Faculty Recruiting Support CICS

Hava T. Siegelmann

Provost Professor
276 CS Building
(413) 577-4282


Advanced Lifelong learning AI, Enhanced Time-aware AI, Innovations in Biological Computation, Super-Turing computation, Computational Neuroscience and Learning, Complex Dynamical systems, Human-robot interface, Health applications, Government and Industrial applications.


Senior faculty for bio-inspired AI, Dr. Siegelmann is an internationally known UMass Provost Professor in Computer Science and a recognized expert in neural networks. She is a core member of the University of Massachusetts Neuroscience and Behavior Program and director of the Biologically Inspired Neural and Dynamical Systems (BINDS) Laboratory. She has been particularly acclaimed for her groundbreaking work in computation beyond the Turing limit, and for achieving advanced learning capabilities through a new type of Artificial Intelligence: Lifelong Learning. Siegelmann conducts highly interdisciplinary research in next-generation machine learning, neural networks, intelligent machine-human collaboration, and computational studies of the brain - with application to AI, data science, and high-tech industry. Prof. Siegelmann is a co-inventor of the Support Vector Clustering (SVC) algorithm, which is widely used across industry and government. Among her recent Nature publications is Biological Underpinning of Lifelong Learning AI, a bio-inspired replay algorithm for advanced lifelong learning, dual fractal structure & function of the human brain, and identification of a previously unknown brain connectome mechanism, which enables cognitive abstraction. 


Ph.D., Computer Science, Rutgers University (1993, Fellow of excellence), M.Sc., Computer Science, Hebrew University (1992, Cum Laude), B.A., Computer Science, the Technion (1988, Suma Cum Laude). Siegelmann has been a visiting professor at MIT, Harvard University, the Weizmann Institute, ETH, the Salk Institute, Mathematical Science Research Institute Berkeley, and the Newton Institute of Cambridge University. 

Professor Siegelmann recently completed a four-year term as a PM of some of DARPA's most significant and innovative AI programs: Lifelong Learning Machines "L2M," one of her key initiatives, inaugurated "third-wave AI," pushing major design innovation, inspired by biology, and a dramatic increase in AI capability. "GARD" is leading to novel advancements in assuring AI robustness against attack. "CSL" is introducing powerful methods of collaborative information sharing on AI platforms without revealing private data. Other programs include advanced biomedical applications. DARPA/DoD bestowed upon her the Meritorious Public Service Medal, one of the highest medals for civilians, for her research and leadership.

Activities & Awards

Siegelmann's long list of awards includes the Obama Presidential BRAIN Initiative award, the ALON fellowship, the Donald O. Hebb Award of the International Neural Network Society (INNS) for "contribution to biological learning;" she was named a Distinguished Lecturer of the IEEE Computational Intelligence Society and was given DARPA's Meritorious Public Service medal. Siegelmann is a fellow of both the IEEE and the INNS; she served on INNS' Board of Governors from 2012 to 2020 and previously as Program Chair of the International Joint Conference on Neural Networks (IJCNN); Siegelmann was recently named a UMass Provost Professor. She has been serving as a vice-chair on the Neural Network Technical Committee (NNTC) of the IEEE Computational Intelligence Society (CIS), as well as on the IEEE CIS Outstanding PhD Dissertation Award committee and the IEEE Task Force on Ethical, Legal, Social, Environmental and Human Dimensions of AI/CI (SHIELD). Siegelmann is an associate editor of the Frontiers in Computational Neuroscience journal and has served as an editor for numerous other major journals. Siegelmann was the founding chair of INNS' diversity committee; she also serves as a co-chair of UMass' diversity council of the university senate. Siegelmann is a leader in increasing awareness of ethical issues in AI and in supporting minorities and women in STEM fields.