Professor of Computer Science
Dr. Elena Vasquez
Stanford University, Department of Computer Science. Researching the intersection of machine learning and human-computer interaction to create more intuitive AI systems.
evasquez@stanford.edu
Gates Building, Room 392
Research Focus
Research Interests
01
Human-AI Interaction
Designing AI systems that understand and adapt to human behavior, creating more natural and intuitive interfaces for complex machine learning models.
02
Explainable AI
Developing methods to make machine learning decisions transparent and interpretable, enabling trust and accountability in automated systems.
03
Computational Cognition
Modeling human cognitive processes using computational methods to better understand learning, decision-making, and problem-solving behaviors.
Selected Works
Publications
A selection of peer-reviewed papers from top-tier conferences and journals.
120+
Citations
CHI 2024
Best Paper Award
Bridging the Gap: Intuitive Interfaces for Complex ML Models
Vasquez, E., Chen, M., & Rodriguez, A. (2024). Proceedings of CHI Conference on Human Factors in Computing Systems.
NeurIPS 2023
Spotlight
Attention Mechanisms in Human-Like Learning Systems
Vasquez, E., & Kim, J. (2023). Advances in Neural Information Processing Systems.
TOCHI 2023
Designing for Trust: Transparency Patterns in AI-Assisted Decision Making
Vasquez, E., Patel, S., & Wong, L. (2023). ACM Transactions on Computer-Human Interaction.
ICML 2022
Cognitive Load Optimization in Interactive Machine Learning
Vasquez, E., & Thompson, R. (2022). International Conference on Machine Learning.
Academic Year 2024-25
Teaching
CS 229
Fall Quarter
Machine Learning
Graduate-level introduction to machine learning, covering supervised learning, unsupervised learning, and reinfortic agents.
Mon/Wed 10:30-12:00 — Gates B01
CS 347
Winter Quarter
Human-Computer Interaction
Design and evaluation of user interfaces, with focus on AI-powered systems and explainable interfaces for complex technologies.
Tue/Thu 14:00-15:30 — Gates B03
CS 499
Spring Quarter
Research Seminar: AI & Society
PhD seminar exploring ethical implications of AI systems. Students present and critique recent papers on AI safety and governance.
Fri 13:00-16:00 — Gates 415
Background
Education
2012 — 2016
Ph.D. Computer Science
MIT — Advisor: Prof. James Mitchell
2010 — 2012
M.S. Computer Science
Stanford University
2006 — 2010
B.S. Mathematics & CS
UC Berkeley — Summa Cum Laude
Recognition
Awards & Grants
2024
NSF CAREER Award
$750,000 — Human-Centered Explainable AI
2023
Sloan Research Fellowship
Alfred P. Sloan Foundation
2022
Google Faculty Research Award
Interactive Machine Learning
2020
ACM SIGCHI Best Paper
CHI Conference 2020
Team
Research Lab
The Human-AI Interaction Lab (HAIL) investigates how people and intelligent systems can work together effectively.
Marcus Chen
PhD Candidate
Adaptive interfaces for ML model debugging
Priya Sharma
PhD Candidate
Explainability in healthcare AI systems
James Wilson
Postdoctoral Researcher
Trust calibration in AI-assisted decisions
Sofia Rodriguez
Research Engineer
Tooling & infrastructure for HCI research
Get in Touch
Contact & Office Hours
I welcome inquiries from prospective students, collaborators, and anyone interested in human-AI interaction research. For media inquiries, please contact the Stanford Communications office.
evasquez@stanford.edu
Gates Building, Room 392, Stanford, CA
Office Hours
Monday
14:00 – 16:00
Thursday
10:00 – 12:00
Please book via Calendly or email to schedule outside regular hours.