Hava Siegelmann

Hava Siegelmann is a professor of computer science. Her academic position is in the school of Computer Science and the Program of Neuroscience and Behavior at the University of Massachusetts Amherst; she is the director of the school's Biologically Inspired Neural and Dynamical Systems Lab and is the Provost Professor of the University of Massachusetts. She was loaned to the federal government DARPA 2016-2019 to initiate and run their most advanced AI programs including her Lifelong Learning Machine (L2M) program. and Guaranteeing AI Robustness against Deceptions (GARD). She received the rarely awarded Meritorious Public Service Medal — one of the highest honors the Department of Defense agency can bestow on a private citizen.

Siegelmann is an American computer scientist who founded the field of Super-Turing computation. As a DAPRA Program Manager she introduced the field of Lifelong Learning Machines, the most recent advancement in Artificial Intelligence, which is a great leap forward from the continual task-learning paradigm. She contributed some of the most significant research results in both Neural Networks and Lifelong Learning. For her lifetime contribution to the field of Neural Networks she was the recipient of the 2016 Donald Hebb Award. She earned her PhD at Rutgers University, New Jersey, in 1993.

In the early 1990s, she and Eduardo D. Sontag proposed a new computational model, the Artificial Recurrent Neural Network (ARNN), which has been of both practical and mathematical interest. They proved mathematically that ARNNs have well-defined computational powers that extend the classical Universal Turing machine. Her initial publications on the computational power of Neural Networks culminated in a single-authored paper in Science and her monograph, "Neural Networks and Analog Computation: Beyond the Turing Limit".