Publications

Robotics & Machine Learning:

Investigated the feasibility of using electroencephalogram (EEG) to achieve binary motor intention classification for robot assistive control in real-time.

Designed a ResNet based CNN architecture for processing the dashboard camera image data to a perception map, hence producing an innovative Perception-based robust control barrier function using a two-layer DNN.

Developed a real time Signed Distance Function generator based of neural radiance fields for construction of online perception based CBFs without prior training using a depth camera for efficient and safe robot navigation.

Soft computing & Energy (Undergrad Research Papers):

Relevant Projects

Developed a multi-robot & multi-target path planning & localization algorithm using deep q learning combined with Graph Neural Network outperforming the Dec-SB and Random Walker algorithm for efficiently solving the Active information acquisition problem.

This project delivers a real-time SDF generator tailored for the FRANKA EMIKA Robot's downstream reactive control tasks. For an in-depth understanding of the challenges, implementation, and results, please visit the project website.

Developed a computer vision-based AI system with YOLO for player and ball detection and a custom CNN for court mapping, delivering real-time analytics to optimize player strategies and identify performance gaps.

Implemented a diffusion-based method using a Markov chain and L1-trained restoration backbone to robustly restore severely degraded facial images with enhanced realism and fidelity, leveraging pretrained models for simplified training.

Developed an end-to-end machine learning pipeline for classifying bone fractures from X-ray images, leveraging MLOps practices with DVC, and deploying solutions on both Azure and AWS. Developed and deployed a Flask-based web interface enabling real-time image upload and fracture detection.

Developed a functional motion planning stack that avoids both static & dynamic obstacles, track the center line of a lane, & handling stop signs. [Behavioral planning logic, static collision checking, path selection, & velocity profile generation] in CARLA simulation.

Developed a Graph Neural Network to learn a distributed policy that mimics the optimal centralized controller considering a multi-agent system with N agents tasked with controlling a dynamical process, while ensuring collision and spread avoidance.

Developed the Pulmonary Embolism Detection model based on CNN (Efficientnet-b0) with a weighted log loss of 0.08 for reducing human delays and errors in detection and treatment of PE from chest CT pulmonary angiography images.

Explored the nexus between movie popularity, factors like runtime, genre, and economic conditions, achieving strong predictive accuracy with Random Forest and XGBoost models, highlighting the potential for genre-specific trends during economic fluctuations.

Developed a forecasting model for predicting COVID-19 cases for 81 countries using DNN and LGBM with an accuracy of 97.6% - 99.8%. Dispelled rumors regarding the weather’s role in COVID-19 transmission; examined and demonstrated that weather had little to no role in the spread of COVID-19.

This project explores the classical computer vision technique (non-deep learning) of converting 2D images into 3D Reconstruction.

This project implements a two-view stereo algorithm to convert multiple 2D view-points into a 3D reconstruction of the scene.

This project provides one of the most simplified implementation of the famous Neural Radiance Fields paper "NeRF Representing Scenes as Neural Radiance Fields for View Synthesis".

To address the challenge of child care during customer service visits, a customer-experience enhancement system is proposed, as a part of ESE 514 : Embedded System final project. The system integrates the dino game, a face-tracking pan-tilt camera, and an LCD and speaker for interactive music engagement. Please refer to our website for all the details.

Education

Additional Education / Online Specialization

• Deep Learning Specialization by deeplearning.ai
• Self-Driving Cars Specialization by University of Toronto
• Machine Learning Engineering for Production (MLOps) Specialization
• Algorithms Specialization by Stanford University
• IBM Data Science Professional Certificate
• Applied Data Science with Python Specialization by University of Michigan
• Business Analytics Specialization by Wharton School of the University of Pennsylvania
• Python for Everybody Specialization by University of Michigan

• Machine Learning by Stanford University
• Google Cloud Business Professional Accreditation by Google Cloud
• Deep Learning Specialization by deeplearning.ai
• Introduction to Programming with MATLAB by Vanderbilt University

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