Dr. Danil Prokhorov

# I am currently a head of research department with Toyota Research Institute North America, Toyota Technical Center, Ann Arbor, Michigan

# I was an technical expert with Scientific Research Laboratory of Ford Motor Co. from November 1997 till August 2005, working on neural networks and other machine learning methods for automotive system modeling, control and optimization 

# I am an active member of the the International Neural Network Society (INNS) (current Vice-President for Conferences, INNS President for 2013-14) 

I am Senior Member of both IEEE and INNS; I am also a recipient of awards including the the Best Paper Award of the IJCNN 2007 and 1999 INNS Young Investigator Award

# I have been helping the community with reviewing papers submitted to many journals and conferences; also serving as Associate Editor of several journals as well as a panelist for the U.S. National Science Foundation (NSF) proposals from academia and industry since 1995

# I got my Masters in Russia (1992) and PhD in USA (1997)

# I have many technical papers to my credit, as well as quite a few patents; see below and Google Scholar for more details

Selected publications:

- Xue Mei, Naoki Nagasaka, Bunyo Okumura, Danil V. Prokhorov: Detection and motion planning for roadside parked vehicles at long distance. Intelligent Vehicles Symposium 2015: 412-418.

- Zhibin Hong, Zhe Chen, Chaohui Wang, Xue Mei, Danil V. Prokhorov, Dacheng Tao: MUlti-Store Tracker (MUSTer): A cognitive psychology inspired approach to object tracking. CVPR 2015: 749-758

- Fairbank, M., Prokhorov, D. and Alonso, E. (2014). Clipping in neurocontrol by adaptive dynamic programmingIEEE Transactions on Neural Networks and Learning Systems, 25(10), 1909-1920.

- Fairbank, M., Prokhorov, D. and Alonso, E. (2013). Approximating Optimal Control with Value Gradient Learning. Lewis, F. and Liu, D. (Ed.), Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (pp. 142-161) Hoboken, NJ: Wiley-IEEE Press.

- Danil V. Prokhorov: A convolutional learning system for object classification in 3-D lidar data. IEEE Transactions on Neural Networks 21(5): 858-863 (2010)

- S. Singh et al., Dynamic Multiple Fault Diagnosis: Mathematical Formulations and Solution Techniques, IEEE Trans. on Systems, Man and Cybernetics (Part A), January 2009.

- D. Prokhorov (Editor), Computational Intelligence in Automotive Applications, Springer, 2008

- I. Tyukin, D. Prokhorov, and C. van Leeuwen, Adaptive Classification of Temporal Signals in Fixed-Weight Recurrent Neural Networks: An Existence Proof, Neural Computation, October 2008.

- D. Prokhorov, "Toyota Prius Neurocontrol and Diagnostics,"  Neural Networks 21(2-3): 458-465 (2008)

- S. Kalik and D. Prokhorov, Automotive Turing Test, Prof. of Performance Metrics in Intelligent Systems (PerMIS), Washington DC, August 2007.

- D. Prokhorov, "Training Neurocontrollers for Robustness with Derivative-Free Kalman Filter," IEEE Transactions on Neural Networks 17(6):1606-1616 (2006)

- D. Prokhorov, Backpropagation Through Time and Derivative Adaptive Critics: A Common Framework for Comparison. In J. Si et al. (Eds.), Learning and Approximate Dynamic Programming, Wiley, 2004.

- Lee A. Feldkamp, Danil V. Prokhorov, Timothy M. Feldkamp: Simple and conditioned adaptive behavior from Kalman filter trained recurrent networks. Neural Networks 16(5-6): 683-689 (2003)

- Prokhorov, D., Feldkamp, L., and I. Tyukin, "Adaptive Behavior with Fixed Weights in Recurrent Neural Networks: An Overview," Proc. of International Joint Conference on Neural Networks (IJCNN), WCCI'02, Honolulu, Hawaii, May 2002.

- N. Barabanov and D. Prokhorov, "Stability Analysis of Discrete-Time Recurrent Neural Networks," IEEE Trans. on Neural Networks, March 2002.

- Prokhorov, D., Feldkamp, L., and T. Feldkamp, "A New Approach to Cluster Weighted Modeling," Proc. of International Joint Conference on Neural Networks (IJCNN), Washington DC, July 2001.

- A. Petrosian, D. Prokhorov, W. Lajara-Nanson, and B. Schiffer, "Recurrent Neural Network Based Approach for Early Recognition of Alzheimer's disease in EEG," Clinical Neurophysiology, Vol.112/8, pp. 1378-1387, 2001.

- D. Prokhorov, G. Puskorius, and L. Feldkamp, Dynamical Neural Networks for Control. In J. Kolen and S. Kremer (Eds.) A Field Guide to Dynamical Recurrent Networks, IEEE Press, 2001.

- L. Feldkamp, T. Feldkamp, and D. Prokhorov, "An Approach to Adaptive Classification," in S. Haykin (Ed.) Intelligent Signal Processing, IEEE Press, 2001.

- Prokhorov, D., and D. Wunsch, "Adaptive Critic Designs," IEEE Trans. on Neural Networks, Vol. 8, No. 5, September 1997, pp. 997-1007.