Dr. Foo is a tenured professor at the Department of Electrical and Computer Engineering at Florida A&M University and Florida State University and the FAMU-FSU College of Engineering. His main research contributions have been in the areas of photovoltaics and machine learning/artificial intelligence. Dr. Foo has authored or co-authored over 150 refereed technical papers and contributed to two book chapters. He has also graduated more than 50 MS and PhD students. He is the Principal Investigator (PI) of more than 20+ funded research projects. His primary research sponsors include the National Aeronautics and Space Administration (NASA), Department of Energy (DOE), National Security Agency (NSA), National Science Foundation (NSF), Air Force Office of Scientific Research (AFOSR), Office of Naval Research (ONR), Boeing Aircraft Company, and the Florida Department of Transportation (FDOT). He also serves as a technical advisor to Airbus in the area of fire detection in aircraft cargo bays. Besides the “Engineering Research Awards” (2004 and 2008) from the FAMU-FSU College of Engineering, he also won the “Teaching Incentive Award” (1995), “Teacher of the Year” award in 2001, and Tau Beta Pi “Teacher of the Year” award in 2010, and two "Best Paper" awards (2001 and 2004). Dr. Foo is a member of Eta Kappa Nu Electrical Engineering Honor Society, since 1982.
Academic Positions
(All held at FAMU-FSU College of Engineering, Tallahassee, FL)
- Chair, Electrical & Computer Engineering, July 2010 – June 2018
- Professor, Electrical & Computer Engineering, August 2005 – present
- Associate Professor of Electrical & Computer Engineering, August 1995 – July 2005
- Assistant Professor of Electrical & Computer Engineering, August 1990 - 1995
- Visiting Assistant Professor of Electrical Engineering, August 1988 – 1990
Ph.D. Students Graduated
- Migara Amarasinghe, "Paralellizing Complexity: Strategies for Accelerating AI Algorithms and Scientific Simulations in Heterogenous Computing Environments", Summer 2024
- Ayodeji Ogundana, “State of Charge Estimation of Lithium Ion Battery for Electric Vehicle Application”, Spring 2024
- Pranaya Krishna Terala, “Battery State of Charge Estimation using Generative Deep Learning for Electric Vehicle Applications”, Fall 2023
- Jackie Jermyn, “Generating and Evaluating Camouflage Patterns for Littoral Environments of Northwest Florida,” Fall 2022
- Huanyu Zang, “Facial Emotion Recognition Using Asymmetric Pyramidal Networks With Gradient Centralization and Learnable Preprocessors,” Fall 2022
- Davis George Moye, “A design-based predictive model for lithium-ion capacitors,” Fall 2019
- Jobeda Jamal Khanam, “Efficient, Stable, and Low-Cost PbS Quantum Dot Solar Cells with Cr-Ag Electrodes,” Fall 2019
- Ifedayo Ogundana, “Improving the Morphology of the Perovskite Absorber Layer in Hybrid Organic/Inorganic Halide Perovskite MAPbI3 Solar Cells,” Summer 2017, currently with Intel Corporation, Austin, TX
- Dana Skinner, "Compressive Sensing: Optimal Reconstruction", Fall 2013, currently with National Security Agency (NSA), Fall 2013
- Indranil Bhattacharya, "Modeling and Simulation of High-Efficiency Multijunction Solar Cells", Summer 2013, currently Chair and Professor, Department of Electrical and Computer Engineering, with Tennessee State University, Cookeville, TN, Fall 2013
- Yuhang Deng, "Study of Multiphase Bidirectional DC-DC Converter Interfacing with Energy Storage for Fuel Cell Vehicle Using Power Hardware-In-the-Loop Concept", Fall 2010, was with General Electric (GE), Dallas, TX.
- Masood Ejaz, "Fast Independent Component Analysis", Spring 2008, currently Professor at Valencia College, Florida
- Jeffrey Connor, "Antenna Array Synthesis Using the Cross-Entropy Method", Summer 2008, was with ArgonST (Boeing), Washington, DC
- Erastus Ogunti, "Power Analysis of Resonant Clocks", Summer 2008, currently Professor and Chair, Department of Electrical Engineering, Federal University of Technology at Akure (FUTA), Nigeria
- Jason Isaacs, "Kernel PCA and Kernel ICA", Spring 2007, currently Senior Scientist, Naval Surface Warfare Center (NSWC), Panama City, FL
- Dan Belc, "Hybrid Wavelet Filter for Medical Image Compression", Spring 2006, was with Siemens, Germany
- Shonda Walker,"Optimal Wavelets for Robust Speech Recognition", Spring 2003, formerly Associate Professor at Georgia Southern, currently Associate Professor at Florida A&M University
X. Xiang, R. Diao, S. Bernadin, S. Y. Foo, F. Sun, A. Ogundana, "An Intelligent Parameter Identification Method of DFIG Systems Using Hybrid Particle Swarm Optimization and Reinforcement Learning," IEEE Access.(2024) https://doi.org/10.1109/ACCESS.2024.3379146
A. S. Ogundana, P. K. Terala, M. Y. Amarasinghe, X. Xiang and S. Y. Foo, "Electric Vehicle Battery State of Charge Estimation With an Ensemble Algorithm Using Central Difference Kalman Filter (CDKF) and Non-Linear Autoregressive With Exogenous Input (NARX)," in IEEE Access (2024), vol. 12, pp. 33705-33719, 2024, https://doi.org/ 10.1109/ACCESS.2024.3371883
Terala, P.; Ogundana, A.; Foo, S. Y.,; Amarasinghe, M.; Zang, H.; State of Charge estimation of Lithium-ion batteries using stacked Encoder-decoder bi-directional LSTM for EV and HEV applications. Micromachines 2022, 15, x. https://doi.org/10.3390/xxxxx
Shohan, Md Jamal Ahmed, Md Omar Faruque, and S. Y. Foo. 2022. "Forecasting of Electric Load Using a Hybrid LSTM-Neural Prophet Model" Energies 15, no. 6: 2158. https://doi.org/10.3390/en15062158
Xiang, X.; S. Y. Foo, Zang, H. Recent Advances in Deep Reinforcement Learning Applications for Solving Partially Observable Markov Decision Processes (POMDP), Problems Part 2—Applications in Transportation, Industries, Communications and Networking and More Topics. Mach. Learn. Knowl. Extr. 2021, 3, 863–878. https://doi.org/10.3390/make3040043
X. Xiang and S. Y. Foo, "Recent Advances in Deep Reinforcement Learning Applications for Solving Partially Observable Markov Decision Processes (POMDP) Problems: Part 1—Fundamentals and Applications in Games, Robotics and Natural Language Processing," Mach. Learn. Knowl. Extr. 2021, 3(3), 554-581; https://doi.org/10.3390/make3030029
H. Zang, S. Y. Foo, S. Bernadin and A. Meyer-Baese, "Facial Emotion Recognition Using Asymmetric Pyramidal Networks With Gradient Centralization," in IEEE Access, vol. 9, pp. 64487-64498, 2021, doi: 10.1109/ACCESS.2021.3075389.
J. J. Khanam, S. Y. Foo, "A comparison of machine learning algorithms for diabetes prediction," ICT Express, ScienceDirect, 2021, ISSN 2405-9595, https://doi.org/10.1016/j.icte.2021.02.004.
DG Moye, PL Moss, X Chen, W Cao, S. Y. Foo, "Observations on Arrhenius Degradation of Lithium-Ion Capacitors," Materials Sciences and Applications 11 (7), 450-461, 2020.
D.G.Moye, P.L.Moss, X.J.Chen, W.J.Cao, S.Y.Foo, “A design-based predictive model for lithium-ion capacitors,” Journal of Power Sources, Vol. 435, 30 September 2019, https://doi.org/10.1016/j.jpowsour.2019.226694.
Khanam JJ, Foo SY, Yu Z, Liu T, Mao P, "Efficient, Stable, and Low-Cost PbS Quantum Dot Solar Cells with Cr-Ag Electrodes," Nanomaterials (Basel). 2019 Aug 27;9(9). pii: E1205. doi: 10.3390/nano9091205.
H. Szu, S. Y. Foo, et al, “The 3rd wave AI requirements,” MedCrave MOJ Applied Bionics and Biomechanics, Vol. 3, Issue 1, pp. 18-22, 2019.
A. Meyer-Baese, S. Y. Foo, et al, “Pinning observability of competitive neural networks with different time–constants,” Neurocomputing, Vol. 329, pp. 97-102, 2019.
J. Khanam, and S. Y. Foo, “Modeling of High Efficiency Multijunction Polymer and Hybrid Solar Cells which can absorb Infrared Light,” Polymers 2019, Vol. 11, Issue 1, 2019.
Amirhessam Tahmassebi, Amir H. Gandomi, Mieke H. J. Schulte, Anna E. Goudriaan, Simon Y. Foo, and Anke Meyer-Baese, "Optimized Naive-Bayes and Decision Tree Approaches for fMRI Smoking Cessation Classification," Hindawi Complexity Journal, Volume 2018, Article ID 2740817, 24 pages. 2018. https://doi.org/10.1155/2018/2740817.
J. M. Padilla, U. Meyer-Baese, and S. Y. Foo, "Security evaluation of Tree Parity Re-keying Machine implementations utilizing side-channel emissions," EURASIP Journal on Information Security, Vol. 3, 2018. https://doi.org/10.1186/s13635-018-0073-z.
J. Khanam and S. Y. Foo, "Modeling of a photovoltaic array in MATLAB simulink and maximum power point tracking using neural network," Electrical & Electronic Technology Journal (2018), Vol. 2, Issue 3, pp. 40-46. 2018. https://medcraveonline.com/EETOAJ/EETOAJ-02-00019.pdf.
Microsoft Summer Faculty program, Summer 2021
Summer Faculty Research Associate, Naval Surface Warfare Center (NSWC), Panama City, FL, Summer 2007. Investigated Markov random field models for sonar imagery
Engineering Consultant, Airbus Company, Germany, Summer 2003. Provided input to the design of a visibility sensor system for aircraft fire detection
Engineering Consultant, RCC-Omnicom, Inc., Tallahassee, FL, Summer 1997 and 1998. Developed Software for Calculating Radio Wave Diffraction Loss due to Knife Edges and developed Software for Neural Network Modeling of the Time-Delay Interference problem
Research Associate, Air Force Summer Faculty Research Program, Fuze Test Branch, Eglin Air Force Base, FL, Summer 1992. Project: Passive Ranging using Binocular Vision
Research Associate, Air Force Summer Faculty Research Program, Fuze Test Branch, Eglin Air Force Base, FL, Summer 1993. Project: Etching semiconductors with a Scanning Tunneling Microscope
IC Designer/Engineer, International Chip Corporation, Columbia, SC, Summer 1986. Project: Integrating communication circuit boards onto custom CMOS VLSI chips
Jobeda J. Khanam and Simon Y. Foo, “Photovoltaic devices and methods, Part B2” US Patent number: 12,009,443 B2. Granted on June 11, 2024.
Jobeda J. Khanam and Simon Y. Foo, “Photovoltaic devices and methods,” US Patent number: 11,522,094. Granted on December 6, 2022.
Indranil Bhattacharya and Simon Y. Foo, US Patent Application No. US 61/219,926, “High Efficiency Photovoltaic Cell for Solar Energy Harvesting”, filed (Florida State University Research Foundation) with the US Patent and Trademark Office on June 24, 2010. Granted in November 2013.