Brojogopal Sapui
Scientist @Namlab
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WORK HISTORY
Scientist @Namlab
Dresden, DE
Working on reconfigurable FET (rFET) devices in 22nm FDSOI technology, focusing on hardware security for edge-AI accelerators, including side-channel analysis, fault injection, and reverse engineering.Leading device-to-circuit-level security co-design, secure matrix-vector multiplication primitives, and the silicon tape-out of security-aware test structures, followed by wafer-level characterization in collaboration with other industry partners.
EDUCATION
Indian Institute of Technology, Kharagpur
Research Fellow, Computer Engineering
International Institute of Information Technology Bangalore
Post graduation Diploma, Data Science and Machine Learning
Karlsruhe Institute of Technology (KIT)
Doctor of Philosophy - PhD, Computer Science
Durgapur Institute of Advanced Technology & Management
B,Tech, Electrical, Electronics and Communications Engineering
ABOUT BROJOGOPAL SAPUI
I am working in NamLab gGmbH as a scientist on reconfigurable FET (rFET) nano-devices in 22nm FDSOI technology, focusing on hardware security-specific (side channel, fault injection, reverse engineering) applications for edge-AI accelerators, secure matrix-vector multiplication, and silicon tape-out of security-aware test structures. I completed my PhD from KIT, Germany. My research topic was to analyze vulnerabilities in Analog emerging non-volatile memory technologies-based and digital edge-AI accelerators. Mostly my work is on leakage/fault model creation, simulation (SPICE)/emulation in FPGAs, verification (SystemVerilog + UVM) and validation for side channel analysis attacks, micro-architectural attacks and fault injection attacks with various EDA tools (Vivado/Vitis, Synopsys and Cadence design flow). Previously, I was working in Wipro(R&D) as an embedded security developer in Automotive (client - General Motors) network design (with C++). Before that, a total of 3.5 years of research experience in Hardware Security, classical cryptography, and Quantum Cryptographic primitives with Machine Learning based security analysis from IIT Kharagpur and ISI Kolkata, India.
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