Kh. Sadman Rahman

I am a final-year Electrical and Electronic Engineering (EEE) student at the University of Dhaka with a strong interest in semiconductor technology, electronic devices, VLSI, memory systems, and emerging computing architectures. My research interests lie at the intersection of device engineering, advanced materials, computer architecture, and AI-enabled hardware. As part of my 4th year research project, I am working on magnetic nanomaterial-based microplastic extraction, developing magnetically driven nanoparticle systems for selective recovery from aqueous environments, alongside AI-based microplastic detection using deep learning and computer vision techniques. This work has strengthened my experience in nanomaterial synthesis, electromagnetic systems, experimental research, and machine learning. 

I am particularly interested in next-generation memory technologies and hardware acceleration for AI, with a focus on connecting device-level innovation with efficient computing systems. I aspire to pursue advanced research in semiconductor devices, memory, and intelligent hardware architectures.

My future research interests are centered on next-generation semiconductor devices, memory technologies, computer architecture, and AI accelerated hardware. I am particularly interested in emerging memory technologies and device architectures for overcoming the limitations of conventional memory systems, including the growing memory bandwidth, latency, energy efficiency, and data movement challenges of modern computing. My interests include non-volatile and emerging memories, memory centric and in memory computing, device circuit co-design, and the exploration of novel electronic devices for future computing platforms.

I am also interested in AI hardware acceleration and computer architecture, particularly energy efficient architectures for machine-learning workloads, heterogeneous and domain specific accelerators, near/in memory computing, hardware software co-design, and efficient dataflow architectures. Ultimately, I aim to explore how advances in semiconductor devices and emerging memory technologies can be translated into scalable computing architectures capable of supporting increasingly data-intensive and AI-driven applications.

My current undergraduate research focuses on the development of a magnetic nanomaterial assisted platform for selective microplastic recovery and AI enabled detection in aqueous environments. The work explores the synthesis and functionalization of magnetic nanoparticles, including Fe₃O₄ based nanomaterials, to enable efficient interaction with and magnetic separation of microplastic particles. A custom electromagnetic extraction system is being developed to generate controlled magnetic field gradients and facilitate the targeted recovery of nanoparticle microplastic complexes from water. The research further investigates surface functionalization and selective coating strategies to enhance the interaction between magnetic nanomaterials and different polymer classes, including polyethylene, polypropylene, polystyrene, nylon, and ABS. In parallel, I am developing a rapid image based detection framework using deep learning based object detection, particularly YOLO architectures, for automated identification, localization, and quantification of microplastics from microscopy images. The overall objective is to integrate nanomaterials, electromagnetic manipulation, environmental sensing, and artificial intelligence into a unified, efficient microplastic recovery and detection platform.