If you are interested in conducting visualization or human-computer interaction (HCI) research under my supervision, this page will give an overview of the process. I advise both Ph.D. and MS students, as well as ambitious undergraduates who want to gain research experience and/or complete a Barrett Honor Thesis. Currently, I am not accepting non-ASU students for internships, nor to I have volunteer positions available for MCS students.
What is visualization research?
- What is visualization research? What should it be? by Jessica Hullman
- So you want a (visualization) Ph.D.? by Niklas Elmqvist
Interested in joining the Lab?
- If you would like me to consider you, please note so on your graduate application to ASU. Feel free to reach out via email after you have applied, so I will be sure to see your application. In general, having an online presence gives you a significant competitive advantage. This includes: (1) a LinkedIn profile and (2) a personal website that contains important academic information like any published papers (with links to PDFs), a CV, contact information, a research statement, portfolio, etc. I recommend that you link to these in your application’s statement of purpose or CV!
- If you contact me prior to applying, there is a chance that I won’t respond. Unfortunately, faculty receive many requests for assistantships from prospective students before they’ve applied, which makes it easy to miss emails from earnest students. To help differentiate yourself from the crowd, you can include a brief personal statement describing some of the following:
- Why do you want to do research in the first place (i.e., what types of problems are you passionate about solving)? More specifically, why do you want to do visualization research?
- Why do you think I would be a good fit as your advisor?
- Do you have prior experience doing research or working in industry? What makes you think you be a successful Ph.D. student?
- As above, linking to items like your LinkedIn profile and personal website are highly recommended!
- In your first semester, you are expected to take the Data Visualization gradaute course (CSE 578) and do well in it. The course is designed to be research-focused, so it’s a good primer for future research and allows us to get to know each other better. If you do poorly in CSE 578 or we realize there is a bad student-advisor fit, it’s better for both of us if you switch to another lab.
- If you are interested in doing an MS thesis, you must first take CSE 578. During the semester, come to my office hours and we’ll have an initial conversation. We’ll review your work at the end of the class and make a decision then.
- If you want to do visualization research for your Barrett Thesis, email me with a brief description of what you’d like to work on and we’ll set up a meeting. Be prepared to present a high-level outline of what type of work you’d like to do, what you think the main challenges will be, and a rough timeline describing how you think you can accomplish your goal.
- If you are just wanting to get research experience as an undergraduate, I am also happy to let you join a graduate student’s project if I have an opening. I cannot provide funding for undergraduates, though I am open to letting you conduct research for course credit. In addition, the FURI program at ASU (which you should certainly apply for!) provides a nice stipend for doing research.
Mentoring: I believe that, especially early on, clear communication is extremely important from the advisor to the Ph.D. student. New students in a research field almost always need guidance, especially about what constitutes good publishable research and how to plan and successfully execute research projects. A good analogy is bicycle training wheels; they prevent you from falling over while you’re learning to ride on your own. If you keep falling over, you’ll quickly get discouraged and not want to continue (and your productivity will plummet). When starting out, you’ll be closely mentored either by myself or a senior student. As you gain experience, becoming proficient at conducting projects and publishing papers, you’ll begin to take a leadership role in the lab, mentoring and helping younger students. Depending on your post-graduation goals (get an industry job, become a professor, work in a research lab, etc.), I will work to put you in a position to succeed, such as coordinating internships and networking with other academic institutions. When my students do well and succeed, it not only makes me happy, but it’s good for our lab. I want to make sure you succeed!
Projects: When starting a new project, we’ll discuss projected timelines, milestones, and other expectations. Progress depends on many factors, including your course load and the scope of the project. We’ll continually be reviewing what you’ve completed, what progress should look like going forward, and if the work so far is acceptable (i.e. if you’ve been slacking off). I’m not a fan of what’s called “Least Publishable Unit,” which is producing work that is just enough to publish a paper in a low-tier conference or journal. You should aim for high-quality work that can achieve good impact in a top venue such as the Vis and CHI conferences. Sprinting to hit a deadline usually results in subpar work that’s unlikely to get accepted. While it’s important that you work hard and hit most of your targets, it shouldn’t come at the expense of good research. If you cannot hit a target, we’ll discuss it over and probably decide to push to the next reasonable venue.
Lab Time: I generally prefer students work in the lab, since that facilitates a more-focused work environment, promotes lab unity, and allows for more interaction and discussion together. That said, if you are making sufficient progress on your work, I’m rather lax on when you show up and leave (I usually don’t arrive before 10 am) and you don’t have to come in every day. In addition to 1-on-1 meetings to discuss your current projects and other academic obligations, group lab meetings will occur weekly. We use that time to review the prior week, update each other’s projects and provide feedback, give practice talks, etc. We also have occasional outside activities like lab dinners. At ASU, we do not tolerate any form of discrimination, harassment, or otherwise hostile conduct. Such actions are a good way to get expelled from the program.
Paper Writing: The bullet point about mentoring also applies to writing research papers. Technical writing like you see in research papers is difficult, and it can be doubly hard if English is not your primary language. Especially for your first couple of papers, you’ll start by producing a bulleted outline of all the critical points to make in the full paper. Once this outline is approved, you’ll create a rough draft well before the target venue’s submission deadline. The target timeline for a first draft is at least 1 month prior to the deadline. While this might seem like an enormous gap, you’ll be surprised at how long it takes to refine a rough draft into a polished and high-quality submission! We’ll go over your draft together and discuss edits for the second draft. You will probably have to make multiple iterations to improve the quality. At some point, your lab mates will also read the paper and provide feedback. This is a helpful step, because the more eyes that see it, the more issues get noticed and the better the overall product is. Best case scenario, everything is ready to go in plenty of time; the days leading up to the deadline are for doing minor tweaks and creating a demo video.
Misc. Lab Practices
Programming Languages and Software Stacks: While I have no hard and fast rules about programming languages and software stacks are required, normally we use popular libraries like D3.js, OpenGL, WebGL, and DeckGL for visualization, paired with layers like Flask, Node.js, SQL, etc. For projects that don’t require VR, high-end rendering, or specialized displays (such as tablet displays), web-based front-ends are generally easier, faster to develop, and more accessible compared to desktop applications, plus you can hook them into any programming paradigm you want via the backend server to do data analysis and management. If you’re new to full-stack dev work, that’s okay! You’ll pick it up as you go, though it certainly helps to have prior experience with it (especially front-end and/or interaction design).
Version control: We have a lab GitHub organization that is available for project management, or you may use your own repos. You should always store your code and data using some kind of version control, be it GitHub, BitBucket, etc.
Paper Writing: We write papers using LaTeX (unless there’s some necessary mitigating circumstance). Don’t worry if you’re not familiar with it; I wasn’t either until I began grad school! Overleaf is an online tool for LaTeX which makes it easy to share and collaborate on paper writing. For creating figures in papers (such as for user study results), we normally use libraries like R’s ggplot2.
Bibliography Management: Especially early on, you will read A LOT of research papers to learn what all is out there in the Data Vis field—past work, current trends, and future directions. I highly recommend you have some sort of log, journal, diary, or other management system for organizing the papers you have read. Ideally, you want something that allows for relatively fast review when you might later need to cite a specific paper and how it applies to your current work. When I was a graduate student, I kept a huge Google Doc where I would paste screenshots from papers and jot down summary notes and relevant quotes. Currently, I use a free software called Zotero, which can export bibtex files for LaTex papers.