Jeffrey Schmidt - Teaching Assistant @ Binghamton University

jschmid1@binghamton.edu

Research interests:
  •  Complex Adaptive Networks
  •  Evolutionary Computation
  •  Neural Networks
  •  Agent Based Modeling
  •  Artificial Intelligence
  •  Economic Modeling

Currently:

Education:
  • MS in Systems Science 2012
  • BS in CS Binghamton University 2006
  • AS in CS Alfred State College 2003

Memberships:
  • The New England Complex Systems Institute

Work Experience
  • Teaching Assistant/Instructor for the complex systems seminar course (2014-Present)
  • Research Assistant for SUNY Research Foundation (2011-2013)
  • Software Engineer at Universal Instruments.  Worked on heuristic algorithms for a version of the traveling salesman problem.  Implemented a Genetic Algorithm for the so called "Deep Optimization" routine.  Created a novel (to my knowledge) data structure based on the TV-tree and kd-tree, dubbed the kdTV-tree, designed to address computational complexity problems encountered by the existing algorithms. (2006-2011)
Awards

Publications/Presentations:
  • Andreas Pape, Tod Guilfoos, Nathan Anderson, and Jeffrey Schmidt, Rational Expectations Voting in Agent-based Models: An Application to Tax Ceilings, Review of Behavioral Economics. Forthcoming.
  • Hiroki Sayama, Irene Pestov, Jeffrey Schmidt, Benjamin James Bush, Chun Wong, Junichi Yamanoi, and Thilo Gross, Modeling complex systems with adaptive networks, Computers and Mathematics with Applications, 65, 1645-1664, 2013
  • Jeffrey Schmidt and Hiroki Sayama, Designing and evaluating algorithms for automated discovery of adaptive network models based on Generative Network Automata, Proceedings of the Fourth IEEE Symposium on Artificial Life (IEEE ALIFE 2013), Singapore, 2013, IEEE, pp.27-34.
  • Jeffrey Schmidt and Hiroki Sayama, Automatic discovery of adaptive network dynamics from temporal network data, presented as a poster at NetSci 2013: International School and Conference on Network Science (also as a talk at STCAN 2013: Satellite Symposium on State-Topology Coevolution in Adaptive Networks), June 3-7, 2013, Copenhagen, Denmark.
  • Dinesh Kommareddy, Jeffrey Schmidt, John M. Darcy II, Ralph M. Garruto, and Hiroki Sayama, Modeling Lyme disease risk using a biobehavioral and ecological approach, presented as a poster at the 2013 Human Biology Association Annual Meeting, April 10-11, 2013, Knoxville, TN. Included in American Journal of Human Biology, 25(2), 263-263.
  • John M. Darcy II, Rita Spathis, Jeff Schmidt, Hannah Keppler, Sarah Hempstead, Tiana Cruz, Dinesh Kommareddy, Joel Thomas, Mellie Riddle, Hiroki Sayama, and Ralph M. Garruto, Emergence, transmission, and risk of Lyme disease and other tick-borne infections: a community based natural experimental model, presented as a poster at the 2013 Human Biology Association Annual Meeting, April 10-11, 2013, Knoxville, TN. Included in American Journal of Human Biology, 25(2), 255-255.
  • Dinesh Kommareddy, Tiana Cruz, Joel Thomas, Emma Valentine, Jeffrey Schmidt, John Darcy, Ralph Garruto, Rita Spathis, and Hiroki Sayama, Emergence, transmission, and risk of Lyme disease: A model study of Binghamton University, presented as a poster at BU-HHMI Interdisciplinary Research for Undergraduate Majors in Science and Engineering: Poster Presentation Session, July 27, 2012, Binghamton, NY.
  • Jeffrey Schmidt, Benjamin James Bush, and Hiroki Sayama, A Python implementation of generative network automata, in Hiroki Sayama, Ali A. Minai, Dan Braha, and Yaneer Bar-Yam, eds., Unifying Themes in Complex Systems Volume VIII: Proceedings of the Eighth International Conference on Complex Systems (ICCS 2011), New England Complex Systems Institute Series on Complexity, NECSI Knowledge Press, 2011, pp.439-440.
  • Benjamin James Bush, Jeffrey Schmidt, and Hiroki Sayama, Behavior and centrality in idea exchanging adaptive social networks, in Hiroki Sayama, Ali A. Minai, Dan Braha, and Yaneer Bar-Yam, eds., Unifying Themes in Complex Systems Volume VIII: Proceedings of the Eighth International Conference on Complex Systems (ICCS 2011), New England Complex Systems Institute Series on Complexity, NECSI Knowledge Press, 2011, pp.437-438.