Biography: Tanay Kamlesh Patel is a Ph.D. student in Electrical Engineering and a Graduate Research Assistant at the SenSIP Center at Arizona State University, specializing in multidimensional signal processing with a focus on classical and quantum machine learning algorithms. His work spans deep learning, quantum computing, and statistical signal processing, with applications in speech, audio, music synthesis, imaging, and anomaly detection. At SenSIP, he contributes to multiple projects, including quantum-enhanced signal processing and hybrid quantum-classical deep learning models.
In addition to his research, Tanay serves as a Teaching Assistant for various signal processing courses (EEE 202, 304, 407, 509, 517, 607) , where he assists students in developing a strong foundation in signal analysis and algorithm implementation. He has mentored undergraduate, graduate students, and teachers as part of NSF-funded REU, RET, and IRES program.
Acknowledgement: Tanay extends his profound gratitude for the unwavering guidance and support from his advisors, peers, and the ASU community, who have been instrumental in his academic and personal growth. The mentorship and encouragement from them have been crucial in navigating the challenges and triumphs of his Ph.D. journey.
List of Publications :
- T. K. Patel, N. Babar, D. Pujara, G. Uehara, J. Larson, A. Spanias, “Training REU Students using Quantum Computing Tools,” (Submitted ICASSP 2026)
- T. K. Patel, D. Knutson, G. Uehara, C. Jazwin, F. Marfai, J. Larson, A. Spanias, “Image Analysis-Synthesis Using the Quantum Fourier Transform,” 2025 IEEE International Symposium on Circuits and Systems (ISCAS), London, United Kingdom, 2025, pp. 1
- Miller, T. K. Patel, G. Uehara, S. Naik and A. Spanias, “Quantum Machine Learning and Spectrogram Fusion for Speech Recognition,” 2024 58th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2024, pp. 674-678.
- J. Larson, D. Pujara, D. Ramirez, L. Miller, T. Patel, N. Babar, A. Spanias. “Building a Research Experience for Undergraduates in Quantum Machine Learning.” FIE Conference 2024. (Accepted)