I am Md Asiful Hoque Prodhan, currently pursuing my Ph.D. in Computer Science at The University of Texas at San Antonio (UTSA). I also serve as a Graduate Teaching Assistant and work under the supervision of Dr. Sushil Prasad. My research focuses on enabling energy-efficient and low-latency machine learning.

With the rapid growth of machine learning applications on edge devices, optimizing energy efficiency has become increasingly critical. My research addresses this challenge by focusing on Spiking Neural Networks (SNNs) — a biologically inspired paradigm that mimics how neurons in the brain communicate through discrete spikes. Unlike traditional Deep Neural Networks (DNNs), which are computationally intensive and require substantial power and memory, SNNs enable event-driven computation and real-time processing, making them well-suited for deployment in resource-constrained environments such as embedded systems, IoT devices, and smartphones.

My work explores indirect learning strategies, where an Artificial Neural Network (ANN) is first trained using conventional methods and then converted into an SNN. This approach leverages the strengths of both paradigms: the robust training techniques and high performance of ANNs, and the energy-efficient, event-driven processing of SNNs. By focusing on effective ANN-to-SNN conversion, my research aims to retain the accuracy benefits of ANN pre-training while achieving the computational efficiency necessary for deployment in real-world, energy-constrained scenarios.

I bring experience from both academia and industry. Before joining UTSA, I served as Assistant Director (ICT) at Bangladesh Bank (the central bank of Bangladesh) and as Assistant Engineer (IT) at Sonali Bank PLC (the largest commercial bank in Bangladesh), where I supported national-scale platforms and IT policy compliance. I also taught as a Lecturer at Daffodil International University.

I earned my B.Sc. in Computer Science and Engineering (CSE) from Ahsanullah University of Science and Technology (AUST), Dhaka, Bangladesh, in 2018.

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