Jerry L. Feldman

Jerry L. Feldman is an American computer scientist and cognitive scientist known for work on connectionist models, neural networks, and cognitive architectures. He has contributed to research linking artificial neural networks with cognitive processes and has held academic positions at major research universities and national laboratories. Feldman's work intersects with influential figures and institutions in artificial intelligence, neuroscience, and psychology.

Early life and education

Feldman was born and raised in the United States and completed undergraduate and graduate studies that connected him with research communities at institutions such as Massachusetts Institute of Technology, Stanford University, and University of California, Berkeley. During his formative training he engaged with faculty and peers involved in projects at Bell Labs, Lincoln Laboratory, and collaborations with researchers associated with Cognitive Science Society, Association for the Advancement of Artificial Intelligence, and Neural Information Processing Systems. His doctoral and postdoctoral mentors included investigators with ties to Marvin Minsky, Noam Chomsky, David Marr, Herbert A. Simon, and laboratories affiliated with Naval Research Laboratory and SRI International.

Academic career and positions

Feldman has held faculty and research appointments at universities and national laboratories, collaborating with departments and centers such as Carnegie Mellon University, University of California, San Diego, University of Michigan, and Los Alamos National Laboratory. He has been affiliated with interdisciplinary programs that bridge Psychology Department, Computer Science Department, and centers like Artificial Intelligence Laboratory and Center for Cognitive Science. Feldman has participated in panels and advisory boards for organizations including National Science Foundation, Defense Advanced Research Projects Agency, National Institutes of Health, and industry partners like IBM Research and Google DeepMind.

Research contributions and theories

Feldman's research emphasizes connectionist and parallel distributed processing approaches to modeling cognition, linking work to seminal frameworks developed by Frank Rosenblatt, Geoffrey Hinton, David Rumelhart, and James L. McClelland. He explored learning algorithms and representational issues related to backpropagation, recurrent neural networks, and unsupervised learning, intersecting with concepts advanced by Yann LeCun, Andrew Ng, Terrence Sejnowski, and Tomaso Poggio. Feldman examined how neural-network models can account for phenomena studied by Ulric Neisser, Jerome Bruner, Elizabeth Bates, and Steven Pinker, and his approaches relate to computational theories from Hubert Dreyfus and Roger Schank. His work addressed stability-plasticity dilemmas, inspired by ideas from Gustav Fechner and Donald Hebb, and engaged with debates on symbolic versus subsymbolic representation alongside proponents such as John Searle and Marvin Minsky.

Feldman contributed to theories of memory, learning, and perception by building models comparable to those from Karl Lashley, Brenda Milner, Endel Tulving, and Eric Kandel. He investigated neural dynamics that resonate with findings from Warren McCulloch and Walter Pitts and examined computational trade-offs discussed by Leslie Valiant and Judea Pearl. His interdisciplinary collaborations touched on topics relevant to Neuroscience Institute, Max Planck Institute, Salk Institute, and clinical research at centers like Mayo Clinic and Johns Hopkins University.

Publications

Feldman authored and coauthored books, chapters, and articles in venues including journals and conferences affiliated with Journal of Cognitive Neuroscience, Cognitive Science, Proceedings of the National Academy of Sciences, Neural Computation, and proceedings of NeurIPS, International Joint Conference on Artificial Intelligence, and Cognitive Science Society Conference. His publications engaged with topics explored by editors and authors such as Daniel Dennett, Patricia Churchland, Paul Smolensky, Gary Marcus, and Philip Johnson-Laird. He contributed chapters to collected volumes alongside scholars from MIT Press, Oxford University Press, and Cambridge University Press, and his work has been cited in textbooks by authors like Simon Haykin and Christopher Bishop.

Awards and honors

Feldman received recognition from professional societies and institutions including fellowships, visiting professorships, and awards from organizations such as Association for the Advancement of Artificial Intelligence, Cognitive Science Society, National Science Foundation, and university teaching awards from institutions including University of California campuses and Carnegie Mellon University. He has been invited to keynote and give distinguished lectures at conferences hosted by IEEE, ACM, Royal Society, and research institutes such as Sloan Foundation and Howard Hughes Medical Institute.

Category:American computer scientists Category:Cognitive scientists