I am an Assistant Professor in the Department of Computer Engineering and Computer Science at California State University, Long Beach. I received my Ph.D. in Computer Science from The University of Texas at San Antonio, where I also earned my M.S. degree in Computer Engineering. Prior to my doctoral studies, I worked as a Software Development Engineer for three years.

My research interests span embedded systems, energy-harvesting Internet of Things (IoT), over-the-air (OTA) firmware updates, intermittent computing, edge AI, Tiny Machine Learning (TinyML), and sustainable computing. My research focuses on designing reliable and energy-efficient systems that enable resource-constrained IoT devices to operate, learn, adapt, and update under intermittent power and tight energy, memory, and computational constraints.

Recent News

August 2026: Joined the Department of Computer Engineering and Computer Science at California State University, Long Beach as an Assistant Professor.

November 2025: Our paper “AERO: Adaptive and Efficient Runtime-Aware OTA Updates for Energy-Harvesting IoT” has been accepted to DATE’26.

January 2025: Our papers, “Energy-Adaptive Checkpoint-Free Intermittent Inference for Low Power Energy Harvesting Systems” and “Energy-efficient Persistently Secure Block-based Differential Checkpointing for Energy Harvesting Devices”, have been accepted to ISQED’25.

August 2024: Successfully defended dissertation proposal and became a Ph.D. Candidate.

July 2024: Received NSF ISVLSI Student Travel Grant Award and the Graduate School Professional Development Travel Award.

June 2024: Our paper “Intermittent OTA Code Update Framework for Tiny Energy Harvesting Devices” has been accepted to TCAD.

May 2024: Our paper “Energy-aware Incremental OTA Update for Flash-based Batteryless IoT Devices” has been accepted to ISVLSI’24.

April 2024: Our paper “Autotile: Autonomous Task-tiling for Deep Inference on Battery-less Embedded System” has been accepted to GLSVLSI’24.

September 2022: Our paper “Construction Worker Ergonomic Assessment via LSTM-Based Multi-Task Learning Framework” has been accepted to CRC’22.

July 2022: Attended DAC’22 Young Fellow Program.

March 2022: Received the Graduate School Professional Development Travel Award.

January 2022: Our paper “An Intermittent OTA Approach to Update the DL Weights on Energy Harvesting Devices” has been accepted to ISQED’22.

November 2021: Attended DAC’21 Young Fellow Program.

June 2021: Our paper “Memory-aware Efficient Deep Learning Mechanism for IoT Devices” has been accepted to ASAP’21.

December 2020: Successfully passed the Ph.D. qualifying exam in the Department of Computer Science at UTSA.