PRAIRIE VIEW, Texas (December 10, 2024) – Mafizur Rahman, a computer science graduate student at Prairie View A&M University, is making strides in advancing artificial intelligence research through his study of analog accelerators for deep learning. Under the guidance of faculty mentors Dr. Lijun Qian and Dr. Lin Li, through the Faculty Research and Innovation for Scholarly Excellence (RISE) Program, Rahman explores the performance of deep neural networks using hardware simulators such as AIHWKIT, CrossSim, and MemTorch to optimize AI for real-world applications.
“Seeing my research accepted at a reputable conference and its potential to shape hardware-based AI has been incredibly rewarding,” Rahman said.
After graduation, Rahman plans to pursue a Ph.D. in electrical engineering at PVAMU while continuing his work on energy-efficient AI hardware at the university’s CREDIT Center. His master’s research demonstrated the resilience of AI models like ResNet50 in analog environments, opening new possibilities for advancements in IoT and wearable technology.
In addition to his academic achievements, Rahman’s collaboration with Sandia National Laboratories has enhanced his expertise in analog simulations. His work reflects PVAMU’s commitment to innovation in science and technology.
By Crysta Mendes