as possible, I confess that I also delay a lot sometimes regrettably.

But don’t worry! – the editors and editorial staffs of most journals are amazingly good at chasing delaying reviewers with endless reminders to the level of spam, so it will eventually come to you with the editorial decision (at least based on my experience). One tip is just forgetting about the paper during this period and let the editorial decision with peer review reports visit you like a surprise event. Once your surprise day comes, what matters is what type of surprise it is – like a surprise birthday party with super positive referee comments accompanied with the editorial decision of acceptance or minor revision; or like a sudden disaster with super negative referee comments accompanied with the editorial decision of rejection; or like mixed feeling with partly positive and partly negative referee comments accompanied with the editorial decision of major revision or resubmission. After surprise calming down, life has to move on – so let’s talk about these to discuss and share some tips on each scenario.

Scenario I – Acceptance/Minor Revision
If most reviewer comments are positive with only minor points for revision, you may get the editorial decision of acceptance or minor revision before acceptance. This is the best outcome you can expect, and your paper is just a step before publication. Based on my personal experience, it is not very common to get acceptance or minor revision in the 1st review round, especially in highly competitive journals. More commonly, you may need to undergo several rounds of major revision/resubmission until getting to this point, sometimes taking many months to over a year.

In this case, you may be requested to do minor revisions to address the editorial comments (on format, style, publication-quality figure preparation, etc) as well as any remaining minor concerns from the reviewers for the final revision. There is not really much tip on this case as it is pretty straightforward most of the time (as you might already address all hard things in the prior steps). One good thing to remember is that it is important to carefully check and correct any remaining errors in your paper that were missed during the scrutiny by the editor and the peer reviewers before submitting the final revision package. In most cases, your paper may not return to the reviewers in this case before the production stage (typesetting for publication, etc), so you have to make sure everything is correct. Borrowing some fresh eyes from your colleagues for proofreading can be a good idea.

Scenario II – Major Revision/Resubmission
When the reviewers’ comments are mixed in opinion while the editor thinks that they are still reasonably addressable, you may get the editorial decision of major revision or resubmission. Major revision and resubmission are different in principle, but their difference is often not very clear depending on the journal’s policy and the editor. In some sense, they are quite similar as the task you have to do is essentially the same – performing the art of rebuttal to address the editor’s and reviewers’ comments in full. The major revision is typically the most effort and time-intensive part of the publication journey. It is a professional and collegial written debate between you and your reviewers judged by the editor with the stake of deciding whether your paper is suitable for publication in the journal. Like sports matches, the major revision can go multiple rounds until the reviewers being satisfied or the editor calls the end of the process like a judge (although very rarely).

The revision of each published paper has been pretty much behind the curtain without public disclosure, but the recent transparent peer review policy in many journals starts to allow people to take a look at the reviewers’ comments and the authors’ response published together with the paper (for example, below image from Nature Communications website) if the authors decided to opt-in. I think it is a very nice way to learn a variety of successful revision examples (as the paper was eventually published).

Considering the diversity of reviewers’ comments in different papers, fields, and journals, it would be impossible to have a universal strategy for the revision. However, there can be several tips to consider in general.

Tip 1. Be professional and polite. As mentioned earlier, the peer review process in the form of the review comments and the response or rebuttal letters is a professional and collegial debate. Hence, it is absolutely important to keep a professional and polite tone throughout the revision process in your response/rebuttal and cover letters even though the reviewers might give unprofessional comments (sadly sometimes it happens). Keep your rebuttal of the reviewers’ critiques in your highest standard of professionalism based on science and evidence-driven rational thoughts.

Tip 2. Be objective not subjective. Views and opinions can vary a lot even in science and engineering where data, logic, and rational mind should prevail over personal opinions. Hence, it is not rare to find that the reviewers disagree with your findings or a certain part of the work based on various reasons and reasonings of their own. Really sadly, although rare, some review comments might contain more subjective disagreement or criticism than they should be due to many reasons (academic competition or some other form of conflict of interest – despite most journals’ policy ask the reviewers not to accept review invitations in such case). But it is of utmost importance that your rebuttal should be objective not subjective in any case. To be objective in your rebuttal of the reviewers’ critiques, you can rely on science and let the science speaks for you – for example:

• Original or newly added data in the manuscript
• Original or newly added (standard or established) analyses in the manuscript
• Reference to support your claim in the literature

Tip 3. You can disagree but do it in right way. It is not always possible or the best to agree with all of the reviewers’ critiques, so you can definitely disagree. However, it is important that you have to do it in the right way when you disagree – disagreement based on scientifically justifiable reasons not your personal objections. While the reviewers of your paper should be experts in their own field, but it is possible that they might misunderstand your work or simply mistakenly miss some important aspects during the review resulted in some erroneous critiques (as common human errors). In such case, you can politely disagree with the erroneous critiques and provide scientifically justifiable reasons (for example, data, analyses, references in the literature, etc) to help the reviewer to notice their error and facilitate the improved communication with a better understanding of your work.

Tip 4. Focus on fundamentals. Since the reviewers’ comments can be highly technical based on their expertise, it is often possible that the critique becomes unnecessarily peripheral. Based on my experience as both an author and a reviewer, a high technicality of the peer review process can yield comments expressed in a peripheral technical manner (referring to the technique, material, analysis the reviewer is familiar with) even though there are more fundamental aspects to be addressed behind perceived by the reviewer. Hence, although the basic principle of the revision and rebuttal is fully addressing the reviewers’ comments, it is possible that you lead the discussion wisely to avoid being peripheral by focusing on the fundamental issues to be addressed based on the reviewer’s critique instead.

For example, the reviewer might recommend and insist on a certain experimental technique because the reviewer thinks that your original manuscript lacks information from such technique/analysis to offer a better understanding or support to your findings/claims. It can be a very tough comment to rebut if the recommended technique or method is very specialized or hard to access in your research environment. However, you can always focus more on the fundamental aspects of the reviewer’s critique and try to address it in a way you can reasonably and realistically do. For instance, if there are more accessible alternative techniques/methods to you that would provide similar/equivalent information like the recommended one, you may try them and explain in your rebuttal response by focusing more on the fundamental aspects of the critique.

Tip 5. Use figure/table wisely. Most of the time, the response/rebuttal letter to the reviewers is a separate document from the revised manuscript (and the revised supplementary information). However, it is not always intuitive or easy to keep tracking the referred revision in the response letter if it requires checking the revised manuscript and supplementary information back and forth whenever encountering the mention of newly added or revised figure/table/sentences in the response (yes – this is very personal experience as a reviewer – but I believe this is pretty commonly shared experience). It can be a great idea to include the revised figure/table/sentences as part of the response/rebuttal letter when you mention them to help your tired reviewers and editor to go easy on checking your revised manuscript. I believe that they will appreciate your kind help.

Tip 6. Use cover letter wisely. While the most important part of the revision is well preparing the response/rebuttal letter to address the reviewers’ comments/concerns/critiques in full, the revision cover letter to the editor is also an important part of it. Since the editor is a judge who makes editorial decisions based on the external reviewers’ comments as well as your revised manuscript, it is important to ensure the editor understands and knows the scope, extent, and thoroughness of your revision in response to the reviewers’ comments. The revision cover letter can serve as an effective way to summarize your revision for the editor and aid their next editorial decision to accept or send out to the original/additional reviewers for further peer review.

There can be various ways to prepare the revision cover letter, but I wish to share a template for revision cover letter that I frequently use (also below image):

​Scenario III – Rejection
Sorry, this is something you definitely don’t want to see. But sadly, it is very common to see the rejection editorial decision after the external review, often many times for one paper during its journey to publication. Most researchers would have an acceptance-to-rejection ratio (or ATR, just made up similar to signal-to-noise ratio (SNR)) far lower than 1. So, you don’t need to be overly frustrated – you are part of the disappointed researcher club. However, the rejection email on the paper that you poured love and tons of effort (especially after multiple rounds of major revisions) would break your heart and crush morale. I believe that it may need more dedicated discussion in the next post.

Part I: Overview 
Part II: Presubmission Inquiry & Initial Submission
Part III: Desk Rejected, What Can be Next Step?
Part IV: Revision, Art of Rebuttal (this post)
Part V: Rejected After Review, End of World?
Part VI: Acceptance & Post-Acceptance Jobs

Disclaimer. The contents are my personal opinion and do not represent the view of any institution or company I am affiliated/employed. If you find any incorrect information, please feel free to let me know via my email.