Directory
Chris Yakopcic
Research Scientist
Adjunct
School of Engineering: Department of Electrical and Computer Engineering
Selected Publications
- Yakopcic, C., Taha, T. M., Mountain, D. J., Salter, T., Marinella, M. J., & McLean, V. (2020, May). Memristor model optimization based on parameter extraction from device characterization data. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(5), 1804-1095.
- Yakopcic, C., Rahman, N., Atahary, T., Taha, T. M., & Douglass, S. (2020, March). Solving constraint satisfaction problems using the loihi spiking neuromorphic processor. IEEE Design, Automation and Test in Europe, 2020, 1079-1084, Grenoble, France.
- Alom, M. Z., Taha, T., Yakopcic, C., Westberg, S., Sidike, P., Nasrin, M. S., Essen, B., Awwal, A., & Asari, V. (2019, March). A state of the art survey on deep learning theory and architectures. MDPI Electronics, 8(3), 292. (Best Paper Award)
- Alom, M. Z., Yakopcic, C., Nasrin, M. S., Taha, T. M., & Asari, V. K. (2019, August). Breast cancer classification from histopathological images with inception recurrent residual convolutional neural network. Journal of Digital Imaging, 32, 605-617.
- Alom, M. Z., Hasan, M., Yakopcic, C., Taha, T. M., & Asari, V. (2019, March). Recurrent residual U-Net (R2U-Net) for medical image segmentation. Journal of Medical Imaging, 6(1).
- Bontupalli, V., Yakopcic, C., Hasan, R., & Taha, T. M. (2018, Dec.). Efficient memristor based architecture for intrusion detection and high-speed packet classification. ACM Journal on Emerging Technologies in Computing Systems (JETC) – Special Issue on Neuromorphic Computing, 14(4), 41:1-41:27.
- Yakopcic, C., Wang, S., Wang, W., Shin, E., Boeckl, J., Subramanyam, G., & Taha, T. M. (2018, Dec.). Filament formation in lithium niobate memristors supports neuromorphic programming capability. Neural Computing and Applications, 30, (12), 3773-3779.
- Yakopcic, C., Hasan, R., & Taha, T. M. (2018, Aug.). Flexible memristor based neuromorphic system for implementing multi-layer neural network algorithms. International Journal of Parallel, Emergent and Distributed Systems, 33(4), 408-429.
- Yakopcic, C., Bontupalli, V., Hasan, R., Mountain, D., & Taha, T. M. (2017, March). Self-biasing memristor crossbar used for string matching and TCAM implementation. Electronics Letters, 53(7), 463-465.
- Yakopcic, C., Taha, T. M., Subramanyam, G., & Pino, R. E. (2013, August). Memristor SPICE model and crossbar simulation with nanosecond switching time. IEEE/INNS International Joint Conference on Neural Networks (IJCNN), 1-7, Dallas, TX. (Best Paper Award)
- Yakopcic, C., Taha, T. M., Subramanyam, G., & Pino, R. E. (2013, August). Generalized memristive device SPICE model and its application in circuit design. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 32(8), 1201-1214.
- Yakopcic, C., Taha, T. M., Subramanyam, G., Pino, R. E. & Rogers, S. (2011, Oct.). A memristor device model, IEEE Electron Device Letters, 30(10), 1436-1438.
Full list of publications can be found here (https://cyakopcic1.wordpress.com/).
Selected Patents
- M. Taha, R. Hasan, C. Yakopcic, On-chip training of memristor crossbar neuromorphic processing systems, U.S. 10,855,429, Jan. 5, 2021.
- M. Taha and C. Yakopcic, Memristor crossbar configuration, U.S. 10,622,064, April 14, 2020.
- Yakopcic, R. Hasan, T. M. Taha, Analog neuromorphic circuit implemented using resistive memories, U.S. 10,474,948, Nov. 12, 2019.
- Yakopcic, T. M. Taha, and R. Hasan, Analog neuromorphic circuits for dot-product operation implementing resistive memories, U.S. Patent, US 10,176,425, Jan. 8, 2019.
Full list of publications can be found here (https://cyakopcic1.wordpress.com/).
Selected Honors and Awards
- 2020 IEEE Dayton Section Computer Society Award
- 2020 MDPI Electronics Journal Best Paper Award
- 2013 IEEE/INNS International Joint Conference on Neural Networks Best Paper Award
Courses Taught
- ECE 431L
- ECE 432L
Degrees
- Ph.D., Electrical Engineering, University of Dayton, 2014
- M.S., Electrical Engineering, University of Dayton, 2011
- B.S., Electrical Engineering, University of Dayton, 2009
Research Interests
- Low Power Autonomous Systems
- Deep Learning for Efficient and Portable Applications
- Spiking Neural Network Processors
- Memristor Based Neuromorphic Circuit Design
- Memristor Device Modeling and Characterization