Biography
Siegelmann earned her BA at Technion, her MSc at Hebrew University and her PhD at Rutgers University, all in Computer Science and high distinction.
In the early 1990s, together with Eduardo D. Sontag, Siegelmann proposed a new computational model, the Artificial Recurrent Neural Network (ARNN), which demonstrated both practical and mathematical utilities. They showed how such interconnections provide very significant computation, and proved mathematically that ARNN have very well-defined computational power that is beyond the classical Universal Turing Machine. Her initial publications on the computational power of Neural Networks culminated in a sole-authored paper in Science and her monograph, "Neural Networks and Analog Computation: Beyond the Turing Limit". Siegelmann demonstrates in her paper in Science that all chaotic systems (that cannot be described by Turing computation) are now described by the Super-Turing model. This is significant since many biological systems not describable by standard means (e.g., heart, brain) can be described as a chaotic system and can now be modeled mathematically.
The theory of Super-Turing computation has attracted followers beyond Computer Science from Physics, Biology, and Medicine. Siegelmann is also one of the originators of the Support Vector Clustering http://www.scholarpedia.org/article/Support_vector_clustering, a widely used algorithm in industry, together with Vladimir Vapnik and colleagues. Siegelmann also introduced a new notion in the field of Dynamical Systems., which describes diseases in the terminology and analysis of dynamical system theory, meaning that in treating disorders, it is too limiting to seek only to repair primary causes of the disorder; any method of returning system dynamics to the balanced range, even under physiological challenges (e.g., by repairing the primary source, activating secondary pathways, or inserting specialized signaling), can ameliorate the system and be extremely beneficial to healing. Employing this new concept, she revealed the source of disturbance during shift work and travel leading to jet-lag and is currently studying human memory and cancer in this light.
Siegelmann has been active throughout her career in advancing and supporting minorities and women in the fields of Computer Science and Engineering. Among other roles, Siegelmann is on the governing board of the International Neural Networks Society and has served as Program Chair of the 2011 International Joint Conference on Neural Networks.
Read more about this topic: Hava Siegelmann
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