George V. Cybenko is the Dorothy and Walter Gramm Professor of Engineering at Dartmouth and a fellow of the IEEE and SIAM.^[1]

Cybenko obtained his BA in mathematics from the University of Toronto in 1974 and received his PhD from Princeton in applied mathematics of electrical and computer engineering in 1978 under Bede Liu.^[2]

Cybenko served as an advisor for the Defense Science Board and the Air Force Scientific Advisory Board, among several other government panels. He was the founding editor-in-chief of Security & Privacy and also of Computing in Science & Engineering, both IEEE technical magazines. His current research interests are distributed information, control systems, and signal processing, with a focus on applications to security and infrastructure protection. He is known for proving the universal approximation theorem for artificial neural networks with sigmoid activation functions.^[3]

• SIAM Fellow (2020), "for contributions to theory and algorithms in signal processing, artificial neural networks, and distributed computing systems."^[4]
• SPIE Eric A. Lehrfeld Award (2016), for "work in cyber security including developing algorithms, analysis techniques, and tools to improve the state of the art in many areas, including computational behavior analysis, adversarial deception detection and dynamics, disclosure risk, and covert channels, and for his efforts in support of the SPIE Defense + Commercial Sensing symposium".^[5]
• US Air Force Commander’s Service Award (2016)^[6]
• IEEE Fellow (1998), "for contributions to algorithms and theory of artificial neural networks in signal processing, and to theory and systems software for distributed and parallel computing."^[7]