I'm Rouhan Noor, a Ph.D. student and Graduate Fellow in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison, Madison, WI, USA. My research focused on Neuromorphic Computing, retina-inspired camera chip development, and in-pixel computing. As part of my research project, I am developing novel brain-inspired architecture to mimic the brain functions in silicon, collaborating with neuroscientists. Previously, I was a Ph.D. student at the University of Florida, Gainesville, FL, and was appointed as a Graduate Research Assistant under the Florida Institute for Cyber Security Research (FICS Research), where my research topic was Hardware Security Assurance, microchips, Nano-scale security, and physical attacks on microchips and advanced packaging. I completed my B.Sc. in Electrical and Electronics Engineering (EEE) from Ahsanullah University of Science and Technology (AUST) in January 2020.

Previously, I worked in VLSI and the semiconductor design industry as a Design Engineer in the Analog Circuit Design and Automation department at Neural Semiconductor Limited, a concern of DBL Group, one of the leading semiconductor design farms in Bangladesh.  I completed 10 tape-outs in the 12nm FinFET, 22nm, 28nm, and 45nm Silicon on Insulator (SOI) process. I automated schematic, analog layout generation, conversion, post-layout extraction flow, post and pre-layout simulation, and testbench generation with Cadence SKILL Script, Python, and TCL/Tk. I am experienced in analog layout in 12nm, 22nm, 28nm, 45nm, and 90nm technology nodes. I design analog IPs like two-stage Op-Amp, differential Op-Amp, Driver Circuit, and Band Gap Reference (BGR) in the 22nm SOI process.

Before joining the University of Florida, I collaborated on a research project related to hardware security with Asst. Prof. Tamzidul Hoque, University of Kansas and the project was Hardware Trojan detection and tolerance techniques without the golden chips. I participated in IEEE Signal Processing Cup 2020 and achieved 8th position in the world ranking. The competition topic was "Unsupervised abnormality detection using intelligent and heterogeneous autonomous systems." I further researched and improved the competition problem solution, and the joint lead-authored paper was accepted in the 19th IEEE ICMLA. My bachelor's thesis focused on pattern detection with Spiking Neural Networks and Neuromorphic Computing with Spike LAYer Error Reassignment (SLAYER) framework. 

My research interest includes:

Neuromorphic Computing, Spiking Neural Network, Hardware Security Assurance