Leilani Gilpin

Assistant Professor of Computer Science - UC Santa Cruz

About

Leilani Gilpin is an assistant professor of computer science at UC Santa Cruz. She holds a Ph.D. in electrical engineering and computer science from the Massachusetts Institute of Technology and a B.S. in computer science and mathematics from the University of California, San Diego. She also has experience as an AI researcher at Sony and the Palo Alto Research Center.

Education

Massachusetts Institute of Technology

Ph.D., Electrical Eng. and Computer Science / 2020

Cambridge, Massachusetts, United States of America

Stanford University

M.S., Computational and Mathematical Engineering / 2013

Stanford, California, United States of America

University of California, San Diego

B.S., Computer Science and Mathematics / 2011

San Diego, California, United States of America

Experience

UC Santa Cruz

Assistant Professor of Computer Science / 2021Present

Sony

AI Researcher / 20202021

Palo Alto Research Center

Technical Staff / 20112013

Publications

Explaining Explanations: An Overview of Interpretability of Machine Learning

2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA) / Oct 01, 2018

Gilpin, L. H., Bau, D., Yuan, B. Z., Bajwa, A., Specter, M., & Kagal, L. (2018). Explaining Explanations: An Overview of Interpretability of Machine Learning. 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA). https://doi.org/10.1109/dsaa.2018.00018

Explaining Explanations: An Overview of Interpretability of Machine Learning

2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA) / Oct 01, 2018

Gilpin, L. H., Bau, D., Yuan, B. Z., Bajwa, A., Specter, M., & Kagal, L. (2018). Explaining Explanations: An Overview of Interpretability of Machine Learning. 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA). https://doi.org/10.1109/dsaa.2018.00018

Graph Analysis for Detecting Fraud, Waste, and Abuse in Healthcare Data

AI Magazine / Jul 04, 2016

Liu, J., Bier, E., Wilson, A., Guerra-Gomez, J. A., Honda, T., Sricharan, K., Gilpin, L., & Davies, D. (2016). Graph Analysis for Detecting Fraud, Waste, and Abuse in Healthcare Data. AI Magazine, 37(2), 33–46. https://doi.org/10.1609/aimag.v37i2.2630

Outracing champion Gran Turismo drivers with deep reinforcement learning

Nature / Feb 09, 2022

Wurman, P. R., Barrett, S., Kawamoto, K., MacGlashan, J., Subramanian, K., Walsh, T. J., Capobianco, R., Devlic, A., Eckert, F., Fuchs, F., Gilpin, L., Khandelwal, P., Kompella, V., Lin, H., MacAlpine, P., Oller, D., Seno, T., Sherstan, C., Thomure, M. D., … Kitano, H. (2022). Outracing champion Gran Turismo drivers with deep reinforcement learning. Nature, 602(7896), 223–228. https://doi.org/10.1038/s41586-021-04357-7

Preprint repository arXiv achieves milestone million uploads

Physics Today / Jan 01, 2014

Preprint repository arXiv achieves milestone million uploads. (2014). Physics Today. https://doi.org/10.1063/pt.5.028530

Perception of Speaker Personality Traits Using Speech Signals

Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems / Apr 20, 2018

Gilpin, L. H., Olson, D. M., & Alrashed, T. (2018). Perception of Speaker Personality Traits Using Speech Signals. Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3170427.3188557

Topological Semiotic Knowledge Representation

Aligning Perceptual and Conceptual Information for Cognitive Contextual System Development / Jan 01, 2018

Topological Semiotic Knowledge Representation. (2018). Advances in Systems Analysis, Software Engineering, and High Performance Computing, 45–78. https://doi.org/10.4018/978-1-5225-2431-1.ch002

Reasonableness Monitors

Proceedings of the AAAI Conference on Artificial Intelligence / Apr 29, 2018

Gilpin, L. (2018). Reasonableness Monitors. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.11364

Co-simulation Solutions using AA4MM-FMI applied to Smart Space Heating Models

Proceedings of the Seventh International Conference on Simulation Tools and Techniques / Jan 01, 2014

Gilpin, L., Ciarletta, L., Presse, Y., Chevrier, V., & Galtier, V. (2014). Co-simulation Solutions using AA4MM-FMI applied to Smart Space Heating Models. Proceedings of the Seventh International Conference on Simulation Tools and Techniques. https://doi.org/10.4108/icst.simutools.2014.254633

A Stress Testing Framework For Autonomous System Verification And Validation (V&V)

2021 IEEE International Conference on Autonomous Systems (ICAS) / Aug 11, 2021

Falco, G., & Gilpin, L. H. (2021). A Stress Testing Framework For Autonomous System Verification And Validation (V&V). 2021 IEEE International Conference on Autonomous Systems (ICAS). https://doi.org/10.1109/icas49788.2021.9551154

Explaining Multimodal Errors in Autonomous Vehicles

2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA) / Oct 06, 2021

Gilpin, L. H., Penubarthi, V., & Kagal, L. (2021). Explaining Multimodal Errors in Autonomous Vehicles. 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA). https://doi.org/10.1109/dsaa53316.2021.9564178

About the social role of child and adolescent psychiatrists in times of epidemic

IACAPAP ArXiv / Jan 01, 2020

Falissard, B. (2020). About the social role of child and adolescent psychiatrists in times of epidemic. IACAPAP ArXiv. https://doi.org/10.14744/iacapaparxiv.2020.20004

ICAIL Doctoral Consortium, Montreal 2019

Artificial Intelligence and Law / May 26, 2020

Araszkiewicz, M., Amantea, I. A., Chakravarty, S., van Doesburg, R., Dymitruk, M., Garin, M., Gilpin, L., Odekerken, D., & Salehi, S. S. (2020). ICAIL Doctoral Consortium, Montreal 2019. Artificial Intelligence and Law, 28(2), 267–280. https://doi.org/10.1007/s10506-020-09267-z

Reasonable Perception

Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction / Mar 01, 2018

Gilpin, L. H., Zaman, C., Olson, D., & Yuan, B. Z. (2018). Reasonable Perception. Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction. https://doi.org/10.1145/3173386.3176994

Getting up to speed in turbulence simulations

Physics Today / Oct 19, 2017

Getting up to speed in turbulence simulations. (2017). Physics Today. https://doi.org/10.1063/pt.6.1.20171019a

Anticipatory Thinking: A Testing and Representation Challenge for Self-Driving Cars

2021 55th Annual Conference on Information Sciences and Systems (CISS) / Mar 24, 2021

Gilpin, L. H. (2021). Anticipatory Thinking: A Testing and Representation Challenge for Self-Driving Cars. 2021 55th Annual Conference on Information Sciences and Systems (CISS). https://doi.org/10.1109/ciss50987.2021.9400212

Explainable Anomaly Detection for District Heating Based on Shapley Additive Explanations

2020 International Conference on Data Mining Workshops (ICDMW) / Nov 01, 2020

Park, S., Moon, J., & Hwang, E. (2020). Explainable Anomaly Detection for District Heating Based on Shapley Additive Explanations. 2020 International Conference on Data Mining Workshops (ICDMW). https://doi.org/10.1109/icdmw51313.2020.00111

Aligning safety and security systems for connected vehicles

Cyber-Security for Urban Transport Systems 2016 / Jan 01, 2016

Ward, D. (2016). Aligning safety and security systems for connected vehicles. Cyber-Security for Urban Transport Systems 2016. https://doi.org/10.1049/ic.2016.0022

Pediatricians called to do More STD Screening

Pediatric News / Oct 01, 2012

JANCIN, B. (2012). Pediatricians called to do More STD Screening. Pediatric News, 46(10), 11. https://doi.org/10.1016/s0031-398x(12)70227-8

City/future in the making: Masterplanning London’s Olympic legacy as anticipatory assemblage

Futures / May 01, 2019

Davis, J., & Groves, C. (2019). City/future in the making: Masterplanning London’s Olympic legacy as anticipatory assemblage. Futures, 109, 13–23. https://doi.org/10.1016/j.futures.2019.04.002

Custom Core ML Models Using Create ML

Beginning Machine Learning in iOS / Jan 01, 2019

Thakkar, M. (2019). Custom Core ML Models Using Create ML. Beginning Machine Learning in IOS, 95–138. https://doi.org/10.1007/978-1-4842-4297-1_4

The first historical account of Vietnam mathematics on arXiv

Apr 24, 2022

Phenikaa, I. (2022). The first historical account of Vietnam mathematics on arXiv. https://doi.org/10.31219/osf.io/mv76r

Separating facts and evaluation: motivation, account, and learnings from a novel approach to evaluating the human impacts of machine learning

AI & SOCIETY / Mar 16, 2022

Jenkins, R., Hammond, K., Spurlock, S., & Gilpin, L. (2022). Separating facts and evaluation: motivation, account, and learnings from a novel approach to evaluating the human impacts of machine learning. AI & SOCIETY. https://doi.org/10.1007/s00146-022-01417-y

Construction and Validation of an Anticipatory Thinking Assessment

Jun 26, 2019

Geden, M., Smith, A., Campbell, J., Spain, R., Amos-Binks, A., Mott, B., Feng, J., & Lester, J. (2019). Construction and Validation of an Anticipatory Thinking Assessment. https://doi.org/10.31234/osf.io/9reby

Reports of the AAAI 2019 Spring Symposium Series

AI Magazine / Sep 30, 2019

Baldini, I., Barrett, C., Chella, A., Cinelli, C., Gamez, D., Gilpin, L., Hinkelmann, K., Holmes, D., Kido, T., Kocaoglu, M., Lawless, W., Lomuscio, A., Macbeth, J., Martin, A., Mittu, R., Patterson, E., Sofge, D., Tadepalli, P., Takadama, K., & Wilson, S. (2019). Reports of the AAAI 2019 Spring Symposium Series. AI Magazine, 40(3), 59–66. https://doi.org/10.1609/aimag.v40i3.5181

Object Detection for Autonomous Driving

Proceedings of The 7th International Conference on Intelligent Systems and Image Processing 2019 / Jan 01, 2019

Chen, W.-H. (2019). Object Detection for Autonomous Driving. Proceedings of The 7th International Conference on Intelligent Systems and Image Processing 2019. https://doi.org/10.12792/icisip2019.002

Impact of Topology-dependent and independent Mobility Models on the Connectivity of Wireless Networks

2008 IEEE Sarnoff Symposium / Apr 01, 2008

Yanmaz, E. (2008). Impact of Topology-dependent and independent Mobility Models on the Connectivity of Wireless Networks. 2008 IEEE Sarnoff Symposium. https://doi.org/10.1109/sarnof.2008.4520052

Tools for trustworthy AI

OECD Digital Economy Papers / Jun 28, 2021

Tools for trustworthy AI. (2021). OECD Digital Economy Papers. https://doi.org/10.1787/008232ec-en

Teens in Danger

PsycEXTRA Dataset / Jan 01, 2005

Teens in Danger. (2005). PsycEXTRA Dataset. https://doi.org/10.1037/e535832006-001

Stator Inter-turn Faults Detection and Localization Using Stator Currents and Concordia Patterns - Neural Network Applications

2007 Compatibility in Power Electronics / May 01, 2007

El-Arabawy, I. F., Masoud, M. I., & Mokhtari, A. E.-K. (2007). Stator Inter-turn Faults Detection and Localization Using Stator Currents and Concordia Patterns - Neural Network Applications. 2007 Compatibility in Power Electronics. https://doi.org/10.1109/cpe.2007.4296552

Links & Social Media

Research Interests

Explainable AI
Diagnostics
Anomaly Detection
Commonsense Reasoning
AI and ethics
Artificial Intelligence
General Physics and Astronomy
Multidisciplinary
General Medicine
Law
Sociology and Political Science
Development
Business and International Management
General Agricultural and Biological Sciences
Human-Computer Interaction
Philosophy
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