David Jurgens

David Jurgens is an assistant professor in the School of Information at the University of Michigan. He holds a PhD from the University of California Los Angeles and was a postdoctoral scholar in the Department of Computer Science at Stanford University and prior at McGill University. His research combines natural language processing, network science and data science to discover, explain and predict human behavior in large social systems. His research has been published in top computational social science and natural language processing venues including PNAS, WWW, ACL, ICWSM, EMNLP, and others. His work has won the Cozzarelli Prize from the National Academy of Science, Cialdini Prize from the Society for Personality and Social Psychology, best paper at ICWSM and W-NUT, best paper nomination at ACL and Web Science, and has been featured in news outlets such as the BBC, Time, MIT Technology Review, New Scientist, and Forbes.

How he got there: Before joining UMSI, David was a postdoctoral scholar, jointly in the the Stanford NLP and SNAP Groups under Dan Jurafsky, Jure Leskovec and Dan McFarland. Prior, he ventured beyond the wall to the cold regions of Montreal (don't let the idyllic summers fool you) and was a postdoctoral scholar at McGill University in the Network Dynamics group with Derek Ruths. Before finishing his PhD, he was a research scientist at the Linguistics Computing Laboratory at Sapienza University of Rome under Roberto Navigli. During his PhD, he was concurrently a visiting researcher at the Information and Systems Science Lab at HRL Laboratories. After trips abroad and to Malibu, he received his PhD in Computer Science from the University of California, Los Angeles under Michael Dyer. Early in his career before he discovered you could study language and people, he received his BA in Philosophy and Political Science and an MS in Computer Science on Computer Vision under Robert Pless from Washington University in St. Louis.

Fall 2017, 2018: SI 671 -- Data Mining: Methods and Applications

Winter 2017—present: SI 630 -- Natural Language Processing: Algorithms and People

Fall 2020—present: SI 650 / EECS 549 -- Information Retrieval

Winter 2023: SI 330 -- Data Manipulation

Fall 2019: SI 710 -- PhD Seminar: Computational Sociolinguistics
A new course! On computational sociolinguistics! With actual computation and actual sociolinguistics! If any of that excites you, drop me an email and I can share more details.

Being a faculty involves too many things to reasonably keep track of so this page is just left out of date in favor of staying sane. For folks who are very interested still, please see my CV for a more up-to-date list.

Current

• Co-editor of a Frontiers special issue on Computational Sociolinguistics. The journal has a rolling deadline so feel free to submit here, or just read the papers as they appear.
• Area chair for Social Media for ACL and EMNLP
• Sponsorship chair for ICWSM 2019.
• Senior PC for WWW 2020 (Web & Society)
• Co-chair of the International Workshop on NLP and Computational Social Science at ACL-2017 with Dirk Hovy, David Bamman, Oren Tsur, and Svitlana Volkova.

Past

• Data Chair for ICWSM 2017
• Co-chair of the International Workshop on NLP and Computational Social Science at ACL-2017 with Dirk Hovy, David Bamman, A. Seza Dogruoz, Brendan O'Connor, Oren Tsur, and Svitlana Volkova.
• Co-chair of the International Workshops on NLP and Computational Social Science at EMNLP-2016 and at WebSci-2016 with Dirk Hovy, David Bamman, A. Seza Dogruoz, Jacob Eisenstein, Brendan O'Connor, Alice Oh, Oren Tsur, and Svitlana Volkova
• General reviewing habits Program Committee at various (most) times for WWW, ICWSM, NAACL, ACL, EMNLP, CSCW, LREC, EACL; External Reviewer for CHI (rarely).
• Co-chair of the International Workshop of Semantic Evaluation (SemEval) workshop in 2015 with Daniel Cer, Preslav Nakov, and Torsten Zesch and in 2016 with Daniel Cer, Marine Carpuat, and Steven Bethard
• Co-organizing SemEval-2016 Task 14: Semantic Taxonomy Enrichment with Mohammad Taher Pilehvar.
• Co-presented the tutorial "Semantic Similarity Frontiers: From Concepts to Documents" with Mohammad Taher Pilehvar at EMNLP-2015 -- over 150 registered attendees!
  Check out our annotated bibliography of recent semantic similarity papers on GitHub.
• Co-presented the tutorial "Multilingual Semantic Processing" with Roberto Navigli at LREC-2014
• Co-organizer of SemEval-2014 Task 3: Cross-Level Semantic Similarity with Mohammad Taher Pilehvar and Roberto Navigli.
• Co-organizer of SemEval-2013 Task 12: Multilingual Word Sense Disambiguation with Roberto Navigli and Daniele Vannella
• Co-organizer of SemEval-2013 Task 13: Word Sense Induction for Graded and Non-Graded Senses with Ioannis Klapaftis
• Co-organizer of SemEval-2012 Task 2: Measuring Degrees of Relational Similarity with Saif M. Mohammad, Peter D. Turney, and Keith J. Holyoak
• Journal Reviewer: Artificial Intelligence, Behavior Research Methods, International Journal of Corpus Linguistics, Language Resources and Evaluation, Natural Language Engineering, PLOS ONE, Transactions on Knowledge Discovery from Data (TKDD)

Broadly, I conduct research in the areas of natural language processing, computational social science, and data science to discover, explain and predict human behavior in large social systems. My current research focuses on four central themes spanning these fields:

• Who are the people communicating? Humans create nearly all of the text we see, yet often who is communicating is overlooked. I design new methods for identifying the demographics of communicators in order to understand large social systems.
• How are people related? There are certain things you would tell your friends but not your mother. Yet, when we study peoples' communication pattern, we often focus on the message rather than the relationship between them. I work on learning to recognize how people are related to one another and what effect this has on their communication and behavior.
• How does our online behavior affect our offline behavior? As our lives are increasingly lived online, what effect does this have in our offline behavior? I study how the experiences we have online --both good and bad-- affect the actions we take, such as exercising, eating, and traveling.
• How can we make online behavior more civil? Anyone who has scrolled through a few YouTube comments or read a newspaper article's comment section knows how quickly conversation can devolve into incivility. I research what effect this has on people and how we can not only detect such behavior but also mitigate it by improving empathy.

My long-term research goal combines human and language technologies to create social understanding that reflects both the content and people involved in communication. In all my research, I strive to improve social equality by representing all people participating in these social systems.

PhD students

I admit roughly one PhD student per year. Sometimes students are co-admitted or co-advised, so the number of admits can vary.

For prospective PhDs, I especially like students who come with a strong computational background with some experience in social science. There are no set criteria, but you're much better off towards admissions if you've contacted me (or your advisor has) and let me know of your interests and goals. Make sure to look over these pages carefully; the match should be pretty strong. A PhD student is very costly - in time and money - and I select students for my research group carefully.

If you're a current PhD student outside of CSE or SI, I'm open to collaborations. One of the best things about SI and CSE is the interdisciplinary environment here and I'm potentially open to hosting students outside my home departments (but inside UM) in lab or co-advising on projects where it makes sense. Regardless, I'd love to hear from you and you're always welcome to come take my classes

Masters

For current masters students, I typically ask that you take one of my classes and do well in it before starting on research. Often the research you do in one of my graduate courses can continue on through my lab, if you're interested. If you've already taken classes before that are similar, send me an email and we can discuss possibilities.

Due to the technical work that we do in the lab, I typically require students to have taking some graduate-level class on NLP (e.g., EECS 595 or SI 630) or advanced Machine Learning to give them the requisite skills. Without those classes, we end up teaching you many of the same techniques in a less principled way which takes more time. If you took a class like this in your undergraduate and think it was sufficient or if you already have significant research experience (just not in NLP or ML), please feel free to reach out and describe your background.

For prospectivemasters students, I do not have any role in MSI admissions but please feel free to drop me an email once you've been accepted. Showing interest in research prior to starting is usually good sign and gives you more opportunities during your masters program to see if research is something you might want to consider.

Undergraduates

I enjoy working with undergraduates and generally have a few students working on various projects in my lab. I do look for some serious work and effort associated with your research project , but in turn, if you want a recommendation letter later, it will reflect that effort. Typically, the biggest issue I face is students who over-estimate their time availability and disappear as coursework starts to pile up. Good research takes time and consistent effort; bugs will happen, experiments will fail, and programs will take time to run, so being able to dedicate a few hours every day (no joke!) to research is critical. If you can't see yourself doing that, it's best to reach out during a semester you think you will have more time.

I have the easiest time working with technically-oriented students, who already have good programming skills. You will typically be paired with a PhD student who can serve as an extra mentor and answer your questions. For some exceptionally strong students, we can try to get you a project all to yourself, but this usually requires you having done research prior. Occasionally, for bigger projects, I might pair you with another undergrad so you get to be your own research team.

As a undergrad, you will be expected to join our group's research meetings. During the school year, we'll typically have one meeting a week that is also with the project's co-supervisor (a PhD student or postdoc). During the summer, I typically also try to meet undergrads twice per week for short meetings so I can provide more rapid feedback and keep the ball rolling; it's a lot easier to course correct every few days than once per week.

Due to the technical work that we do in the lab, I typically require students to have taking some upper-division class on NLP or Machine Learning to give them the requisite skills. Without those classes, we end up teaching you many of the same techniques in a less principled way which takes more time. That said, if you think you have the skills without the classes, please feel free to reach out and describe your background.

Non-PhD External Students not at the University of Michigan

I unfortunately rarely work with undergraduate and masters students who are not physically at the University of Michigan. I still get emails from external students asking if we could together on something remotely and I really would love to, but my priority is to advise the current students at UM given the limited bandwith I have for advising. Your best bet to work with me is to get admitted to one of our programs and then drop me an email.

However, I do on occasion have self-funded visiting students for the summer and (rarely) during the academic year. In these cases, usually the student has some prior research experience, similar research interests, and (due to luck) there is a current project going on in my lab where they would be a good fit. If you are a self-funded student who wants to come for the summer, you should send an email in February or March before the summer that

1. Describes your research experience and state what parts are relevant to the work going on in my group.
2. Clearly state why you want to work with me. This lets me know that you are familiar with my work and know what you might be working on!
3. What you want to get out of a summer research experience and what you want to learn. This helps me make sure that the trip is a success for you as well.

If you're a PhD student somewhere else and want to work with me (while being external), this could happen under the right circumstances. Typically, your advisor at your primary institution and I would co-advise you. I typically only do these kinds of arrangements when I know your advisor (more common) or when the collaborative project make sense (rare). To get this started, have your advisor email me (not you directly) about what the project is.

Postdocs

I would love to have you all in my lab but this is generally dependent on funding (but seriously, I would take you all if I could). Email me if you think you're a good match and tell me why and we might be able to figure something out. That said, at the moment, I'm not currently actively seeking postdocs (due to funding, of course). If you're coming with your own funding, that changes everything, so drop me a line then.

Q: How do I pronounce your last name?
A: Like you would in the old country

Q: Which old country is that?
A: 🤷

Q: Can I research with you or be a member of the Blablablab?
A: For an overly-detailed answer, click the "Prospective students" tab thingie above. That should cover everything.