Anindita Chattopadhyay
@aninditachattopadhya1
I build GNN-based hardware security verification and real-time FPGA intrusion detection systems.
What I'm looking for
At ADE/DRDO, I've built graph neural network pipelines that turn raw Verilog netlists into RTL- and gate-level hardware Trojan detection and localization models. My work has resulted in four peer-reviewed IEEE and Springer publications, including an ICCC 2025 Best Paper award.
I've also designed a deterministic FPGA-based intrusion detection system for ARINC-825 avionics buses, delivering 40 ns latency at 100 MHz on a Xilinx Zynq-7020. The design distinguishes cyberattacks from hardware faults through dual-channel redundancy and was verified across 10 adversarial and fault-injection scenarios with a 100% pass rate.
Before research, I automated enterprise network diagnostics and provisioning at Accenture, reducing provisioning time by 30%. I'm seeking to extend my work in hardware security, side-channel and fault-injection analysis, and trustworthy AI for chip and system verification.
Experience
Work history, roles, and key accomplishments
Research Engineer
Aeronautical Development Establishment (ADE), DRDO
Dec 2022 - Present (3 years 8 months)
Designs and trains Graph Neural Network models for hardware Trojan detection in RTL and gate-level netlists. Built an end-to-end pipeline from raw Verilog to GNN classification and published 4 peer-reviewed papers.
Automated fault diagnostics and reporting for enterprise networks, reducing provisioning time by 30% through toolchain optimization. Managed activation and configuration of enterprise network circuits and performed circuit-level debugging and root cause analysis.
FPGA-Based Intrusion Detection System
Aeronautical Development Establishment (ADE), DRDO
Designed a deterministic real-time hardware detection pipeline in Verilog achieving 40ns latency at 100MHz on Xilinx Zynq-7020 SoC. Engineered a dual-channel redundancy correlator distinguishing cyberattacks from hardware faults with zero misclassification.
Education
Degrees, certifications, and relevant coursework
B.M.S. College of Engineering
Master of Technology, VLSI Design and Embedded Systems
2021 - 2023
Grade: 8.5
Pursued M.Tech in VLSI Design and Embedded Systems with a CGPA of 8.5.
EPCET
Bachelor of Engineering, Electrical and Electronics Engineering
2014 - 2018
Completed Bachelor of Engineering in Electrical and Electronics Engineering.
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