Student Name: Deep Pujara, PhD
Email: [email protected]
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Biography:
Deep Dhavalbhai Pujara is currently pursuing a direct Ph.D. program in Electrical Engineering at Arizona State University, Tempe, Arizona. He completed his Master’s degree in Electrical Engineering at Arizona State University in December 2023 and received his Bachelor of Technology in Electronics and Communication Engineering from the Institute of Technology, Nirma University, Ahmedabad, Gujarat, India in 2021.
At ASU, Deep currently serves as a Graduate Research Associate at the Sensor, Signal and Information Processing (SenSIP) Laboratory under the supervision of Professor Andreas Spanias and Professor Cihan Tepedelenlioglu. His ongoing research focuses on the co-design of machine learning algorithms for embedded hardware, with current projects including embedded machine learning for real-time photovoltaic fault detection, topology reconfiguration of solar arrays under partial shading, and vision transformer approaches for solar data analysis. His work encompasses applications in solar energy systems, signal processing, and embedded real-time inference.
Deep currently maintains teaching responsibilities as a Graduate Teaching Associate in the School of Electrical, Computer, and Energy Engineering, where he conducts weekly laboratory sessions for EEE 598 Deep Learning. He has served as a Graduate Research Mentor for NSF-funded Research Experience for Undergraduates programs during the summers of 2022 and 2024, guiding undergraduate students in machine learning applications for photovoltaic systems, and previously supported students in EEE 407/591 Digital Signal Processing.
His current professional experience includes working as an AI Speech and Signal Processing Intern at Skyworks Solutions, developing performance simulators for custom systolic array accelerators. Previously, he served as a Broadcast Application Engineering Intern at Skyworks Solutions in the summer of 2023, designing USB-to-SPI bridge systems. His research contributions include multiple peer-reviewed conference papers on embedded machine learning and intelligent photovoltaic systems. During his undergraduate studies, he contributed to signal processing projects at the Indian Space Research Organization (ISRO) and led his team to victory in the National Level Smart India Hackathon.
List of Publications :
- J. Larson, et al., “WIP: Building a Research Experience for Undergraduates in Quantum Machine Learning,” 2024 Frontiers in Education (FIE), Washington DC, USA.
- D. Ramirez, D. Pujara, C. Tepedelenlioglu, D. Srinivasan and A. Spanias, “Infrared Computer Vision for Utility-Scale Photovoltaic Array Inspection,” 2024 15th International Conference on Information, Intelligence, Systems & Applications (IISA), Volos, Greece, 2024.
- D. Pujara, D. Ramirez, C. Tepedelenlioglu, D. Srinivasan and A. Spanias, “Real-time PV Fault Detection using Embedded Machine Learning,” 2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS), St. Louis, MO, USA, 2024, pp. 1-5.
- W. Chao, et al., “Introducing Quantum Computing in a Sophomore Signals and Systems Course,” 2023 IEEE Frontiers in Education Conference (FIE), pp. 1-5. IEEE, 2023.
- D. Pujara, D. Ramirez, C. Tepedelenlioglu, D. Srinivasan and A. Spanias, “Design of a New Photovoltaic Intelligent Monitoring and Control Device,” 2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA), Volos, Greece, 2023, pp. 1-4.
- S. Rao, D. Pujara, A. Spanias, C. Tepedelenlioglu and D. Srinivasan, “Real-time Solar Array Data Acquisition and Fault Detection using Neural Networks,” 2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS), Wuhan, China, 2023, pp. 1-5.
- D. Pujara, P. Patel and S. Gajjar, “Geo Tracking of Waste, Triggering Alerts and Mapping Areas with High Waste Index,” 2020 IEEE 17th India Council International Conference (INDICON), New Delhi, India, 2020, pp. 1-5.
- D. Pujara, P. Kukreja and S. Gajjar, “Design and Development of E-Sense: IoT based Environment Monitoring System,” 2020 IEEE Students Conference on Engineering & Systems (SCES), Prayagraj, India, 2020, pp. 1-5.
Acknowledgments:
Grateful to the ASU SenSIP Center for the opportunities and support they have provided for collaboration and research projects with the industry.