Our Team

Members

The researchers behind BrainSeek Lab's work on MicroArchitecure Security, RISC-V SoC, design deep learning, neuromorphic computing, and efficient AI systems.

Faculty
PI
GS
Gopalakrishnan Srinivasan
Principal Investigator
Assistant Professor and Narayanan Family Foundation Fellow,
Department of CSE, IIT Madras.
Research interests span adversarial robustness, model compression, spiking neural networks, neuromorphic hardware, Deep Learning and efficient language models.
Email Scholar LinkedIn

Students
AB
Ayush
PhD Student
Biologically informed SNN models, drawing on computational neuroscience principles to guide neuromorphic network design.
SNN · Bio-Inspired Scholar LinkedIn
GP
Girinath P
MS Student, co-advised with prof. Kamakoti
Works on efficient and secure microarchitecture for general-purpose and machine learning workloads.
Secure microarchitecture LinkedIn
GP
Varun Parsai
MS Student, co-advised with prof. Kamakoti
Building a RISC-V based vector co-processor for machine learning applications with native support for mixed-precision vision models.
Computer Architecture
RR
Rajshekhar Rakshit
MS Student
Works on model quantization and SNN optimization.
Quantization · SNN Scholar LinkedIn
D
Dinakaran
part-time MS Student
Works on microarchitectural optimizations on the Shakti C-class CPU for machine learning applications. Currently working at Mindgrove Technologies.
Microarchitectural Optimization LinkedIn
RK
Rakshitha Kalkura
MS Student
Works on robustness and adversarial attacks in SNNs, along with SNN optimization.
Robstness SNN Scholar LinkedIn
NM
Nupur Mishra
MS Student
Works on regularization of SNNs.
Regularization SNN Scholar LinkedIn
AP
Aman Pandey
MS Student
Works on ML-based enhancements for CPU microarchitecture for higher performance and energy-efficiency.
ML based system enhancement
SB
Saptajit Banerjee
MS Student, co-advised with Prof. Gandham Phanikumar
Autonomous vehicle navigation Scholar LinkedIn
RS
Rahul Kumar Singh (2025)
MTech Student
Scholar LinkedIn
SV
Sankar Vinayak (2024)
MTech Student | Graduated
Towards Practical Equilibrium Propagation: Robustness, Regularization, and Sequence Learning
Energy Models Scholar LinkedIn
RK
Ramkumar (2024)
MTech Student | Graduated
Spike-Sparse TET: Towards Energy-Efficient Direct Training of Spiking Neural Networks
Spike Sparsity Scholar LinkedIn
PS
Priyanshu Sharma (2024)
MTech Student | Graduated
Stable and Efficient ANN-to-SNN Conversion via Threshold Correction and Composite Temporal Fine-tuning
TET LinkedIn
A
Atyam Lakshmi Nikhitha (2024)
MTech Student | Graduated
Design and Analysis of Reuse Cache for ML Workloads
TET
SS
Subramanian Segaran (2023)
MTech Student | Graduated
Optimization of Neural Networks using Weight Sharing Techniques
Optimization of NN LinkedIn
PK
Pratik Vinod Kadlak (2023)
MTech Student | Graduated
Optimizing Deep Neural Networks for Edge Deployment
ML on Edge LinkedIn
AB
Arun R Bhat (2023)
MTech Student | Graduated
Mixed Precision Quantization of Neural Networks
Quantization+
DB
Devgokul B V
Project Associate
Researching neuromorphic hardware design and architecture for efficient spiking neural network acceleration.
Neuromorphic Hardware Scholar LinkedIn
PD
Preethi Carmel Bosco
Project Associate
Works on LLMs
LLM Architecture LinkedIn
NM
Noel Manuel (2026)
Dual Degree
Torch2Gemmini: End-to-End Deployment of PyTorch Models on FPGA-Based Gemmini Accelerator
EP22B035 LinkedIn
VM
Varun M (2022)
Btech EE
NeuroFlex: Lossless Element-Level ANN–SNN Co-Execution for Efficient Sparse Inference
Neuromorphic Computing LinkedIn
HN
Hiran N (2021)
Btech Mechanical
Towards Stable and Scalable Event-Driven Training of Spiking Neural Networks
SNN LinkedIn
AS
Adithya Satyarthi (2022)
Btech Eng. Physics
Hardware-Algorithm Co-design for Ternary JEPA Models
Hardware
AR
Akaash R (2022)
Btech EE
Design of Dual Sparse SNN Accelerator for ML Workloads
Neuromorphic Computing
SR
Sreeram Radhakrishnan
Btech EE
Works neuromorphic hardware design and architecture for efficient spiking neural network acceleration.
EE23B075 Neuromorphic Hardware LinkedIn
PR
Pranav Ramesh
Btech CSE
Worked on SNN optimization and ANN-SNN conversion
ANN-SNN Conversion Scholar LinkedIn
SR
Shivanshu Kumar (2026)
UGRC
Understanding information flow in Decoder Only Transformers for Language Generation
ShishuLM: Efficient Language Modeling with Low Attention Transformers
CS23B058 Scholar LinkedIn
MB
Medapuram Lakshminarasimha Madhav Bhardwaj (2026)
UGRC
Exploration of SNNs for Transformers
CS23B035
AI
Abhinav I S (2026)
UGRC
Shared Last-Level Cache for Shakti C-Class Processor: Control Flow, Miss Handling, and Verification
EE23B002
SS
Sanjeev Subrahmaniyan S B (2026)
UGRC
Shared Last-Level Cache for Shakti C-Class Processor: Control Flow, Miss Handling, and Verification
EE23B102
ST
Sriprakash T (2026)
UGRC
Rethinking Attention in Graph Learning: Graph Neural Networks vs. Graph Transformers
MM23B066
RK
Rakshitha Kalkura (2025)
UGRC
Gradient-based Bit-Flip Attack for Effective Fault Injection in Spiking Neural Networks (SNNs)
CS25E052 LinkedIn
SB
Sanket Pramod Bhure (2025)
UGRC
SIPHER: Spike based Neuromorphic Computing for Secure Inference against Bit-Flip Attack
AE20B108 LinkedIn
AS
Aditya S (2025)
UGRC
An Investigation of Bit Flip Attacks on Binary Neural Networks
CS22B096
NR
Nishok RP (2025)
UGRC
OGE Attack in Binary Neural Networks, Transformers Using Spiking Neural Networks
CS22B035
SS
Shreyas S (2025)
UGRC
Modeling the Memory Subsystem of Hybrid ANN-SNN Accelerators
EP22B040
MB
Medapuram Lakshminarasimha Madhav Bhardwaj (2023)
BTech CSE
Exploration of SNNs for Transformers
SNN based Transformers
SN
Sanat Passan B (2022)
Btech EE
Design and Implementation of Branch Predictors for the Shakti C-Class Processor
Architecture
AP
Agara Mudhalvan G P (2022)
Btech EE
Design of Dual Sparse SNN Accelerator for ML Workloads
Neuromorphic Computing
AG
Aksshith G (2022)
Btech EE
Design of Dual Sparse SNN Accelerator for ML Workloads
Neuromorphic Computing
SS
Shreyas S (2022)
Btech Eng. Physics
Modeling the Memory Subsystem of Hybrid ANN-SNN Accelerators
Hardware
GR
Gokulakrishnan R (2021)
Btech CSE
Efficient Open-source RISC-V Trace Generation for Enabling Reuse in Computer Architecture Research
RISC-V Computer Architecture
NA
Niveath A (2021)
Btech CSE
Reuse Cache and Applications in ML Workloads
ML system
GT
Ganesh T (2021)
Btech CSE
Towards Practical SNN Prefetchers: A Lightweight Approach to Pathfinder
ML system
GB
Gurugubelli Aditya Bharadwaj (2021)
Btech CSE
The V-Way Cache
Computer Architecture
GB
Logesh K T (2021)
Btech CSE
Fiber Cache Simulator
Computer Architecture
SN
Sai Kiran Narayanaswami
Independent Study
QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities
SS
Shriram S
Independent Study
HoloFNO: A Physics-Supervised Fourier Neural Operator for Real-Time Holographic Atom Trap Generation with Mechanistic Diagnostics and Sinusoidal Bypass
ED24B030
AL
Adithya L
Independent Study
HoloFNO: A Physics-Supervised Fourier Neural Operator for Real-Time Holographic Atom Trap Generation with Mechanistic Diagnostics and Sinusoidal Bypass
ED24B039
AS
Aksith Singh
Intern, SNU
Representation Drift in Spiking Neural Networks
AS
Ananth Shyam
Intern, SNU
QUARK: Quantization and Adversarially Robust Knowledge Distillation for Mixed-Precision Convolutional Neural Network Architectures
VP
Vineeth Roshan Premanand
Intern, SSN
SparseIMC: Sparsity-Aware In-Memory Computing for Energy-Efficient Neural Network Acceleration
SSN
SR
Sreeram Ramesh
Intern, SSN
SparseIMC: Sparsity-Aware In-Memory Computing for Energy-Efficient Neural Network Acceleration
SSN
GS
Gayathri Subramanian
MS Student, co-advised with Prof. Kamakoti
Secure Memory Disambiguation: Mitigating Performance-Induced Security Vulnerabilities.
uArch - Hardware Security Scholar LinkedIn Thesis Link