Highly analytical and results-driven Dual Degree student specializing in Electronics and Electrical Communication Engineering, with a robust foundation in Deep Learning, Computer Vision, and Robotics. Proven ability to innovate and deliver high-impact solutions, demonstrated by a publication accepted at IEEE ICDCS 2025 and significant contributions to projects in autonomous driving and federated learning. Seeking to apply advanced research capabilities and technical expertise to develop cutting-edge AI/ML systems and drive technological advancements in dynamic environments.
Research Intern
Bangalore, Karnataka, India
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Summary
Led the deployment and evaluation of advanced diffusion policies for robotic arm control, significantly improving accuracy and action diversity.
Highlights
Deployed diffusion policies utilizing FiLM-ResNet and temporal U-Net for real-time 1 kHz control of a robotic arm, achieving 92.14% test-time accuracy.
Collected and structured over 130 RGB-D frames and action trajectories into ReplayBuffers, enabling robust training and evaluation of robotic control models.
Improved action diversity by 35% over IBC and BET baselines using multi-modal sampling with Diffusion Policy, enhancing robotic arm adaptability.
Modified the evaluation script from an RTDE-based interface to the ROS2 Framework, resulting in 92% test-accuracy for the Franka arm and streamlining research workflows.
Mentor
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Summary
Mentored first-year students, providing academic and professional guidance within the ECE department's welfare program.
Highlights
Mentored 4 first-year students from the ECE department, providing academic guidance and fostering professional development within the Students Welfare Program.
Junior Secretary
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Summary
Served as Junior Secretary, contributing to departmental operations and student engagement initiatives.
Highlights
Managed administrative tasks and supported departmental events, enhancing operational efficiency and student engagement within the ECE department.
Vision and Controls Team Member
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Summary
Contributes to cutting-edge research in autonomous ground vehicles, leading to significant publications and simulations.
Highlights
Collaborated with lead researchers on Vertical Federated Learning, contributing to a publication accepted at IEEE ICDCS.
Participated in CDC 2025, implementing Pure Pursuit and Stanley controllers for autonomous F1Tenth car simulation, demonstrating advanced control system expertise.
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Dual Degree (BTech and MTech)
Electronics and Electrical Communication Engineering
Grade: 8.13/10 CGPA
Courses
Advanced Calculus
Probability and Statistics
Linear Algebra
Optimization Models
Signals and Systems
Numerical and Complex Analysis
Programming and Data Structures
Digital Signal Processing
Control Systems
Machine Learning specialization (Coursera)
CS-182 Deep Learning (UC Berkeley)
Summer Analytics (IIT Guhwathi)
Published by
HotDiML @ IEEE ICDCS 2025
Summary
Co-authored a research paper accepted at HotDiML @ IEEE ICDCS 2025, Glasgow, UK, focusing on novel methods for enhanced regression in Vertical Federated Learning.
Python, C/C++, Arduino, Verilog, MATLAB, LaTeX.
NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, PyTorch, TensorFlow, OpenCV, ROS1/ROS2.
Google Colab, Kaggle, Docker, Git, PyCharm, VSCode, Proteus, Xilinx, Vivado, LTSpice.
Deep Learning, Natural Language Processing (NLP), Convolutional Neural Networks (CNN), Computer Vision, Federated Learning, Generative AI (VAE, GAN, Diffusion Models).
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Summary
Developed a geometric path tracking algorithm for small-scale autonomous vehicles, specifically for F1Tenth cars.
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Summary
Implemented Deep Learning models from scratch to reinforce mathematical foundations and gain a deeper understanding of neural network mechanics.