Silvia Ferrari | Scholars@Duke

Silvia Ferrari
Adjunct Professor in the Department of Mechanical Engineering and Materials Science

Professor Ferrari's research aims at providing intelligent control systems with a higher degree of mathematical structure to guide their application and improve reliability. Decision-making processes are automated based on concepts drawn from control theory and the life sciences. Recent efforts have focused on the development of reconfigurable controllers implementing neural networks with procedural long-term memories. Full-scale simulations show that these controllers are capable of learning from new and unmodeled aircraft dynamics in real time, improving performance and even preventing loss of control in the event of control failures, nonlinear and near-stall dynamics, and parameter variations. New optimal control problems and methods based on computational geometry are being investigated to improve the effectiveness of integrated surveillance systems by networks of autonomous vehicles, such as, underwater gliders and ground robots.

Current Appointments & Affiliations

Adjunct Professor in the Department of Mechanical Engineering and Materials Science, Pratt School of Engineering, Duke University 2017
Faculty Network Member of the Duke Institute for Brain Sciences, Duke Institute for Brain Sciences, University Institutes and Centers 2011

Contact Information

144 Hudson Hall, Box 90300, Durham, NC 27708
301 Gross Hall, Durham, NC 27708
silvia.ferrari@duke.edu

Background
Education, Training, & Certifications
- Ph.D., Princeton University 2002
- M.A., Princeton University 1999
- B.S., Embry-Riddle Aeronautical University 1997
Duke Appointment History
- Adjunct Professor in the Department of Mechanical Engineering and Materials Science, Mechanical Engineering and Materials Science, Pratt School of Engineering 2015 - 2017
- Professor of Mechanical Engineering and Materials Science, Mechanical Engineering and Materials Science, Pratt School of Engineering 2014 - 2015
- Assistant Professor in the Department of Electrical and Computer Engineering, Electrical and Computer Engineering, Pratt School of Engineering 2009 - 2014
- Assistant Professor in the Department of Computer Science, Computer Science, Trinity College of Arts & Sciences 2010 - 2013
- Associate Professor of Mechanical Engineering and Materials Science, Mechanical Engineering and Materials Science, Pratt School of Engineering 2010 - 2013
- Assistant Professor of Mechanical Engineering and Materials Science, Mechanical Engineering and Materials Science, Pratt School of Engineering 2002 - 2009
Recognition
In the News
- JUN 3, 2014 LiveScience
  
  Engineers model better navigation systems after brain’s adaptability
Awards & Honors
- Faculty Early Career Development (CAREER) Program. National Science Foundation. 2005
Research
Selected Grants
- Bayesian Nonparametric Models to Represent Knowledge and Uncertainty for Decentralizing Planning awarded by Massachusetts Institute of Technology 2011 - 2018
- Collaborative Research: A Distributed Approximate Dynamic Programming (ADP) Approach for Robust Adaptive Control of Mult awarded by National Science Foundation 2014 - 2017
- MRI: Acquisition of a High-Resolution Stereoscopic Interactive Visualization System for Research and Education in Scienc awarded by National Science Foundation 2014 - 2016
- Collaborative Research: A Neurodynamic Programming Approach for the Modeling, Analysis, and Control of Nanoscale Neuromo awarded by National Science Foundation 2012 - 2015
- Development of a Human Pilot Model for Autonomous Driving of Vehicle Models and Reproduc the behaviour of Ferrari Driver 2013 - 2014
- A Distributed Optimal Control Approach to Managing Risk and Uncertainty in Multi-Agent Systems awarded by Office of Naval Research 2010 - 2014
- Analysis and Design of Cultured Neuronal Networks for Adaptive and Reconfigurable Control awarded by National Science Foundation 2009 - 2014
- Collaborative Research: An Adaptive Dynamic Programming Approach to the Coordination of Heterogeneous Robotic Sensors Ne awarded by National Science Foundation 2010 - 2014
- A Constrained Optimization Approach to Supervised Training of Neural Netoworks for Smooth Function Approximation and Sys awarded by National Science Foundation 2008 - 2014
- CAREER: Robust Adaptive Control, Demonstrated for Reconfigurable Flight Systems awarded by National Science Foundation 2005 - 2012
- Optimal dynamic predictions of semi-arid land cover change and implications for ecosystem goods and services 2008 - 2012
- Optimal Control of Mobile Sensor Networks awarded by Office of Naval Research 2008 - 2010
- Parametric Control of Underwater Gliders for Acoustic Sensing awarded by Office of Naval Research 2007 - 2008
- Adaptive Sensor Management and Situation Assessment for Surveillance Systems awarded by Office of Naval Research 2004 - 2007
- Analysis and Design of a Global Adaptive Critic Controller awarded by National Science Foundation 2003 - 2006
Publications & Artistic Works
Selected Publications
- Academic Articles
  - Toader, Andrew C., Hrishikesh M. Rao, Minyoung Ryoo, Martin O. Bohlen, Jessi S. Cruger, Hanna Oh-Descher, Silvia Ferrari, Tobias Egner, Jeff Beck, and Marc A. Sommer. “Probabilistic inferential decision-making under time pressure in rhesus macaques (Macaca mulatta)..” J Comp Psychol 133, no. 3 (August 2019): 380–96. https://doi.org/10.1037/com0000168.
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  - Zhu, Pingping, Silvia Ferrari, Julian Morelli, Richard Linares, and Bryce Doerr. “Scalable Gas Sensing, Mapping, and Path Planning via Decentralized Hilbert Maps..” Sensors (Basel, Switzerland) 19, no. 7 (March 28, 2019). https://doi.org/10.3390/s19071524.
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  - Gemerek, J., S. Ferrari, B. H. Wang, and M. E. Campbell. “Video-guided Camera Control for Target Tracking and Following.” Ifac Papersonline 51, no. 34 (January 1, 2019): 176–83. https://doi.org/10.1016/j.ifacol.2019.01.062.
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  - Wei, H., P. Zhu, M. Liu, J. P. How, and S. Ferrari. “Automatic pan-tilt camera control for learning Dirichlet Process Gaussian Process (DPGP) mixture models of multiple moving targets.” Ieee Transactions on Automatic Control 64, no. 1 (January 1, 2019): 159–73. https://doi.org/10.1109/TAC.2018.2849584.
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  - Foderaro, G., P. Zhu, H. Wei, T. A. Wettergren, and S. Ferrari. “Distributed Optimal Control of Sensor Networks for Dynamic Target Tracking.” Ieee Transactions on Control of Network Systems 5, no. 1 (March 1, 2018): 142–53. https://doi.org/10.1109/TCNS.2016.2583070.
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  - Zhang, Xu, Greg Foderaro, Craig Henriquez, and Silvia Ferrari. “A Scalable Weight-Free Learning Algorithm for Regulatory Control of Cell Activity in Spiking Neuronal Networks..” International Journal of Neural Systems 28, no. 2 (March 2018). https://doi.org/10.1142/s0129065717500150.
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  - Oh-Descher, Hanna, Jeffrey M. Beck, Silvia Ferrari, Marc A. Sommer, and Tobias Egner. “Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration..” Neuroimage 162 (November 15, 2017): 138–50. https://doi.org/10.1016/j.neuroimage.2017.08.069.
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  - Rudd, K., G. Foderaro, P. Zhu, and S. Ferrari. “A generalized reduced gradient method for the optimal control of very-large-scale robotic systems.” Ieee Transactions on Robotics 33, no. 5 (October 1, 2017): 1226–32. https://doi.org/10.1109/TRO.2017.2686439.
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  - Foderaro, G., A. Swingler, and S. Ferrari. “A model-based approach to optimizing Ms. Pac-Man game strategies in real time.” Ieee Transactions on Computational Intelligence and Ai in Games 9, no. 2 (June 1, 2017): 153–65. https://doi.org/10.1109/TCIAIG.2016.2523508.
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  - Oh, Hanna, Jeffrey M. Beck, Pingping Zhu, Marc A. Sommer, Silvia Ferrari, and Tobias Egner. “Satisficing in split-second decision making is characterized by strategic cue discounting..” J Exp Psychol Learn Mem Cogn 42, no. 12 (December 2016): 1937–56. https://doi.org/10.1037/xlm0000284.
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  - Wei, H., W. Lu, P. Zhu, S. Ferrari, M. Liu, R. H. Klein, S. Omidshafiei, and J. P. How. “Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models.” Automatica 74 (December 1, 2016): 360–68. https://doi.org/10.1016/j.automatica.2016.07.018.
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  - Mazumder, P., D. Hu, I. Ebong, X. Zhang, Z. Xu, and S. Ferrari. “Digital implementation of a virtual insect trained by spike-timing dependent plasticity.” Integration, the Vlsi Journal 54 (June 1, 2016): 109–17. https://doi.org/10.1016/j.vlsi.2016.01.002.
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  - Ferrari, S., G. Foderaro, P. Zhu, and T. A. Wettergren. “Distributed Optimal Control of Multiscale Dynamical Systems: A Tutorial.” Ieee Control Systems 36, no. 2 (April 1, 2016): 102–16. https://doi.org/10.1109/MCS.2015.2512034.
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  - Albertson, John D., Tierney Harvey, Greg Foderaro, Pingping Zhu, Xiaochi Zhou, Silvia Ferrari, M Shahrooz Amin, Mark Modrak, Halley Brantley, and Eben D. Thoma. “A Mobile Sensing Approach for Regional Surveillance of Fugitive Methane Emissions in Oil and Gas Production..” Environmental Science & Technology 50, no. 5 (March 2016): 2487–97. https://doi.org/10.1021/acs.est.5b05059.
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  - Lu, W., P. Zhu, and S. Ferrari. “A hybrid-adaptive dynamic programming approach for the model-free control of nonlinear switched systems.” Ieee Transactions on Automatic Control 61, no. 10 (January 1, 2016): 3203–8. https://doi.org/10.1109/TAC.2015.2509421.
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  - Wei, H., and S. Ferrari. “A geometric transversals approach to sensor motion planning for tracking maneuvering targets.” Ieee Transactions on Automatic Control 60, no. 10 (October 1, 2015): 2773–78. https://doi.org/10.1109/TAC.2015.2405292.
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  - Rudd, K., and S. Ferrari. “A constrained integration (CINT) approach to solving partial differential equations using artificial neural networks.” Neurocomputing 155 (January 1, 2015): 277–85. https://doi.org/10.1016/j.neucom.2014.11.058.
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  - Wei, H., and S. Ferrari. “A geometric transversals approach to analyzing the probability of track detection for maneuvering targets.” Ieee Transactions on Computers 63, no. 11 (November 1, 2014): 2633–46. https://doi.org/10.1109/TC.2013.43.
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  - Rudd, Keith, Gianluca Di Muro, and Silvia Ferrari. “A constrained backpropagation approach for the adaptive solution of partial differential equations..” Ieee Transactions on Neural Networks and Learning Systems 25, no. 3 (March 2014): 571–84. https://doi.org/10.1109/tnnls.2013.2277601.
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  - Foderaro, G., S. Ferrari, and T. A. Wettergren. “Distributed optimal control for multi-agent trajectory optimization.” Automatica 50, no. 1 (January 1, 2014): 149–54. https://doi.org/10.1016/j.automatica.2013.09.014.
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  - Lu, W., G. Zhang, S. Ferrari, M. Anderson, and R. Fierro. “A particle-filter information potential method for tracking and monitoring maneuvering targets using a mobile sensor agent.” Journal of Defense Modeling and Simulation 11, no. 1 (January 1, 2014): 47–58. https://doi.org/10.1177/1548512912445406.
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  - Lu, W., G. Zhang, and S. Ferrari. “An information potential approach to integrated sensor path planning and control.” Ieee Transactions on Robotics 30, no. 4 (January 1, 2014): 919–34. https://doi.org/10.1109/TRO.2014.2312812.
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  - Rudd, K., J. D. Albertson, and S. Ferrari. “Optimal root profiles in water-limited ecosystems.” Advances in Water Resources 71 (January 1, 2014): 16–22. https://doi.org/10.1016/j.advwatres.2014.04.021.
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  - Zielinski, D. J., R. Kopper, R. P. McMahan, W. Lu, and S. Ferrari. “Intercept tags: Enhancing intercept-based systems.” Proceedings of the Acm Symposium on Virtual Reality Software and Technology, Vrst, November 12, 2013, 263–66. https://doi.org/10.1145/2503713.2503737.
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  - Zielinski, D. J., R. P. McMahan, W. Lu, and S. Ferrari. “ML2VR: Providing MATLAB users an easy transition to virtual reality and immersive interactivity.” Proceedings Ieee Virtual Reality, October 7, 2013, 83–84. https://doi.org/10.1109/VR.2013.6549374.
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  - Ferrari, S., K. Rudd, and G. Di Muro. “A Constrained Backpropagation Approach to Function Approximation and Approximate Dynamic Programming,” February 7, 2013, 162–81. https://doi.org/10.1002/9781118453988.ch8.
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  - Foderaro, G., S. Ferrari, and T. A. Wettergren. “Distributed optimal control for multi-agent trajectory optimization.” Automatica, 2013.
  - Lu, W., and S. Ferrari. “An approximate dynamic programming approach for model-free control of switched systems.” Proceedings of the Ieee Conference on Decision and Control, January 1, 2013, 3837–44. https://doi.org/10.1109/CDC.2013.6760475.
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  - Rudd, K., G. Foderaro, and S. Ferrari. “A generalized reduced gradient method for the optimal control of multiscale dynamical systems.” Proceedings of the Ieee Conference on Decision and Control, January 1, 2013, 3857–63. https://doi.org/10.1109/CDC.2013.6760478.
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  - Swingler, A., and S. Ferrari. “On the duality of robot and sensor path planning.” Proceedings of the Ieee Conference on Decision and Control, January 1, 2013, 984–89. https://doi.org/10.1109/CDC.2013.6760010.
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  - Wei, H., W. Ross, S. Varisco, P. Krief, and S. Ferrari. “Modeling of human driver behavior via receding horizon and artificial neural network controllers.” Proceedings of the Ieee Conference on Decision and Control, January 1, 2013, 6778–85. https://doi.org/10.1109/CDC.2013.6760963.
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  - Zhang, X., Z. Xu, C. Henriquez, and S. Ferrari. “Spike-based indirect training of a spiking neural network-controlled virtual insect.” Proceedings of the Ieee Conference on Decision and Control, January 1, 2013, 6798–6805. https://doi.org/10.1109/CDC.2013.6760966.
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  - Foderaro, G., A. Swingler, and S. Ferrari. “A model-based cell decomposition approach to on-line pursuit-evasion path planning and the video game Ms. Pac-Man.” 2012 Ieee Conference on Computational Intelligence and Games, Cig 2012, December 1, 2012, 281–87. https://doi.org/10.1109/CIG.2012.6374167.
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  - Tolic, D., R. Fierro, and S. Ferrari. “Optimal self-triggering for nonlinear systems via Approximate Dynamic Programming.” Proceedings of the Ieee International Conference on Control Applications, December 1, 2012, 879–84. https://doi.org/10.1109/CCA.2012.6402727.
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  - Zhang, Guoxian, Silvia Ferrari, and Chenghui Cai. “A comparison of information functions and search strategies for sensor planning in target classification..” Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : A Publication of the Ieee Systems, Man, and Cybernetics Society 42, no. 1 (February 2012): 2–16. https://doi.org/10.1109/tsmcb.2011.2165336.
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  - Ferrari, S., and G. Daugherty. “A Q-learning approach to automated unmanned air vehicle demining.” Journal of Defense Modeling and Simulation 9, no. 1 (January 1, 2012): 83–92. https://doi.org/10.1177/1548512911414599.
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  - Maheswaranathan, Niru, Silvia Ferrari, Antonius M. J. Vandongen, and Craig S. Henriquez. “Emergent bursting and synchrony in computer simulations of neuronal cultures..” Front Comput Neurosci 6 (2012). https://doi.org/10.3389/fncom.2012.00015.
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  - Ferrari, S., M. Anderson, R. Fierro, and W. Lu. “Cooperative navigation for heterogeneous autonomous vehicles via approximate dynamic programming.” Proceedings of the Ieee Conference on Decision and Control, December 1, 2011, 121–27. https://doi.org/10.1109/CDC.2011.6161127.
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  - Foderaro, G., V. Raju, and S. Ferrari. “A cell decomposition approach to online evasive path planning and the video game Ms. Pac-Man.” Ieee International Symposium on Intelligent Control Proceedings, November 7, 2011, 191–97. https://doi.org/10.1109/ISIC.2011.6045414.
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  - Lu, W., G. Zhang, S. Ferrari, R. Fierro, and I. Palunko. “An information potential approach for tracking and surveilling multiple moving targets using mobile sensor agents.” Proceedings of Spie the International Society for Optical Engineering 8045 (September 26, 2011). https://doi.org/10.1117/12.884116.
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  - Ferrari, S., J. Sarangapani, and F. L. Lewis. “Special issue on approximate dynamic programming and reinforcement learning.” Journal of Control Theory and Applications 9, no. 3 (August 1, 2011). https://doi.org/10.1007/s11768-011-1104-1.
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  - Foderaro, G., V. Raju, and S. Ferrari. “A model-based approximate λ-policy iteration approach to online evasive path planning and the video game Ms. Pac-Man.” Journal of Control Theory and Applications 9, no. 3 (August 1, 2011): 391–99. https://doi.org/10.1007/s11768-011-0272-3.
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  - Bezzo, N., R. Fierro, A. Swingler, and S. Ferrari. “A disjunctive programming approach for motion planning of mobile router networks.” International Journal of Robotics and Automation 26, no. 1 (March 7, 2011): 13–25. https://doi.org/10.2316/Journal.206.2011.1.206-3405.
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  - Bernard, B., and S. Ferrari. “A geometric transversals approach to analyzing track coverage of omnidirectional sensor networks for maneuvering targets.” Proceedings of the Ieee Conference on Decision and Control, December 1, 2010, 1243–49. https://doi.org/10.1109/CDC.2010.5717198.
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  - Ferrari, Silvia, Guoxian Zhang, and Thomas A. Wettergren. “Probabilistic track coverage in cooperative sensor networks..” Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : A Publication of the Ieee Systems, Man, and Cybernetics Society 40, no. 6 (December 2010): 1492–1504. https://doi.org/10.1109/tsmcb.2010.2041449.
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  - Foderaro, G., C. Henriquez, and S. Ferrari. “Indirect training of a spiking neural network for flight control via spike-timing-dependent synaptic plasticity.” Proceedings of the Ieee Conference on Decision and Control, December 1, 2010, 911–17. https://doi.org/10.1109/CDC.2010.5717260.
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  - Foderaro, G., and S. Ferrari. “Necessary conditions for optimality for a distributed optimal control problem.” Proceedings of the Ieee Conference on Decision and Control, December 1, 2010, 4831–38. https://doi.org/10.1109/CDC.2010.5718021.
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  - Lu, W., G. Zhang, and S. Ferrari. “A randomized hybrid system approach to coordinated robotic sensor planning.” Proceedings of the Ieee Conference on Decision and Control, December 1, 2010, 3857–64. https://doi.org/10.1109/CDC.2010.5717351.
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  - Swingler, A., and S. Ferrari. “A cell decomposition approach to cooperative path planning and collision avoidance via disjunctive programming.” Proceedings of the Ieee Conference on Decision and Control, December 1, 2010, 6329–36. https://doi.org/10.1109/CDC.2010.5717137.
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  - Ferrari, S., G. Foderaro, and A. Tremblay. “A probability density function approach to distributed sensors' path planning.” Proceedings Ieee International Conference on Robotics and Automation, August 26, 2010, 432–39. https://doi.org/10.1109/ROBOT.2010.5509184.
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  - Ferrari, S., and G. Foderaro. “A potential field approach to finding minimum-exposure paths in wireless sensor networks.” Proceedings Ieee International Conference on Robotics and Automation, August 26, 2010, 335–41. https://doi.org/10.1109/ROBOT.2010.5509193.
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  - Ferrari, S., and G. Daugherty. “Q-learning approach to automated Unmanned Air Vehicle (UAV) demining.” Proceedings of Spie the International Society for Optical Engineering 7692 (June 25, 2010). https://doi.org/10.1117/12.850135.
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  - Ferrari, S., R. Fierro, and D. Tolic. “A geometric optimization approach to tracking maneuvering targets using a heterogeneous mobile sensor network.” Proceedings of the Ieee Conference on Decision and Control, December 1, 2009, 1080–87. https://doi.org/10.1109/CDC.2009.5400166.
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  - Zhang, G., and S. Ferrari. “An adaptive artificial potential function approach for geometric sensing.” Proceedings of the Ieee Conference on Decision and Control, December 1, 2009, 7903–10. https://doi.org/10.1109/CDC.2009.5399490.
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  - Di Muro, G., and S. Ferrari. “A constrained backpropagation approach to solving Partial Differential Equations in non-stationary environments.” Proceedings of the International Joint Conference on Neural Networks, November 18, 2009, 685–89. https://doi.org/10.1109/IJCNN.2009.5179018.
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  - Baumgartner, K. A. C., S. Ferrari, and A. V. Rao. “Optimal control of an underwater sensor network for cooperative target tracking.” Ieee Journal of Oceanic Engineering 34, no. 4 (November 3, 2009): 678–97. https://doi.org/10.1109/JOE.2009.2025643.
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  - Baumgartner, K. A. C., S. Ferrari, and T. A. Wettergren. “Robust deployment of dynamic sensor networks for cooperative track detection.” Ieee Sensors Journal 9, no. 9 (September 1, 2009): 1029–48. https://doi.org/10.1109/JSEN.2009.2025836.
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  - Zhang, G., S. Ferrari, and M. Qian. “An information roadmap method for robotic sensor path planning.” Journal of Intelligent and Robotic Systems: Theory and Applications 56, no. 1–2 (September 1, 2009): 69–98. https://doi.org/10.1007/s10846-009-9318-x.
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  - Cai, Chenghui, and Silvia Ferrari. “Information-driven sensor path planning by approximate cell decomposition..” Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : A Publication of the Ieee Systems, Man, and Cybernetics Society 39, no. 3 (June 2009): 672–89. https://doi.org/10.1109/tsmcb.2008.2008561.
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  - Ferrari, Silvia, and Chenghui Cai. “Information-driven search strategies in the board game of CLUE..” Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : A Publication of the Ieee Systems, Man, and Cybernetics Society 39, no. 3 (June 2009): 607–25. https://doi.org/10.1109/tsmcb.2008.2007629.
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  - Ferrari, Silvia. “Multiobjective algebraic synthesis of neural control systems by implicit model following..” Ieee Transactions on Neural Networks 20, no. 3 (March 2009): 406–19. https://doi.org/10.1109/tnn.2008.2008332.
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  - Ferrari, S., R. Fierro, B. Perteet, C. Cai, and K. Baumgartner. “A geometric optimization approach to detecting and intercepting dynamic targets using a mobile sensor network.” Siam Journal on Control and Optimization 48, no. 1 (January 1, 2009): 292–320. https://doi.org/10.1137/07067934X.
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  - Fierro, R., S. Ferrari, and C. Cai. “An information-driven framework for motion planning in robotic sensor networks: Complexity and experiments.” Proceedings of the Ieee Conference on Decision and Control, December 1, 2008, 483–89. https://doi.org/10.1109/CDC.2008.4739437.
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  - Cai, C., and S. Ferrari. “A Q-learning approach to developing an automated neural computer player for the board game of CLUE®.” Proceedings of the International Joint Conference on Neural Networks, November 24, 2008, 2346–52. https://doi.org/10.1109/IJCNN.2008.4634123.
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  - Di Muro, G., and S. Ferrari. “A constrained-optimization approach to training neural networks for smooth function approximation and system identification.” Proceedings of the International Joint Conference on Neural Networks, November 24, 2008, 2353–59. https://doi.org/10.1109/IJCNN.2008.4634124.
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  - Ferrari, S., B. Mehta, G. Di Muro, A. M. J. VanDongen, and C. Henriquez. “Biologically realizable reward-modulated hebbian training for spiking neural networks.” Proceedings of the International Joint Conference on Neural Networks, November 24, 2008, 1780–86. https://doi.org/10.1109/IJCNN.2008.4634039.
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  - Baumgartner, K., S. Ferrari, and G. Palermo. “Constructing Bayesian networks for criminal profiling from limited data.” Knowledge Based Systems 21, no. 7 (October 1, 2008): 563–72. https://doi.org/10.1016/j.knosys.2008.03.019.
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  - Baumgartner, K., and S. Ferrari. “A geometric transversal approach to analyzing track coverage in sensor networks.” Ieee Transactions on Computers 57, no. 8 (August 1, 2008): 1113–28. https://doi.org/10.1109/TC.2008.56.
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  - Ferrari, Silvia, James E. Steck, and Rajeev Chandramohan. “Adaptive feedback control by constrained approximate dynamic programming..” Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : A Publication of the Ieee Systems, Man, and Cybernetics Society 38, no. 4 (August 2008): 982–87. https://doi.org/10.1109/tsmcb.2008.924140.
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  - Ferrari, Silvia, and Mark Jensenius. “A constrained optimization approach to preserving prior knowledge during incremental training..” Ieee Transactions on Neural Networks 19, no. 6 (June 2008): 996–1009. https://doi.org/10.1109/tnn.2007.915108.
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  - Bruzzone, R., M. Strano, G. Palermo, K. C. Baumgartner, and S. Ferrari. “Network Models of Criminal Behavior.” Ieee Control Systems 28, no. 4 (January 1, 2008): 65–77. https://doi.org/10.1109/MCS.2008.924037.
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  - Ferrari, S., R. Fierro, B. Perteet, C. Cai, and K. C. Baumgartner. “A Multi-Objective Optimization Approach to Detecting and Intercepting Dynamic Targets Using Mobile Sensors.” Siam Journal on Control and Optimization, 2008.
  - Baumgartner, K., and S. Ferrari. “Optimal placement of a moving sensor network for track coverage.” Proceedings of the American Control Conference, December 1, 2007, 4040–46. https://doi.org/10.1109/ACC.2007.4282825.
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  - Cai, C., S. Ferrari, and M. Qian. “Bayesian network modeling of acoustic sensor measurements.” Proceedings of Ieee Sensors, December 1, 2007, 345–48. https://doi.org/10.1109/ICSENS.2007.4388406.
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  - Cai, C., and S. Ferrari. “Comparison of information-theoretic objective functions for decision support in sensor systems.” Proceedings of the American Control Conference, December 1, 2007, 3559–64. https://doi.org/10.1109/ACC.2007.4282852.
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  - Ferrari, S., C. Cai, R. Fierro, and B. Perteet. “A geometric optimization approach to detecting and intercepting dynamic targets.” Proceedings of the American Control Conference, December 1, 2007, 5316–21. https://doi.org/10.1109/ACC.2007.4282986.
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  - Chandramohan, R., J. E. Steck, K. Rokhsaz, and S. Ferrari. “Adaptive critic flight control for a general aviation aircraft: Simulations for the beech bonanza fly-by-wire test bed.” Collection of Technical Papers 2007 Aiaa Infotech at Aerospace Conference 1 (November 5, 2007): 840–55.
  - Cai, C., and S. Ferrari. “On the development of an intelligent computer player for CLUE®: A case study on preposterior decision analysis.” Proceedings of the American Control Conference 2006 (December 1, 2006): 4350–55.
  - Ferrari, S. “Track coverage in sensor networks.” Proceedings of the American Control Conference 2006 (December 1, 2006): 2053–59.
  - Ferrari, S., and A. Vaghi. “Demining sensor modeling and feature-level fusion by bayesian networks.” Ieee Sensors Journal 6, no. 2 (April 1, 2006): 471–83. https://doi.org/10.1109/JSEN.2006.870162.
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  - Baumgartner, K. C., S. Ferrari, and C. G. Salfati. “Bayesian network modeling of offender behavior for criminal profiling.” Proceedings of the 44th Ieee Conference on Decision and Control, and the European Control Conference, Cdc Ecc ’05 2005 (December 1, 2005): 2702–9. https://doi.org/10.1109/CDC.2005.1582571.
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  - Ferrari, S., and M. Jensenius. “Robust and reconfigurable flight control by neural networks.” Collection of Technical Papers Infotech at Aerospace: Advancing Contemporary Aerospace Technologies and Their Integration 2 (December 1, 2005): 1161–66.
  - Qian, M., and S. Ferrari. “Probabilistic deployment for multiple sensor systems.” Proceedings of Spie the International Society for Optical Engineering 5765, no. PART 1 (September 29, 2005): 85–96. https://doi.org/10.1117/12.601597.
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  - Ferrari, Silvia, and Robert F. Stengel. “Smooth function approximation using neural networks..” Ieee Transactions on Neural Networks 16, no. 1 (January 2005): 24–38. https://doi.org/10.1109/tnn.2004.836233.
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  - Ferrari, S., and R. F. Stengel. “Online adaptive critic flight control.” Journal of Guidance, Control, and Dynamics 27, no. 5 (January 1, 2004): 777–86. https://doi.org/10.2514/1.12597.
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  - Ferrari, S., and R. F. Stengel. “Classical/neural synthesis of nonlinear control systems.” Journal of Guidance, Control, and Dynamics 25, no. 3 (January 1, 2002): 442–48. https://doi.org/10.2514/2.4929.
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  - Ferrari, S., and R. F. Stengel. “An adaptive critic global controller.” Proceedings of the American Control Conference 4 (January 1, 2002): 2665–70. https://doi.org/10.1109/ACC.2002.1025189.
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  - Ferrari, S., and R. F. Stengel. “Algebraic training of a neural network.” Proceedings of the American Control Conference 2 (January 1, 2001): 1605–10. https://doi.org/10.1109/ACC.2001.945956.
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  - Ferrari, S., and R. F. Stengel. “Classical/neural synthesis of nonlinear control systems.” Aiaa Guidance, Navigation, and Control Conference and Exhibit, December 1, 2000.
  - Crispin, Y., and S. Ferrari. “Adaptive control of chaos induced capsizing of a ship.” Intelligent Engineering Systems Through Artificial Neural Networks 5 (December 1, 1995): 569–74.
- Book Sections
  - Ferrari, S., and R. F. Stengel. “Model-based adaptive critic designs.” In Handbook of Learning and Approximate Dynamic Programming, 65–95, 2004. https://doi.org/10.1109/9780470544785.ch3.
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- Conference Papers
  - Liu, C., Y. Chen, J. Gemerek, H. Yang, and S. Ferrari. “Learning recursive bayesian nonparametric modeling of moving targets via mobile decentralized sensors.” In Proceedings Ieee International Conference on Robotics and Automation, 2019-May:8034–40, 2019. https://doi.org/10.1109/ICRA.2019.8793879.
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  - Morelli, J., P. Zhu, B. Doerr, R. Linares, and S. Ferrari. “Integrated mapping and path planning for very large-scale robotic (VLSR) systems.” In Proceedings Ieee International Conference on Robotics and Automation, 2019-May:3356–62, 2019. https://doi.org/10.1109/ICRA.2019.8793795.
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  - Doerr, B., R. Linares, P. Zhu, and S. Ferrari. “Random finite set theory and optimal control of large spacecraft swarms.” In Advances in the Astronautical Sciences, 168:3729–48, 2019.
  - Liu, C., and S. Ferrari. “Vision-guided planning and control for autonomous taxiing via convolutional neural networks.” In Aiaa Scitech 2019 Forum, 2019. https://doi.org/10.2514/6.2019-0928.
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  - Clawson, T. S., T. C. Stewart, C. Eliasmith, and S. Ferrari. “An adaptive spiking neural controller for flapping insect-scale robots.” In 2017 Ieee Symposium Series on Computational Intelligence, Ssci 2017 Proceedings, 2018-January:1–7, 2018. https://doi.org/10.1109/SSCI.2017.8285173.
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  - Zhu, P., J. Isaacs, B. Fu, and S. Ferrari. “Deep learning feature extraction for target recognition and classification in underwater sonar images.” In 2017 Ieee 56th Annual Conference on Decision and Control, Cdc 2017, 2018-January:2724–31, 2018. https://doi.org/10.1109/CDC.2017.8264055.
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  - Chang, S., J. Isaacs, B. Fu, J. Shin, P. Zhu, and S. Ferrari. “Confidence level estimation in multi-target classification problems.” In Proceedings of Spie the International Society for Optical Engineering, Vol. 10628, 2018. https://doi.org/10.1117/12.2319988.
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  - Fu, B., and S. Ferrari. “Robust flight control via minimum H∞ entropy principle.” In Aiaa Guidance, Navigation, and Control Conference, 2018, 2018. https://doi.org/10.2514/6.2018-1313.
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  - Gemerek, J. R., S. Ferrari, and J. D. Albertson. “Fugitive gas emission rate estimation using multiple heterogeneous mobile sensors.” In Isoen 2017 Isocs/Ieee International Symposium on Olfaction and Electronic Nose, Proceedings, 2017. https://doi.org/10.1109/ISOEN.2017.7968897.
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  - Clawson, T. S., S. B. Fuller, R. J. Wood, and S. Ferrari. “A blade element approach to modeling aerodynamic flight of an insect-scale robot.” In Proceedings of the American Control Conference, 2843–49, 2017. https://doi.org/10.23919/ACC.2017.7963382.
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  - Clawson, T. S., S. Ferrari, S. B. Fuller, and R. J. Wood. “Spiking neural network (SNN) control of a flapping insect-scale robot.” In 2016 Ieee 55th Conference on Decision and Control, Cdc 2016, 3381–88, 2016. https://doi.org/10.1109/CDC.2016.7798778.
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  - Zhu, P., J. Morelli, and S. Ferrari. “Value function approximation for the control of multiscale dynamical systems.” In 2016 Ieee 55th Conference on Decision and Control, Cdc 2016, 5471–77, 2016. https://doi.org/10.1109/CDC.2016.7799109.
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  - Zhu, P., H. Wei, W. Lu, and S. Ferrari. “Multi-kernel probability distribution regressions.” In Proceedings of the International Joint Conference on Neural Networks, Vol. 2015-September, 2015. https://doi.org/10.1109/IJCNN.2015.7280577.
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  - Albertson, J. D., T. A. Foster-Wittig, S. Ferrari, G. Katul, and E. Thoma. “Bayesian estimation of methane emission rates from a single high-frequency gas sensor.” In Proceedings of the Air and Waste Management Association’S Annual Conference and Exhibition, Awma, 1:622–26, 2014.
  - Bellini, A. C., W. Lu, R. Naldi, and S. Ferrari. “Information driven path planning and control for collaborative aerial robotic sensors using artificial potential functions.” In Proceedings of the American Control Conference, 590–97, 2014. https://doi.org/10.1109/ACC.2014.6859095.
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  - Hu, D., X. Zhang, Z. Xu, S. Ferrari, and P. Mazumder. “Digital implementation of a spiking neural network (SNN) capable of spike-timing-dependent plasticity (STDP) learning.” In 14th Ieee International Conference on Nanotechnology, Ieee Nano 2014, 873–76, 2014. https://doi.org/10.1109/NANO.2014.6968000.
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  - Wei, H., W. Lu, P. Zhu, G. Huang, J. Leonard, and S. Ferrari. “Optimized visibility motion planning for target tracking and localization.” In Ieee International Conference on Intelligent Robots and Systems, 76–82, 2014. https://doi.org/10.1109/IROS.2014.6942543.
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  - Wei, H., W. Lu, P. Zhu, S. Ferrari, R. H. Klein, S. Omidshafiei, and J. P. How. “Camera control for learning nonlinear target dynamics via Bayesian nonparametric Dirichlet-process Gaussian-process (DP-GP) models.” In Ieee International Conference on Intelligent Robots and Systems, 95–102, 2014. https://doi.org/10.1109/IROS.2014.6942546.
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  - Lu, W., S. Ferrari, R. Fierro, and T. A. Wettergren. “Approximate dynamic programming recurrence relations for a hybrid optimal control problem.” In Proceedings of Spie the International Society for Optical Engineering, Vol. 8387, 2012. https://doi.org/10.1117/12.919286.
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  - Lu, W., G. Zhang, and S. Ferrari. “A comparison of information theoretic functions for tracking maneuvering targets.” In 2012 Ieee Statistical Signal Processing Workshop, Ssp 2012, 149–52, 2012. https://doi.org/10.1109/SSP.2012.6319645.
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  - Crispin, Y., and S. Ferrari. “Model-reference adaptive control of chaos in periodically forced dynamical systems.” In 6th Symposium on Multidisciplinary Analysis and Optimization, 882–90, 1996.

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