Curriculum Vitae
Swan Hall #B102
Occidental College
1600 Campus Road
Los Angeles, CA 90041
(323) 341-4116
justinnhli@oxy.edu
https://justinnhli.com/
@justinnhli
Research Interest
My research is broadly on the strategies that people and artificial agents might use in their search for knowledge during problem solving, from indicators that more knowledge is needed, to strategies for acquiring that knowledge, to the mechanisms, algorithms, and representations of knowledge for efficient retrieval.
Experience
| Occidental College, Los Angeles, CA | |
| Associate Professor in Computer Science and Cognitive Science | 2021 – present |
| Assistant Professor in Computer Science and Cognitive Science | 2015 – 2021 |
| University of Michigan, Ann Arbor, MI | |
| Graduate Student Research Assistant | 2009 – 2015 |
| Engineering Teaching Consultant | 2012 – 2014 |
| Center for Talented Youth, Baltimore, MD | |
| Teaching Assistant | 2008 – 2009 |
| Northwestern University, Evanston, IL | |
| Teaching Assistant | Spring 2009 |
| Gateway Science Workshop Facilitator | 2006 – 2009 |
Education
| PhD in Computer Science. University of Michigan, Ann Arbor, MI. | 2016 |
|
BS in Computer Science, cum laude. Northwestern University, Evanston, IL. with a Certificate in Engineering Design |
2009 |
Publications
Undergraduate co-authors are marked with an asterisk ().
Journal Articles
| Justin Li. Explorable Web Apps to Teach AI to Non-Majors. The Journal of Computing Sciences in Colleges, 34(4), 128-133. | 2019 |
| Justin Li and Emma Kohanyi. Towards Modeling False Memory with Computational Knowledge Bases. Topics in Cognitive Science (TopiCS), 9(1), 102-116. | 2017 |
Peer-Reviewed Conference Papers
| Justin Li, Bryce Boyle. Towards a Computational Model of a Dynamic Feeling of Knowing. In Proceedings of the 19th International Conference on Cognitive Modeling (ICCM). | 2022 |
| Justin Li. Integrating Declarative Long-Term Memory Retrievals into Reinforcement Learning. In Proceedings of the 8th Annual Conference on Advances in Cognitive Systems (ACS). | 2020 |
| Justin Li. A Heuristic Strategy for Identifying Misclassified Data Using Classification Labels. In Proceedings of the 7th Annual Conference on Advances in Cognitive Systems (ACS), 75-93. | 2019 |
| Justin Li and Emma Kohanyi. Towards Modeling False Memory with Computational Knowledge Bases. In Proceedings of the 14th International Conference on Cognitive Modeling (ICCM). | 2016 |
| Justin Li, Steven Jones, Shiwali Mohan, and Nate Derbinsky. Architectural Mechanisms for Mitigating Uncertainty during Long-Term Declarative Knowledge Access. In Proceedings of the 4th Annual Conference on Advances in Cognitive Systems (ACS). | 2016 |
| Justin Li and John E. Laird. Spontaneous Retrieval for Prospective Memory: Effects of Encoding Specificity and Retention Interval. In Proceedings of the 13th International Conference on Cognitive Modeling (ICCM), 142-147. | 2015 |
| Justin Li and John E. Laird. Spontaneous Retrieval from Long-Term Memory in a Cognitive Architecture. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 544-550. | 2015 |
| Justin Li and John E. Laird. The Computational Problem of Prospective Memory Retrieval. In Proceedings of the 12th International Conference on Cognitive Modeling (ICCM), 155-160. | 2013 |
| Justin Li and John E. Laird. Preemptive Strategies for Overcoming the Forgetting of Goals. In Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI), 1234-1240. | 2013 |
| Nate Derbinsky, Justin Li, and John E. Laird. A Multi-Domain Evaluation of Scaling in a General Episodic Memory. In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI), 193-199. | 2012 |
| Justin Li, Nate Derbinsky, and John E. Laird. Functional Interactions between Memory and Recognition Judgments. In Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI), 228-234. | 2012 |
Peer-Reviewed Symposia Papers, Edited Commentaries, and Other Publications
| Justin Li, Steven Jones, and John E. Laird A Rational Analysis and Computational Modeling Perspective on IAM and Déjà Vu. Commentary on Barzykowski and Moulin (2023), Are involuntary autobiographical memory and déjà vu natural products of memory retrieval? In Behavioral and Brain Sciences, (in print). | 2023 |
| Justin Li and John E. Laird. Preliminary Evaluation of Long-term Memories for Fulfilling Delayed Intentions. In Papers from the 2011 AAAI Fall Symposium Series: Advances in Cognitive Systems (ACS), 170-177. | 2011 |
Peer-Reviewed Abstracts
| Justin Li. Weaving Diversity and Inclusion into CS Content. In Proceedings of the 48th ACM Technical Symposium on Computer Science Education (SIGCSE). | 2017 |
| Nate Derbinsky, Justin Li, and John E. Laird. Algorithms for Scaling in a General Episodic Memory (Extended Abstract). In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1387-1388. | 2012 |
Invited Panels
| ACS Academia Panel, at the Proceedings of the 8th Annual Conference on Advances in Cognitive Systems (ACS). | 2020 |
Workshop Presentations
| Retracing the Rational Analysis of Memory, at the 34th Soar Workshop | 2014 |
| Do's and Don't's of Episodic Memory, at the 31st Soar Workshop | 2011 |
Grants
| Ron Buckmire, Justin Li, Amanda Zellmer (PIs), Carmel Levitan, Eileen Spain (co-PIs). Evaluating Effective Inclusive Teaching and its Use for Faculty Promotion and Tenure, HHMI Inclusive Excellence 3 Initiative, $535,000. | 2022 |
| Gretchen North (PI), Janet Scheel, Ron Buckmire, Aleksandra Sherman, Justin Li (co-PIs). Creating Opportunities for High-Achieving Students in Science and Mathematics through Scholarships, Research Experiences, Leadership, and Community, NSF S-STEM, $1,000,000. | 2020 |
| Justin Li (PI). Attendee Support for the 2020 AAAI Doctorial Consortium, NSF, $17,100. | 2020 |
| Justin Li (PI), Jeff Cannon, Diana Ngo, Janet Scheel, Amanda Zellmer (co-PIs). Acquisition of a High-Performance Computing Cluster for Occidental College, NSF MRI, $493,878. | 2019 |
Awards
| Outstanding Graduate Student Instructor Award, EECS Department, University of Michigan | Fall 2009 |
Software
| Justin Li and Uri Wilensky (2009). NetLogo Sugarscape 1 Immediate Growback Model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. | 2009 |
| Justin Li and Uri Wilensky (2009). NetLogo Sugarscape 2 Constant Growback Model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. | 2009 |
| Justin Li and Uri Wilensky (2009). NetLogo Sugarscape 3 Wealth Distribution Model. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. | 2009 |
Media Appearances
|
How Reddit.com’s /r/professors Provides a Glimpse Into Future Brand Issues for Universities.
Inside Higher Ed, April 2, 2020. [I'm the "mathematics professor" whose YouTube lecture was taken down.] |
| What Do You Need? AI Might Soon Know Before You Do. PC Magazine, August 16, 2018. |
| A new kind of computer science major delves into how technology is reshaping society. LA Times, March 13, 2018. |
| Terminator 2 took aim at the ethics of artificial intelligence. AV Club, September 23, 2016. |
Design
| Engineering Design Portfolio | Spring 2009 |