31 Dec 2018 by Mark

Year in Review: 2018

Summary: A copy of my end of year message to my lab, where I review the key events from the past year.

This past year the lab grew in a number of ways, both because existing projects that started at the end of 2017 have now hit full steam and because of new project funding that came in over the past year. Looking back with virtue of hindsight, I would characterize 2015 and 2016 as the lab’s “seedling period” where most of the groundwork for today’s projects was laid (e.g., Greg/Ryan/Jessica’s work on the MechProcessor, Wei’s work on Design Manifolds, Faez’s work on diverse ranking and matching) and 2017 was perhaps the “germination period” where we saw a number of projects take root and bring on new members. With that analogy, I consider 2018 the beginning of the “blooming period,” where we really got to see our hard work pay off with a series of exciting papers and new projects that have expanded the what our lab is capable of. Honestly, this has been the most intellectually fulfilling year of my career and a ton of fun! I have all of your hard work to thank for that. I am truly humbled to work with such a great group of researchers.

The People

The best parts of my lab are the people, so I wanted to start my 2018 review by noting some of the important departures and arrivals this past year. In January, Kailyn Cage (now Dr. Cage—the first member of her family to earn an PhD!) successfully defended her dissertation entitled “Optimizing Mass Customization through Consideration of Human Variability and Machine Specification Trade-Offs” and walked in the May, 2019 ceremony. Kailyn has since taken her immense talents to the SF Bay Area where she started in Amazon Lab 126 (Amazon’s hardware R&D lab located in Sunnyvale). We also bid farewell in May to two undergrad researchers (Josh Land, now a Software Eng. at Appian, and Ashwin Jeyaseelan) who help out in two ongoing DARPA projects. We were joined in the summer by high school interns Jaime Yen (Eleanor Roosevelt HS) and Isabel Beariault (Holton Arms HS) who were investigating materials for soft-robot design and locomotion. Jaime continues with us through May 2019 as part of ERHS’s research practicum (looking forward to the Science Fair next spring!). In the fall, we also welcomed Rachel Hess as a M.S. student working on our new NIH project and also Dr. David Anderson who joined us in November after finishing his Ph.D. under Kris Wood at SUTD. Lastly, in the next few weeks, Dr. Dan Elton, who has been with us since Summer 2017 will be taking up an exciting new position nearby as a Staff Scientist at the National Institutes of Health applying deep learning to medical imaging, primarily radiological images (CT Scans) and we will be joined by Dr. Jun Wang who just completed his Ph.D. under Rahul Rai at UBuffalo.

I am continually impressed by the range of backgrounds all of you bring to the table—from mechanical engineering to physics to statistics/applied math to computer science. Many of the ideas we have been exploring together involve the unique intersection of your many fields; for example, connections between differential geometry and generative models, or between type theory and conceptual design, among many others. Such bridges would simply not be practical without you. You really do make the whole greater than the sum of their parts! This expansion outgrew our old lab in the Engineering Lab building, and led to a new lab space in Martin Hall that we are still in the process of renovating. I’m looking forward to building out that space in 2019!

On a related note personal to me, 2018 saw my undergrad Gemstone team graduate from UMD (Team PRINT). While they didn’t spend much time seated in the lab with you all, some of them interacted with you at lab social events and they have been a big part of my life at UMD for the past four years. (Gemstone is a four-year intensive research program where I advised them during their time at UMD.) This culminated with them successfully defending their undergrad thesis and also getting a paper accepted in and presented at IDETC 2018, which I consider impressive considering they were all undergrads not working with a grad student or post-doc. Many of them are off to high-profile jobs or graduate schools, including Microsoft, UC Berkeley, NAVAIR, Textron, UCLA, among others.

The Science

In broad terms, your scientific efforts have led to our most productive year to-date, by almost every measure I can think of. Depending on how exactly you count it, this year we published around 15 papers, more than double that of last year. This includes multiple papers in the flagship journals of my field (including JMD and SAMO), largely thanks to the excellent work of Faez and Wei. They have consistently put forward brilliant work that I think really drives at some mathematical boundaries of my “home” field in unique ways.

Perhaps just as important, however, we also expanded the reach of our work into broader readership journals like Scientific Reports (part of the Nature publishing group) and Machine Learning venues (like ICML and NeurIPS). Here thanks is due to Dan and Zois for their ambition and drive to get our work out there into related fields that lie beyond my traditional publishing community; I have learned a great deal from both of you. We’ve also begun making inroads at bridging design and robotics, particularly via Charlie’s collaborations with Sarah Bergbrieter on soft robotic actuators that he presented at the IROS soft robotics workshop in the fall. Likewise, a collaboration between Wei and Nicholas has resulted in an invited AIAA SciTech submission; I am looking forward to seeing how our work might integrate with the efforts of the aerospace community. I’m enjoying watching all the ways that you are all making design’s contributions more relevant to other fields—it is only through such efforts that we’ll ultimately expand the impact of design to many more areas of society and get out of our academic bubble.

While papers are easy to measure, your efforts have also led to scientific advances in other ways that often more difficult to keep track of. For example, earlier this year, Charlie, Nicholas, and Josh worked immensely hard at the tail end of Phase I of the DARPA Fundamental Design program. Their efforts were rewarded since we were awarded the Phase II funding for the program over some other very deserving and top-notch institutions and companies. Because of their hard work, I have had the pleasure of being invited to give talks at two NASA laboratories (Langley and Goddard), ARPA-E, and United Technologies all of which were interested in building upon our efforts. Charlie, Nicholas, and now David are exploring some honestly foundational work at the core of ML + Design that we are in the process of writing up for 2019. Even if they are only partially successful, they could fundamentally re-envision the basis for computational design in ways that really build on our strengths. If you haven’t had the chance to chat with them in lab about what they are working on, I encourage you to do so.

In terms of new projects starting up, Faez’s work on diversity algorithms last year laid the foundation for a new NSF grant we just received that will explore how idea diversity impacts final solution quality. Wei’s airfoil manifold papers led to the preliminary results that we used to support a new NIH grant on 3D printable grafts for children with congenital heart disease (this is the project Rachel is now on). Charlie and Nicholas’ work via our FUN DESIGN project provided background material that led us to win a Generate Design project with Lockheed Martin over the next year. While I don’t bother many of you with these kinds of details on a day-to-day basis, I think it is important that you see how the hard work and collaborations you set up really do impact the lab’s activities in the long term.

The Field

While there has generally been renewed interest in the combination of ML and Mechanical Design for the past decade or so, it does seem to me like 2018 saw a marked increase the pace and scale of this interest. For example, in the later part of this year, the Journal of Mechanical Design launched a special issue on the topic of Machine Learning and Engineering Design, and then Design Science followed closely thereafter with a special issue on Deep Learning. At ASME IDETC, machine learning tended to be a specialized topic and was even considered an “emerging topic” in DAC as of only 3-4 years ago. Now, by contrast, sessions with significant coverage of Machine Learning occur in all major design conferences, both as full sessions as well as workshops (e.g., I hosted a Deep Learning workshop at Design Computing and Cognition this past summer). Even in venues not specifically targeting design’s intersection with machine learning, we’ve been seeing pickup; for example, in the Special Issue on Design Creativity that Kate Fu, Dave Brown, and I guest edited for Artificial Intelligence for Engineering Design Analysis and Manufacturing (AIEDAM), ML approaches played a part.

This has also been mirrored in a growing willingness by federal and industry funders to explore ML + Design approaches in a variety of domains. As one example, if you take a look at DARPA’s AI Next Campaign (the agency’s current AI portfolio), of the roughly twenty programs listed there two of them are design programs (that’s around 10% of the AI programs). If you had told me five years ago that that would be the case today, I would not have believed you. Interests do tend to go in cycles and I’m not sure how long such trends will last, but for the time being it is certainly refreshing to see academic, industry, and government sectors all giving the intersection of ML and Design a chance. It is now up to us to make sure we deliver the kind of results that demonstrate design’s value, both within and beyond our field!

Alumni News

Occasionally, I’ll get some updates from past lab alumni. Over this past year, we had a visit from Greg Carmean, who is still nearby at NSWC Carderock. We had fun looking at how the campus has changed since he was here and discussed how he is helping modernize how his department at NSWC-CD handles things like code review and version control (yay Git!). I also talked with Ceena Modarres who is still enjoying being up in NYC as a Data Scientist at Capital One after completing the Data Incubator program here in DC. His group there has been doing some cool collaborations with John Paisley’s group at Columbia, and he was actually at NeurIPS a few weeks ago presenting at the AI in Financial Services workshop on some work in explainable deep learning for credit lending. Both Greg and Ceena said to say hi to everyone!

Thanks everyone again for a great 2018, and I’m looking forward to what we can accomplish together in 2019!

The Graduate School Statement of Purpose: A Faculty Perspective

Summary: I talk about writing an effective graduate school Statement of Purpose (SoP) from the perspective of how I (a faculty member in Mechanical Engineering) read it, along with common mistakes I see applicants make. I offer a few tips for students looking to make sure their SoP gets into the right hands and communicates the necessary details so that you’ll have the best shot of getting accepted.

Applying to graduate school, particularly for Ph.D. positions, can be a nerve-racking experience for many students. Part of the stress comes from the all-important Statement of Purpose, where you have the opportunity to represent yourself and your interests beyond what your purely numerical scores (e.g., GPA, GRE, TOFEL, etc.) or recommendation letters might say about you. There are many guides all over the Internet about how to write your Statement of Purpose (SoP) (See Berkeley, Purdue, UCLA, UNI, etc.). I won’t replicate their advice here.

However, to write well you need to know your audience. So rather than talk about how to write a SoP, I want to describe what it is like to read one. By going in the reverse direction and giving you the faculty perspective, I’m hoping you’ll better understand how and why faculty members read a SoP so that you’ll have an easier time writing something that communicates effectively to them. (With the important caveat that this is all my own opinion, and that other faculty may read a SoP slightly differently.)

Why the type of Graduate School program you’re applying to matters

Before we dive into specific details, we need to differentiate between at least three types of “Graduate School” programs (in Science and Engineering):

  1. Ph.D. Program: long-term commitment usually at least four years in length where the primary responsibility of the student is to conduct research with a faculty advisor. This includes M.S./Ph.D. programs where a student receives an M.S. degree during the course of pursuing their Ph.D. degree.
  2. M.S. w/ Thesis: shorter-term commitment, typically two years in length, where the student splits their time between taking graduate courses and conducting a two year research project with a faculty advisor.
  3. M.S. w/ Coursework: like the M.S. w/ Thesis, except without the research aspects; you just take courses of your own choosing and then graduate with the degree. Depending on the student, there might be no primary faculty advisor that you communicate with on a regular basis. This also includes M.Eng. degrees or “Professional Masters” programs.

Why differentiate? Because faculty will expect your SoP to be fundamentally different depending on what your eventual goals are.

Advice for Particular Types of Graduate Programs

For each of the three main programs, I’ll mention: 1. what I’m looking for in the SoP, 2. common mistakes I see applicants make, and 3. suggestions for improving your SoP so it has a better chance of success.

Ph.D. Program

From the faculty perspective, Ph.D. students are a big, but important, commitment. You will develop a long-term professional relationship with your faculty advisor and they will act as a mentor (officially or unofficially) to you for the rest of their life, even after you graduate. Beyond mentoring, faculty provide most of the financial support for their Ph.D. students, for things like tuition, a stipend, any experimental resources they need to complete their research, not to mention hours of one-on-one training. In exchange for these years of training, the Ph.D. student and the advisor will eventually carve out new areas of knowledge that will push forward the cutting edge of science and technology. In short: big commitment and big pay-off, for both the student and advisor, over the course of about 4-6 years.

What runs through my head when I open the SoP

This student is looking primarily for a faculty mentor that will guide their research throughout the course of the Ph.D. I should be looking to see if I’m the right person to guide them. This means I’m paying attention to:

  1. Are they interested in research that is relevant to my area?
  2. Who else in the department could act as good additional mentors to them?
  3. Do their interests align with projects I have going on right now (or wish to start)?
  4. What are their career goals once they get their Ph.D.?
  5. Do they appear to have enough preparation and credentials that it is worth my time to contact them and set up a remote interview?
  6. If they are the right fit, can I find the appropriate financial support for them over the duration of the Ph.D.?

Ideally, the SoP would help me answer the above questions as easily as possible.

Common Mistakes and Suggestions for Improvement

In line with my above points, here are common mistakes applicants make:

  1. The applicant doesn’t say what their research interests are.

    If a student is fantastic (good grades, research experience, great letters of recommendations, etc.), but doesn’t tell me what kind of research they want to do, there is no way for me to determine if I’d be the right advisor for them.

    Suggestion: Be upfront about the kind of research you want to do, preferably in the first paragraph. Say something to the effect of “My research interests include insert broad MechE topic area here, specifically in insert specific sub-fields here.” This way, in the first paragraph of your statement I know whether you are appropriate for my lab or possibly another faculty member’s lab.

    It’s important to strike a balance here. If you say “I’m interested in Mechanical Engineering”, I would say “this student doesn’t yet know what kind of research they want to do, so how do I know if I’ll be a good advisor for them?” On the other hand, if you are super-specific and say something like “I want to work on agent-based architectures for swarm-based, unmanned underwater vehicles” then I might say “hmm, I don’t really have any funded projects specifically on that topic right now, so maybe the student wouldn’t ultimately be happy with my available projects; maybe another faculty member might have something closer to that.” Look over faculty web pages and try to find a happy medium that is specific enough to pique some faculty interests, but broad enough appeal to the projects they have going on.

  2. The applicant doesn’t make it clear which faculty might be appropriate mentors for them.

    If you want to work with particular people but don’t mention them, you are missing a golden opportunity.

    Suggestion: name dropping particular faculty in your SoP is one of the best ways to get those particular people to look over your application. Look over faculty webpages and specifically highlight one or more faculty that you might possibly want to work with. For example, if you really like the work of Dr. X, but could also see yourself working with Dr. Y or Z, then say something like “I am particularly interested in Dr. X’s work on super cool research topic by Dr. X, but would also be interested in related work by Dr. Y and Dr. Z in the areas of research topics of Drs. Y and Z that you like.”

    That strategy is powerful for multiple reasons. First, it shows you did your homework on what people are working on. Second, it demonstrates that you have specific research interests, but also are flexible regarding projects in related areas. Third, it is eye-catching: if I see my name explicitly listed in a SoP, I spend much more time reading it through, since I already know that the student is possibly interested in my specific line of research.

  3. The applicant doesn’t mention what they want to do after they complete their Ph.D.

    If you don’t mention what you want to do once you have your Ph.D., then I can’t determine if I’ll be able to provide the appropriate contacts or support when you graduate.

    Suggestion: mention why you want to get a Ph.D. and what your goals are once you graduate. Do you want to do research at a research University? Teach at a teaching university? Work in an Industry lab? Start-up company? Open your own bakery/circus/boutique coffee shop? Let us know.

    This is important since this helps us determine two things: 1) why do you want to go through the long and arduous Ph.D. process, and 2) are we the best people to provide you with that kind of path once you graduate? If you’re interested in working as a research scientist for Fancy Company or National Lab, and I have many connections or joint-projects with those or similar labs, then I’ll likely be able to give you what you need to succeed.

  4. Not listing skills or experience that match the research field you are trying to go into.

    Your experience and skills should match the job you want. If you’ve spent years doing experimental work, but list heavy computational or theoretical research interests, we may think “This person is really interested in my area, but do they really know what they are getting themselves into? How much extra training will they need to get up-to-speed on the work in my area?”

    Suggestion: make it crystal clear how your past experience translates directly into applicable skills that will be useful when you start. For example, what if you want to join a lab that does computational work? Did you do a project where you had to learn and master C++ programming? Go ahead and mention it! What about your time doing biological research in a wet-lab? Think about how that experience translates to the new lab you want to join and tailor it to them: maybe your exceptional pipetting ability is not worth mentioning, but your data-analysis abilities would be perfect!

  5. It is unclear what options exist to financially support the student.

    Typically students are funded by the advisor out of an active research grant they have at that time. If you express interest in a project related to that grant, and we have money available, it’s your lucky day! However, sometimes things aren’t that lucky: maybe we’re waiting to hear back about a pending grant, or there is a student graduating in one year who is already on that grant, so money won’t be available for a new student on that project until he or she graduates. This could mean that I can’t admit a fantastic student that I normally would because the right funding didn’t line up.

    Suggestion: if you’re open to receiving other forms of funding, say so. For example, Teaching Assistantships might be possible for several semesters while waiting for dedicated research grant funding. Or if your country has some kind of fellowship program (NSF GRFP or NDSEG are examples in the U.S.) that you have already applied for (or anticipate applying for), then you should mention this. If you’re open to different funding options, then that increases the possibility that we can provide continuous financial support throughout your entire time as a Ph.D. student.

M.S. w/ Thesis

For a research-focused M.S. degree, where you are expected to work with a faculty advisor, the same advice from Ph.D. applications above applies. In addition to that advice, you should be specific about your goals for the M.S. degree.

Students apply to a research-focused M.S. program for a variety of reasons: 1) they like research, but are unsure about whether they want to go all the way with a Ph.D., so they test the water with the M.S. + research first and then maybe apply for the Ph.D. later; 2) They just want the M.S. degree, and intend to go into industry upon completing it, but like research and are hoping to cover some of the M.S. costs through a research assistantship; or 3) they want to get into a Ph.D. program, but believe that having an M.S. first before applying for Ph.D. programs will benefit them more than the direct Ph.D. program (this is less useful if you intend to stay at one institution for both degrees).

Whatever your goals, be specific about them, since that will help faculty determine the appropriate level of support, expectations for your application, and how you might fit into the research group.

M.S. w/ Coursework

This type of degree program doesn’t directly typically involve a faculty advisor, and so faculty have less say in these applications and the advice above is less relevant to you. Since these are often reviewed by a department’s graduate office, I don’t have much input here other than to be specific in your degree goals and state concrete ways in which the programs at that particular university will benefit you.

General Tips for Improving Readability

Given the above considerations, there are some general ways that you can make your SoP easier to read:

  1. Organization and Formatting are your Friends.

    SoPs that are well organized, either by using topic paragraphs/sentences or section headings make it really easy to scan through the SoP and make a judgement. For example, bolding the names of research interests or particular professors make it less likely that person will miss that detail in a quick read. You can even use special headings to organize the SoP, such as “Faculty who are closely related to my research interest:” or “Prior Research Experience:” or “Degree Goals:”

  2. Quality Over Quantity

    The longer the SoP is, the more likely the reader is to skip around looking for the information they want, rather than reading the whole thing. Just like a resume, assume that a first-pass read of your SoP will only be ~10 seconds, so you want to get your point across quickly. This means 1) highlight important points in the first paragraph, 2) keep it shorter, if possible, and 3) use organization to make things easy to scan. Feel free to use all the space provided to tell your story, but make sure that if they only read the first paragraph you’d be able to pique the interest of the appropriate faculty member. I’ve seen a SoP with only a couple of to-the-point paragraphs that led me to interview someone, as well as a multi-page, well organized SoP, labeled with clear section headings that allowed me to identify whether the candidate was appropriate within seconds. Length doesn’t matter as much as quality and clarity.

  3. Print It Out and Give it to Someone to Quickly Read:

    Get a friend of yours to look at your SoP quickly and give you their gut reaction. You have been working so hard on it that you’ll know it inside and out, but a fresh set of eyes can be really useful. Is the page too crammed with text that it looks cluttered, busy, and unapproachable? Is it easy for them to find the above mentioned information? Are there spelling or other errors you didn’t catch? Spending one minute with a third party will drastically help you improve your chances on the real deal.

Best of luck!

Contact Information

Email: fuge@umd.edu

Tel: +1 (301) 405-2558

Lab: M0104 Engineering Lab Building

Office Hours: By Appointment, 2172 Glenn L. Martin Hall, University of Maryland, College Park, MD 20742

Can we meet?

During the Fall and Spring semesters, anyone can stop by my office hours (posted above). If I’m not in during my posted hours, I’m likely traveling, and will try to note such times outside my door in advance. When you stop by my office, check the door position:

Door wide open: Come on in and sit down, no need to knock. This applies even if I’m talking to other people.

Door open, but only slightly: Knock first, and then wait for a response.

Door closed: I’m not in, or cannot be disturbed at the moment. Send me an email, leave a note on my door, or come back during office hours.

If you just need me to sign a form and don’t have to discuss the form with me, just go ahead and say so. Don’t stand around for 20 minutes just to get my signature. If we talked about something during my hours that requires me to do something for you, follow it up with an email summarizing what you need me to do, so that it doesn’t fall off my radar. Put “Note from Office Hours:” in the first part of the subject header to jog my memory.

I don’t want to take up your office hours. Can we meet another time?

Generally, group office hours are more effective than one-on-one meetings for several reasons: For classes, students often ask relevant and related questions, and can provide valuable insight on top of what I can offer; by asking your questions around other students, you’ll get to benefit from their experience. For course and requirements advising, this is even more the case, since students often know details about the curriculum that I may not. This also holds for job advice.

For research, there might be some project-specific details that only the two of us would know, but you’d be surprised at how your peers can offer a lense that complements my own. (After all, they are your future colleagues, and these kind of discussions will be pro forma). Also, the research advice I give one student can benefit other students as well.

If you need to discuss something confidential, then come by towards the end of my hours and let me know that you have something to discuss in private. At the end of my office hours, I’ll close my door and we can discuss things in confidence.

Did you get my email, and how long should I wait until I resend you something?

Professors frequently receive hundreds of emails a day. Here are some tips for improving the response time to your messages:

  1. Include specific phrases in your subject line: certain phrases get automatically flagged so that I respond to them faster.
  2. Include the action you want me to do in the subject line: for example, I can process “Project IDETC Sketching Study: Approve IRB Form 7634 in attached link by Tuesday, 5pm” much faster than “Re: Protocol IV-7634 adjusted”.
  3. Make sure I’m listed in the “To:” field if there is something that you need me to respond to or take action on: I check “CC:” or “BCC:” messages less frequently.
  4. If it has been a week since the response, don’t be afraid to follow up again. Sometimes, when there are lots of important things going on, messages can get lost or buried in the shuffle. Professors have at least seven bosses, constantly requesting things from them, so make sure to be pro-active and follow up.
  5. Get on my critical path. Response rates will increase dramatically.

If you need a response in under 24 hours, you should call my office phone.

Can I do research with your group?

Current Undergraduate Students

We always welcome motivated and talented undergrad students who are interested in conducting research in design. If you are looking for something during the semester, you can come by office hours to chat about possible options. Please check out some of our publications to get an idea of what we do. You can get involved by either volunteering for fun or signing up as an official undergraduate researcher. If you are interested in doing research during the summer, check out the Maryland Summer Scholars program.

Generally, you will work on a specific project with one or more of the lab members so that you can learn what research is like and whether that career choice is right for you. We expect an undergraduate researcher to commit to one semester of 6-8 hours/week or two semesters of 3-4 hours/week in order to get to see all aspects of the research process. If interested, stop by office hours and then send me an email with your resume and transcript (prepend “Undergrad Reseach:” to the subject line).

Current Graduate Students

We often have a variety of M.S.-level or Ph.D.-level projects available for motivated and talented students. Take a look at some of our publications and then stop by office hours so that we can discuss how you can contribute.

Can you write me a Recommendation Letter?

I want all of my students and colleagues to succeed, and I view writing recommendation/reference letters as a critical part of that. I put a lot of thought and time into each of my letters, and often get more requests than I have time to devote to them. Surprisingly, most of the time spent writing a letter is not the valuable “writing” portion, but actually keeping track of destinations and all the background things I need to write a good letter. So, if you want to maximize your chances of me writing you a recommendation letter, follow these steps:

  1. Stop by my office hours or email me to get my permission first (prepend “Recommendation Letter:” to the subject header). The sooner you ask me, the more likely I am to say yes. More than two months before the deadline is great, especially in high-demand times, such as the Fall semester. If the first letter deadline is less than a month away, your chances of receiving a positive response drop exponentially as the deadline approaches. (A rushed letter is a poorly done letter, and I don’t want to do you more harm than good.)
  2. If applicable, ask any graduate student TAs or any Ph.D. students you worked with to email me a summary of the work you did for them and their opinions of that work. Have them put “Reference Letter supplement for your name” in the subject line so I can search for it easily. When you ask them, be sure to make their job easy by summarizing your work for them.
  3. Fill out one of the following online forms. These help me keep track of your letter destinations/deadlines and provides me some more detail about how you want me to position the letter. This will really help your chances of getting the highest quality letter possible.
  4. After filling out the online form, send me one email with all of the following documents attached or linked to (if applicable to the application):
    • Transcript.
    • CV/resume.
    • A draft of your Statement of purpose/Research Statement/Teaching statement (whatever statements or essays are applicable to the letter).
    • Highlight the date that the earliest letter is due. I will submit all of them by that date.
  5. Sit back and wait for my confirmation. I will send you one short email letting you know that I have everything, and confirming the number of letters you listed in the online form.
  6. From this point forward, you can assume with 100% certainty that I will submit your letters on time. You do not need to send me email reminders (if you do, it will only slow down progress on my end). I recognize how important these letters are to you and your career and I consider them one of the most critical documents I write. I will not drop the ball on this.
  7. Once I have submitted all the letters you requested, I might send you one confirmation email letting you know that everything is done. This is a good time to check various online systems and make sure that they received everything correctly. If something is amiss, you can let me know.
  8. Unfortunately, I cannot accept thank-you gifts for writing letters under any circumstances, so please don’t get me anything. The preferred way to thank me is to continue to do fantastic and high-integrity work wherever you end up, and to keep in touch so that I can follow your future success. I didn’t take this job to get chocolate; I took it so that I could help you grow and excel. Your success is my success.

Following the above steps will ensure that I can write you a good letter and will put you ahead of someone else in my queue if he or she did not follow the above steps. If I send you a quick email just directing you back to this page, that means you likely didn’t do one of the steps completely and that I can’t move forward until you do.

Can you participate in my Ph.D. dissertation/proposal/defense committee?

I love learning about new intersecting fields of research, and am generally happy to serve on various committees. I prefer to be a helpful and involved committee member, but also have limited time, which means that I can only handle a few of these commitments at once. This is on a first-come, first-served basis, so it is in your best interest to chat with me as soon as you think you might want me as a member. If I’m already committed to too many students, I’ll have to decline, regardless of how well I know you.

I am fairly open-minded to any research that intersects design. That said, if your topic is so far away from my expertise level that I cannot provide useful feedback, I may have to decline your request. The best way to determine this is to either a) send me an brief paragraph describing your research and how my expertise would benefit your research, or b) stop by office hours to chat about it.

Once I agree to be on your committee you should follow these steps to ensure efficient and high-quality feedback:

  1. Make sure to use appropriate subject headers at the beginning of any emails you send me. This will flag your message as important and will allow me to respond to you faster. For example:
  2. Around 2-4 weeks before any important oral talk (e.g., your defense, etc.), you should email one of my students and have them book you as a speaker during one of our group meetings. Use this opportunity to practice your talk. This benefits my students, since they get to see the format and learn how to ask good questions. It also benefits you, since you can get some feedback that will make you much better prepared for the “real deal” a few weeks later.
  3. Twenty four hours prior to any formal talk that you want me to attend, please email me a draft of your proposal/dissertation/paper etc., so that I can come prepared.
  4. Immediately prior to the above talk, give me a printout of your visual aids or supporting documents. This helps me give you better and more constructive notes and feedback during the talk.
  5. If possible, have someone there (other than yourself) who can take notes for you on any questions that we ask you. I suggest purchasing a high quality, portable audio recorder that you can use to record the feedback if you are unable to locate a designated note taker (always ask permission of everyone if you plan on recording any audio).
  6. Make sure to send me directions to the talk location and a contact number 24 hours ahead of time. I may not be familiar with a particular building and I want to respect both your and my time by not wandering around lost.

What department should I apply to?

I directly supervise students in the Mechanical Engineering Department, so if you wish to work in the lab, you should apply to that department. I frequently collaborate on projects with PIs and students from other departments, particularly in Computer Science, so if you wish to get a degree from a different department you will need to find a primary advisor in that department and then contact me once you get here.

Will you be recruiting new graduate students to your lab this year? For what projects?

Generally, yes, provided there is an appropriate match of skills, interests, and funding. Specifics regarding projects would be determined once your application is processed. For a flavor of the kind of projects we do, check our publications.

Can I be your student?

I don’t see applications until after they pass through general admissions. To maximize the chances that I see your application, follow these steps:

  1. Make sure you apply to the right department: Mechanical Engineering.
  2. Select the appropriate final degree goal you are seeking: If you intend to eventually graduate from UMD with a Ph.D. degree, apply to the Ph.D. program, rather than the M.S. program. If you intend to graduate from UMD with just an M.S. degree, but want to do some research while here, then apply to the M.S. program.
  3. Specify in your application that you are interested in “Design” or “Design and Reliability” (the official sub-division in UMD’s ME department). For the 2015 admission cycle, you can choose one or two “Area of Interest” from about 21 choices in the online form; the ones on that list that I readily check are: “Product Design”, “Computer Aided Design”, “Optimization”, “Software”, and “Design Decision Support Systems”. Make sure that you select one of those categories so that I find your application faster.
  4. Where possible, list my name as someone you’d be interested in working with.
  5. In your essay, explain how your research interests and skills complement the ones we list use in our publications.
  6. Use your essay to demonstrate research effectiveness, and highlight any publications that you have. If possible, link to any portfolio or code samples, such as a GitHub account that demonstrates concrete examples of your skills.

What do you look for in choosing graduate students for your lab?/What should I put in my Statement of Purpose?

In addition to strong research skills related to our publications, we also value the following:

  • Strong ability to communicate effectively in written and oral English.
  • Creativity, humor, and the ability to think “outside the box”.
  • Diversity, both cognitive and otherwise.
  • Ability to quickly pick up new skills, particularly software and programming languages.

For some tips and tricks on writing good Statements of Purpose, check out my suggestions.

I am very interested in your research area. What other schools besides UMD have M.E. professors working on similar research?

We work at the intersection of Design, Machine Learning, and Open Innovation. To locate other professors working at this intersection, check out research published at some of the following conferences: ASME IDETC (particularly DTM, DAC, and CIE), the Design Computing and Cognition conference, CHI, Creativity and Cognition, KDD, and ICED. Also check out the following journals: JMD, JCISE, AIEDAM, Design Studies, Research in Engineering Design, and Computer-Aided Design.

Can I be a visiting scholar in the group

Assuming certain circumstances and alignment of interests, yes, this is possible. Send me an email prepended with “Visiting Scholar:” and note: when and how long you plan to visit, how your stay would be funded, and a brief paragraph describing the proposed research your trip would address and why our lab is appropriate. This way, I can see what kind of space and resources we would have available.

Can I do a Post-Doc with your group?

Because of the level of commitment involved, I will typically only consider someone for a postdoc if I am familiar with his or her research (or if he or she is recommended to me by someone whose research I’m familiar with). I normally must know by Fall of the preceding year to consider someone for a postdoc in the next year. If you fit both of those criteria, send me an email (prepend “Post-Doc Position:” to your subject) and include answers to the following question:

  1. How has your Ph.D. training prepared you for the type of work we conduct in our lab?
  2. What joint research opportunities do you see?
  3. How long of a post-doctoral position were you planning for?
  4. Would the post-doctoral experience be externally funded (e.g., through a government or university fellowship), or do you require funding from one of my grants?

If the right combination of interests and funding exists, we can move forward from there.

How can we begin a collaboration?

There are many ways that industry partners can collaborate with us.

  • Financial support through industry-sponsored research grants: Contact me and I can provide more details (prepend “Industry Support:” to the subject for a faster response).
  • You have some of your own data that you would like to analyze using some of our prior techniques or tools: Let us know and we can collaborate together on the analysis once appropriate agreements regarding publication and patenting are set forth.
  • You have research technologies that complement our skills or technologies and you are interested in pursuing a joint external funding opportunity: we are always interested in collaboration possibilities that combine our respective strengths. Contact me and we can explore proposal possibilities (prepend “Industry Proposal:” to the subject for a faster response).

We would like to hire your best student. Can you put us in touch?

Full-time Employment

Prepare a statement that I can forward to relevant students and send it to me in an email, (prepend “Industry Employment:” to the subject line). Make sure it is specific, concrete, and actionable, so that students know how to interpret it. I should be able to just hit “Forward” without needing to offer any additional explanation myself. No attachments, please. You should also send a representative to Design Day once a semester, as you will have the opportunity to talk our best students and view their work.

Internships for Ph.D. Students

We wholeheartedly support internship possibilities for our Ph.D. students, as it typically affords advantages for both the student and the employer, and promotes better collaboration between our lab and our industry partners. The best opportunities possess the following properties:

  • The internship allows the student to contribute to his or her dissertation research. This includes the option to publish resulting internship research, after we ameliorate appropriate IP concerns.
  • The employer is ok with the student continuing to work in research areas related to the internship. This is a great way to establish a continuing research collaboration and gain visibility for both the company and the student. Obviously, the student would not continue to use proprietary technologies developed while employed at the company, unless specified apriori.

If your internship opportunity possesses these properties, then send me an email with “Industry Employment:” prepended to the subject line, and a self-contained summary of the position that I can forward to my students.

Can your students help me with my design project?

In addition to the advice above, we also teach several, project-based courses where students frequently complete engineering projects. If you have an exploratory project that you would like to propose to student teams in one of our affiliated courses, send me an email with “Industry Course Project:” prepended to the subject line. In that email, give me a paragraph description of the potential project and the course you were hoping to pitch it to. I will then make a determination about whether it looks like a good educational experience for the students and how we might move forward. Also, be aware of the University’s Intellectual Property policy.