Felix Wang

Biography

Felix Wang is a Senior Member of Technical Staff in the Center for Computing Research at Sandia National Laboratories. He has a background in artificial intelligence and signal processing, and he earned a Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign. His research interests include biologically inspired algorithms, complex adaptive systems, neuromorphic and neural computing, representation learning, and distributed computation.

Felix’s research focus centers around neural algorithm development, where his contributions include the design of spiking algorithms (e.g. for navigation, event-based sensors), extending their implementation onto neuromorphic platforms, research in biologically inspired learning algorithms, and large-scale spiking neural network simulations. He is the lead developer of the parallel neural simulator STACS (Simulation Tool for Asynchronous Cortical Streams).

Education

• Ph.D., Electrical and Computer Engineering, University of Illinois at Urbana-Champaign (UIUC), 2018
  • Thesis: Polychronization as a Mechanism for Language Acquisition in Spiking Neural Networks
• M.S., Electrical and Computer Engineering, UIUC, 2014
• B.S., Electrical and Computer Engineering, UIUC, 2011

Publications

• F. Wang, S. Kulkarni, B. Theilman, F. Rothganger, C. Schuman, S. Lim, J. B. Aimone, “Scaling neural simulations in STACS,” Neuromorphic Computing and Engineering, vol. 4, no. 2, pp. 024002, Apr. 2024
• K. Michaelson, F. Wang, R. Zanetti, “Terrain-relative navigation with neuro-inspired elevation encoding,” in Proceedings of the IEEE/ION Position Location and Navigation Symposium (PLANS), Monterey, CA: Apr. 2023
• M. M. Baker, A. New, M. Aguilar-Simon, Z. Al-Halah, S. M. R. Arnold, E. Ben-Iwhiwhu, A. P. Brna, E. Brooks, R. C. Brown, Z. Daniels, A. Daram, F. Delattre, R. Dellana, E. Eaton, H. Fu, K. Grauman, J. Hostetler, S. Iqbal, C. Kent, N. Ketz, S. Kolouri, G. Konidaris, D. Kudithipudi, E. Learned-Miller, S. Lee, M. L. Littman, S. Madireddy, J. A. Mendez, E. Q. Nguyen, C. Piatko, P. K. Pilly, A. Raghavan, A. Rahman, S. K. Ramakrishnan, N. Ratzlaff, A. Soltoggio, P. Stone, I. Sur, Z. Tang, S. Tiwari, K. Vedder, F. Wang, Z. Xu, A. Yanguas-Gil, H. Yedidsion, S. Yu, G. K. Vallabha, “A domain-agnostic approach for characterization of lifelong learning systems.” Neural Networks, vol. 160, pp. 274-296, Mar. 2023
• F. Wang, C. Teeter, S. Luca, S. Musuvathy, J. B. Aimone, “Distributed localization with grid-based representations on digital elevation models,” in Proceedings of the International Conference on Neuromorphic Systems (ICONS), Knoxville, TN: Jul. 2022
• D. Kudithipudi, M. Aguilar-Simon, J. Babb, M. Bazhenov, D. Blackiston, J. Bongard, A. P. Brna, S. C. Raja, N. Cheney, J. Clune, A. Daram, S. Fusi, P. Helfer, L. Kay, N. Ketz, Z. Kira, J. L. Krichmar, S. Kriegman, M. Levin, S. Madireddy, S. Manicka, A. Marjaninejad, B. McNaughton, R. Miikkulainen, Z. Navratilova, T. Pandit, A. Parker, P. Pilly, S. Risi, T. J. Sejnowski, N. Soures, A. S. Tolias, D. Urbina-Melendez, F. J. Valero-Cuevas, G. M. van de Ven, J. T. Vogelstein, F. Wang, R. Weiss, A. Yanguas-Gil, X. Zou, and H. Siegelmann, “Biological Underpinnings for Lifelong Learning Machines,” Nature Machine Intelligence, vol. 4, no. 3, pp. 196-210, Mar. 2022
• C. M. Vineyard, S. Cardwell, F. Chance, S. Musuvathy, F. Rothganger, W. Severa, J. D. Smith, C. Teeter, F. Wang, J. B. Aimone, “Neural Mini-Apps as a Tool for Neuromorphic Computing Insight,” in Proceedings of the Neuro-Inspired Computational Elements (NICE) Conference, ser. NICE ’22, Virtual Event, USA: ACM, pp. 40-49, Mar. 2022
• S. Cardwell, C. M. Vineyard, W. Severa, F. Chance, F. Rothganger, F. Wang, S. Musuvathy, C. M. Teeter, J. B. Aimone, “Truly heterogenous HPC: co-design to achieve what science needs from HPC,” in Proceedings of the 2020 Smoky Mountains Computational Sciences and Engineering Conference (SMC2020), Virtual Event, USA: Aug. 2020
• F. Chance, J. B. Aimone, S. Musuvathy, M. Smith, C. M. Vineyard, F. Wang, “Crossing the cleft: communication challenges between neuroscience and artificial intelligence,” Frontiers in Computational Neuroscience, vol. 14, May 2020
• A. Yanguas-Gil, A. Mane, J. W. Elam, F. Wang, W. Severa, A. R. Daram, “The insect brain as a model system for low power electronics and edge processing applications,” in Proceedings of the 2019 IEEE Space Computing Conference (SCC), Pasadena, CA, USA: Aug. 2019
• F. Wang, W. Severa, F. Rothganger, “Acquisition and Representation of Spatio-Temporal Signals in Polychronizing Spiking Neural Networks,” in Proceedings of the Neuro-Inspired Computational Elements (NICE) Workshop, ser. NICE ’19. New York, NY, USA: ACM, pp. 11:1-11:5, Mar. 2019
• W. Severa, A. J. Hill, C. M. Vineyard, R. Dellana, L. Reeder, F. Wang, J. B. Aimone, A. Yanguas-Gil, “Building a Comprehensive Neuromorphic Platform for Remote Computation,” in 2019 Government Microcircuit Applications and Critical Technology (GOMACTech) Conference, Albuquerque, NM, USA: Mar. 2019
• F. Wang, T. Quach, J. Wheeler, J. B. Aimone, C. D. James, “Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification,” IEEE Transactions on Information Forensics and Security, vol. 13, no. 10, pp. 2553-2562, Oct. 2018
• A. J. Hill, J. W. Donaldson, F. H. Rothganger, C. M. Vineyard, D. R. Follett, P. L. Follett, M. R. Smith, S. J. Verzi, W. Severa, F. Wang, J. B. Aimone, J. H. Naegle, C. D. James, “A Spike-Timing Neuromorphic Architecture,” 2017 IEEE International Conference on Rebooting Computing (ICRC), Washington, DC, USA, pp. 1-8, Nov. 2017
• F. Wang, “Simulation Tool for Asynchronous Cortical Streams (STACS): Interfacing with Spiking Neural Networks,” in 5th Complex Adaptive Systems (CAS) Conference, San Jose, CA, USA: Procedia Computer Science, vol. 61, pp. 322-327, Nov. 2015
• I. Karlin, A. Bhatele, J. Keasler, B. L. Chamberlain, J. Cohen, Z. DeVito, R. Haque, D. Laney, E. Luke, F. Wang, D. Richards, M. Schulz, C. Still, “Exploring traditional and emerging parallel programming models using a proxy application,” in 27th IEEE International Parallel and Distributed Processing Symposium (IPDPS), Boston, MA, USA: IEEE Computer Society, pp. 919-932, May 2013

Patents & Trademarks

• F. Wang, J. B. Aimone, “Grid-based coding of terrain maps for localization,” Application no. 18/127,830 (filed), Mar. 2023