Talya Eden

Talya Eden is an Assistant Professor in the Department of Computer Science at Bar Ilan University. She previously held a postdoctoral position at the Foundations of Data Science Institute (FODSI), jointly affiliated with MIT and Boston University, hosted by Prof. Ronitt Rubinfeld, Prof. Piotr Indyk, and Prof. Sofya Raskhodnikova. She earned her PhD from the School of Electrical Engineering at Tel Aviv University under the supervision of Prof. Dana Ron.

Her research focuses on sublinear-time algorithms and property testing, with a strong emphasis on approximating graph parameters efficiently. Her work lies at the intersection of theoretical computer science, graph algorithms, and data science, addressing fundamental problems in large-scale graph analysis.

Her recent publications, appearing in top venues such as STOC, FOCS, SODA, and ICALP, demonstrate consistent contributions to the fields of graph sampling, counting, streaming algorithms, and learning-augmented computation. Key themes include k-clique and triangle estimation, arboricity-based complexity, and robustness in streaming models.

She has collaborated extensively with leading researchers including Dana Ron, Ronitt Rubinfeld, Piotr Indyk, and C. Seshadhri. Her work often explores the theoretical limits of what can be computed efficiently on massive graphs with limited access.

Notable Scientific Contributions:

• Developed nearly optimal algorithms for sampling k-cliques in sublinear time.
• Established tight connections between arboricity and the complexity of edge sampling and degree moment estimation.
• Contributed to adversarially robust streaming algorithms using dense-sparse trade-offs.
• Explored learning-based approaches to enhance sublinear-time support estimation.

Talya Eden advises students and is actively involved in the theoretical computer science research community. She has not received any explicitly mentioned scientific awards in the provided text, but her publication record in elite conferences indicates high recognition.