Here are a few comments from students who have participated in the Informatics Skunkworks.
I joined Informatics Skunkworks during the beginning of sophomore year, right when COVID started. Even though I hadn’t really done any sort of academic research before, I never really felt like an outsider when I joined the group, and I found that I was able to quickly make contributions to projects even as someone who had never had exposure to materials science before. I definitely credit a lot of my development as a student and researcher to Skunkworks (especially my decision to pursue a career in research), and a lot of it can be credited to the mentorship Dr. Morgan, Dr. Afflerbach, and Dr. Jacobs have provided me over the course of my time at UW. Professor Morgan has done a fantastic job cultivating a community that is able to let anyone of any skill level contribute easily (a rarity!), and I would wholeheartedly recommend Skunkworks to anyone who is even remotely interested in the intersection between machine learning and materials science.
Casey Lin, Class of ’23, 01/17/23 (Applying to graduate schools)
I feel really lucky and thankful to join the Informatics Skunkworks in my junior year when I decided to pursue a career in data science. As a beginner in the machine learning field, the Educational Group led by Benjamin Afflerbach well prepared me to the ML concepts and tools. The research group in natural language processing mentored by Maciej Polak and Prof. Dane Morgan trained me to research independently, learn by doing, communicate effectively with peers, and show the work in the presentation. The most valuable part for me is to learn how to manage the project by proposing new ideas, experimenting the methods, and working with the team. For students interested in ML but don’t know where to start, especially for those worried about their non-CS background, I strongly recommend starting your journey here to try an interesting topic and get a hands-on experience. I ended up in a top graduate program with the help from Skunkworks and I believe you will too!
Shaonan Wang, Class of ’22, 5/31/22 (Starting Master of Science in Data Science program at Columbia University in Fall 2022)
I joined the Informatics Skunkworks at the second year of my undergraduate study (Domain error project, mentored by Prof. Dane Morgan) and I consider it to be one of the most important decision I made during my undergraduate life. My long term goal is to be a researcher and Skunkworks helped me to achieve my goal from several aspects. First, it is a great opportunity to put the knowledge I learned from classroom into practice and gain deeper understanding. As the project developed, I applied knowledge from statistics, machine learning, and later deep learning, which is parallel to my learning outcomes from Sophomore to Junior. Secondly, Informatics Skunkworks was a great place to learn what it means to do “research”. I’d like to say “thank you” to my mentor Prof. Dane Morgan and graduate student Lane Schultz. Compared to the past where I recklessly introduced new method, now I’m a more careful person who is likely to take “baby steps” and control the variation during the experiment. Thirdly, I think the weekly meeting is a great opportunity to practice presenting and communication skills. Trying to persuade people with your findings and advocating for your next-stage plan is a valuable skill. Lastly, Informatics Skunkworks is a great place to meet with people who share similar interest with you so it is a great opportunity to expand your network. In short, my experience was that the Skunkworks group is a supportive community for everyone who is motivate to learn regardless of your personal background.
Yiqi Wang, Class of ’22, 4/20/22 (Starting Master of Electrical and Computer engineering (ECE) program at Carnegie Mellon Univ. Fall 2022)
I joined Informatics Skunkworks in my first month as a freshman and ended up staying for the next three years. With my mentors Benjamin Afflerbach, Ryan Jacobs, and Greg Palmer, I used machine learning models to investigate perovskite semiconductors and predict their electronic properties from their crystal structures. It was one of the most valuable experiences of my undergraduate career. Along with learning how to apply machine learning in research, I gained a deeper understanding of general research skills such as statistics and data presentation. I greatly developed my technical abilities within Python and Scikit-learn along with my soft skills in communication and collaboration with the rest of my team. Aside from fulfilling my own interests, this experience significantly boosted my resume at a time when I had no job experience and helped me get my first internship/co-op offers. I am very grateful to have been a part of this organization, and I absolutely recommend other students with similar interests to try it out.
Aditya Sharma, Class of 2021, 4/8/22
I joined Informatics Skunkworks for almost a year and was a member of the project on information retrieval using Natural Language Processing methods. It was the most valuable experience I had during my undergraduate years. Not only was I able to apply machine learning concepts that I learned from classes to solve various problems in material science, but I also learned how to perform research properly and improve results effectively with the support from our mentor Maciej Polak and Professor Dane Morgan. Throughout the experience, I was able to develop my technical skills in using python and TensorFlow and qualitative skills through communication and coordination with teammates and mentors. I am very thankful to have had the chance to join Skunkworks in my last year of school, and I will definitely recommend anyone who wants to expand their research skills or knowledge in machine learning to join the group.
Ching-Wen (Jasmine) Wang, class of ’21, 12/15/21
I joined the Informatics Skunkworks at the end of my freshman year and I really learned a lot from this valuable experience. Working in the group helps me develop skills in applying advanced Machine Learning models on real-world materials science problems and carrying out research end-to-end including early-stage exploration, dataset preparation, implementation, and final writeup. Moreover, I was also able to present our work in the NextGen program and REU program, which was an awesome opportunity for us to share our work with other students in the field and improve our own work afterwards. The environment in the Skunkworks Informatics is really supportive with all the researchers in the group collaborating efficiently and helping each other on a wide variety of projects. I am really grateful for the support provided by Professor Dane Morgan and graduate student Mingren Shen as I had the opportunity to work on an interesting research project and greatly improve my research skills during the process. This valuable experience and all the skills I learned in the group helped me get admissions to several great PhD programs in Computer Science and will also be very helpful in my future research.
Yuhan Liu, class of ’21, 05/15/21 (Starting PhD in Computer Science at University of Chicago in Fall 2021)
I joined Skunkworks from 2018 to 2020. To me, it was the most valuable and memorable journey of my undergraduate career. I really like its supportive and diverse environment. People with different backgrounds, e.g., material science, computer science, math, have the chance to work together on various applied machine learning projects. They are all very nice and willing to help. Personally, I really appreciated the generous support from Professor Dane Morgan and my mentor Mingren Shen. Under their guidance, I developed solid machine learning skills and more importantly, learned how to do research. Meanwhile, two of our paper for automatic defect detection have been submitted. All of this enabled me to get admitted to a great machine learning Ph.D. program. So if you are interested in machine learning and its applications like me, I highly recommend you to join Skunkworks.
Dongxia Wu, class of ’20, 01/01/20 (Starting PhD in Computer Science and Engineering (CSE) at Univ. CA San Diego (UCSD) in Fall 2021, supported by Haliciolu Data Science Institute (HDSI) Graduate Prize Fellowships).
If you are interested in machine learning and its applications, Informatics Skunkworks is the right place for you. I joined the group with little experience in machine learning. But with examples of more experienced teammates and advice from Prof. Dane Morgan, I was able to start contributing to the team and eventually started to help newcomers to the team. Through experience in Skunkworks, I learned about how to perform research, developed my own research interest, and utilized this experience to get admitted to a great graduate school.
Zuoyi Li, class of ’19, 01/01/20 (Starting Masters in Computer Science at U. Michigan (Ann Arbor) in Fall 2020)
Skunkworks hosted me as a NextGen scholar over summer 2018. I worked on the Automated Defect Detection project where I utilized the neural-network based model named ‘RetinaNet’. Professor Morgan and our supervisors, Mingren Shen and Vanessa Meschke, fostered a supportive environment that allowed fellows to learn at their own pace and seek help when needed. During this time, I was able to explore many new technologies, such as UW-Madison’s HT-Condor high throughput system, which I used to generate learned models. In addition to boosting my software skills, this project also ignited my desire, which has since developed into a passion, for delving deeper into the fields of A.I. and M.L. I’m extremely grateful for this experience. It has given me the confidence and skills to pursue the above fields at graduate school here at UW-Madison.
Varun Sreenivasan, class of ’20, 07/14/20 (Starting Masters in Computer Science at UW Madison in Fall 2020)
Skunkworks has provided me, among many other undergraduates, rare opportunities to research and practice machine learning techniques. Professor Morgan and the other Skunkworks leaders provide an environment where your learning is the priority, and the results and papers follow. It is rare to find a research advisor that cares and invests in his students as much as Professor Morgan. During my time at Skunkworks, I felt that Dane played to my strengths as a researcher, and was patient when I didn’t know something. Skunkworks has been stellar on my resume and has helped me bolster my skills in programming and machine learning. My only regret is that I didn’t hear about Skunkworks sooner!
Nicholas (Nick) Lawrence, class of ’20, 01/28/20
My involvement in Skunkworks has been an extremely rewarding experience. Skunkworks pushed me outside of my comfort zone to delve into something that I had never tried and challenged me to continuously learn how to develop and improve machine learning models. Professor Morgan’s investment in the group and myself as a member has been invaluable. He has helped me develop personally and professionally in areas such as pushing my analytical mindset beyond the classroom setting, professional communication, presentations, and breaking down machine learning theory to develop viable machine learning models. I was encouraged to ask questions and felt continuously supported by my fellow Skunkworks members. My time with Skunkworks has shown that the Skunkworks group has a home for everyone, regardless of whether or not you have past machine learning experience.
Linda Xiao, class of ’20, 10/17/19
Informatics Skunkworks provided me the most valuable experience of my undergraduate life at UW-Madison. Working in this group enabled me to apply Machine Learning knowledge to real-world tasks as well as learn more about cutting-edge Machine Learning topics. Besides boosting my understanding of Machine Learning, Informatics Skunkworks also gave me many other opportunities. During the year I was working in this group, I was able to participate in poster presentation in academic conferences, build connections to ML related industries, and, most importantly, submit a paper to an academic journal. These experiences were a highlight of my undergraduate life and will also benefit my future career.
Xiaoyu (Sean) Sun, class of ’20, 10/17/19 (Started Master of Comp. Data Science (MCDS) program at Carnegie Mellon Univ. Spring 2020)
I would highly recommend joining Informatics Skunkworks to anyone who is interested in applying computer science and machine learning to real-world scientific problems. I spent my final year at UW-Madison on the Skunkworks team and it was one of the most enriching experiences of my undergraduate career. During my time at Skunkworks, I was able to dive into interesting research problems while developing skills in data analytics and computational modeling. I was able to grow as an independent thinker and produce interesting results that will be written up into a journal publication. I plan to take this knowledge and skillset with me into my future academic and professional career.
Elliot Strand, class of ’19, 6/10/19 (Started graduate school at Univ. Colorado, Boulder Fall 2019)
I joined the Informatics Skunkworks at the beginning of my junior year and quickly began a project investigating the mechanical properties of concrete. Through this opportunity, I learned an incredible amount about the research process – from learning the fundamentals of machine learning to coding in Python and, eventually, to writing a paper. The camaraderie of the group was also a major benefit: everyone in the lab was more than willing to answer any of my questions and I greatly enjoyed talking to other members and learning about their projects. My experience with the Informatics Skunkworks fostered my interest in autonomy and artificial intelligence and led me to pursue graduate school.
Michael Hibbard, class of ’18, 8/4/18 (Started graduate school at UT-Austin Fall 2019)
I wanted to express my appreciation for the undergraduate research position your team gave me this academic year. Informatics Skunkworks has helped me learn a lot about how undergraduate research works and what is expected of researchers. I was able to build and strengthen many key skills through my work this year, such as independent working and research presenting. These skills can be used throughout the rest of my academic and professional career.
Ebenezer T. Fanibi, class of ’21 (expected), 5/4/18
Joining the Informatics Skunkworks group was one of the best decisions I made during my undergraduate career. It gave me the opportunity to learn how to do academic research in a very supportive environment, and helped me define my academic interests. I especially enjoyed learning how to apply programming skills I learned in my coursework to research questions. I won a Hilldale Undergraduate Research Fellowship for my Skunkworks project, completed my undergraduate thesis on it, and hope to publish a paper on it in an academic journal. Being exposed to the other projects in the group gave me a taste of the potential of computational methods for effectively answering all sorts of different research questions, and inspired me to look at how researchers outside of materials science use them. I intend to go to graduate school to study computational social science, and my Skunkworks experience helped me get admission to some of the top programs in the field.
Aidan Combs, class of ’19 (expected), Engineering Physics, 4/5/18
My experience working on a Skunkworks project has been very helpful in developing skills that any science or engineering student needs to function in a professional setting. Specifically, solving programming problems independently and in a group, and presenting results in a clear, concise, and convincing way. Professor Morgan and the postdoc students involved were always helpful and patient in helping me to develop these skills. The chance to get involved with the research process with no previous experience also is and will continue to be helpful in my current and future research work.
Josh Perry, class of ’20 (expected), Engineering Physics, 2/12/18
Skunkworks has been the highlight of my college career. After joining the lab my sophomore year as a materials science undergrad without any previous coding experience, I learned I love to program and switched to a computer science major. Skunkworks gave me the opportunity to learn Python, Sci-Kit Learn, neural networks, among other various data mining methods and provided the resources and mentorship to succeed. The lab taught me how to analyze data, work on a team, and how to meet expectations while also never being overwhelming. The skills I learned after a year at Skunkworks also helped me land and succeed at a summer internship. I highly recommend the program to any engineering or computer science student interested in machine learning.
Joshua Cordell, class of ’18, Computer Science, 9/29/17
Being connected with the Skunkworks lab has opened many doors and allowed me to explore and develop my interests in materials science and computer science. During the time I’ve spent with the lab, I’ve been able to develop my programming skills, make connections with a tech startup in California, and learn valuable leadership and time management skills. Professor Morgan particularly has contributed to what I’ve learned at Skunkworks by providing guidance on research tasks while still allowing me to think independently and learn from any mistakes. Working with Skunkworks has helped me find a niche on campus and define my academic interests more than any other experience at UW.
Vanessa Meschke, class of ’18, Materials Science and Engineering, 9/1/17 (graduate student at Colorado School of Mines starting 8/2019)
I spent my final year as an undergraduate joining and contributing to what would become a publication in Computational Materials Science. I was fortunate to stay after graduation as a researcher, where I could mentor new students and was even given the responsibility of managing an investigation. This experience, and being accountable for rigorous, defensible results fostered the mindset and habits that helped me to enjoy success in my work and build competitive credentials that will surely open doors for me. It is sad to say goodbye to Dr. Morgan’s tutelage and the camaraderie of the Skunkworks lab. I’m grateful for having signed up and encourage anyone with thoughts of trying it for themselves to consider the Skunkworks’ undergraduate oriented mission as they weigh their options.
Aren Lorenson, Class of ’16, Materials Science and Engineering, 6/8/17
Joining the Skunkworks was one of the most beneficial activities I did during my undergraduate career. It taught me vital programing skills including Matlab, Python, and GitHub. It also taught me how to analyze problems and formulate solutions using data analytics. Data science is going to be an invaluable skill to have into the future and is already starting to dominate many scientific, business, and health fields. The Skunkworks also gave me a great introduction to how research works at the academic level, greatly improving my resume when applying to graduate school. It directly contributed to my admission to many top graduate schools including MIT, UC-Berkeley, and Northwestern.
Zach Jensen, Class of ’17, Materials Science and Engineering, 6/4/17
Being a part of Skunkworks was one of the most valuable experience in my college life. My Skunkworks’ project was the first time I used machine learning skill in real life. The leading professor and postdoc were always patient and helpful when I met challenges, and there were lab times in which experienced team members provided help for students who just joined. I have learned a lot of technical, teamwork and communication skills in the Skunkworks, and it was a very enjoyable time. I managed to have one paper published based on the project. Furthermore, I also use this experience to build up my resume, which helped me to gain the offer from my dream technology company, Google.
Hoatian (Will) Wu, Class of ’17, Materials Science and Engineering, 5/17/17