معرفی
Elena Zheleva is an Associate Professor in the Department of Computer Science at the University of Illinois at Chicago (UIC). She leads the EDGES Lab, focusing on unifying causal inference, machine learning, and network analysis to address societal challenges. Her research bridges data science, privacy, and AI fairness, with applications in social networks, health, and policy. She earned her Ph.D. from the University of Maryland in 2011.
Research Interests: Dr. Zheleva's work spans data science, machine learning, causal inference, graph mining, and privacy. She develops methods to address biases in relational data, designs personalized privacy tools, and studies network interference effects. Key applications include social media analysis, healthcare informatics, and algorithmic fairness.
Publication Trends: Her recent articles emphasize causal inference in networked environments, tackling problems like peer effects, diffusion interference, and bias in ranking systems. She frequently publishes in top-tier venues (e.g., UAI, WWW, KDD), showcasing innovations in experimental design, fairness-aware AI, and graph-based learning.
Awards & Honors:
- NSF CAREER Award (2021)
- COE Research Award (2021)
- DCFemTech Award (2017)
- Best Paper Honorable Mention at ICWSM 2020
Advising & Grants: She mentors 5 Ph.D. candidates and has graduated 13+ students. Her lab secured major grants from NSF, DARPA, Adobe, and Anthem for projects on relational causal inference, COVID-19 attitudes, and privacy-aware systems. Key grants include NSF CAREER, TRIPODS, and DARPA EDIFICE.
Leadership: Dr. Zheleva co-organizes workshops (e.g., KDD tutorials on causal inference), serves as associate editor for ACM TIST and DAMI, and is program chair for SDM 2025. She leads the EDGES Lab, fostering collaborations in computational social science and AI ethics.
