MASc Candidate, Electrical & Computer Engineering, University of Waterloo
Hello There!
I'm a 2nd-year master's student affiliated with the CL2 Lab, working on generative models (diffusion) for generalizable path planning. I am currently advised by Prof. Yash Pant.
Previously, I was a MITACS GRI at the University of Toronto, where I worked on novel view generation and animation of human models (NeRFs + diffusion) under the guidance of Prof. Igor Gilitschenski. I completed my Bachelor’s in Mechanical Engineering at TCE, focusing on fast, depth-aware grasping for transparent objects under the guidance of Prof. Saravana Perumaal.
Kinematic aware, animatable, and class-agnostic 3D deformable objects from casual monocular videos without the use of any priors or camera poses - A Template-Free Approach
Competitions and Projects
*Below are some of the projects I had fun working on, click the title for details.
Motion prediction with rasterized images using CNN and LSTM encoder-decoder models. Also exploring Kalman filters and other optimization techniques to enhance non-learning-based approaches. Currently working on Vectornet for a faster, raster-free pipeline.
Detection of helmets, player classification, tracking using Kalman and DeepSORT for accurate mapping. Implemented predictive tracking and analysis of game trends using past data.
Annotate and classify catheter positions with a robust approach that accurately identifies endpoints, despite their footprint being less than 1% of the overall image.
• Enhanced GNSS positioning and navigation accuracy on smartphones.
• Processed and cleaned GNSS logs to compute precise location, achieving a 94th position out of 810.
• Implemented Kalman smoothing and velocity-based models for improved GNSS data accuracy.
• Designed a slider-crank actuation mechanism to automate compression in BVM ventilators.
• Conducted pressure trajectory analysis using COMSOL multiphysics to achieve required PIP and PEEP values at the outlet.
• Fabricated and characterized a device utilizing MOF as advanced moisture sorbents for energy-efficient high-temperature cooling.
• Conducted XRD and Thermogravimetric Analysis to assess MOF structure and water uptake characteristics.
More Projects
G2Net Gravitational Wave Detection - European Gravitational Observatory: Find gravitational wave signals from binary black hole collisions Used FFT and 1D CNN to detect the gravitational waves.
Placed 33/1219 teams
March Machine Learning Mania 2022 - Men’s: Predict the 2022 College Men's Basketball Tournament (kaggle competition), also here is the visulalization tool for bracket builing
NCAA_BracketBuilder Placed 14/930 participants
Crypto- Market prediction based on anonymised features (Ubiquant Market Prediction) I
Used Tabnet based model.
Placed 99/2893 participants
TEAM YUKTA RACING - Autobots Assemble! We Build, We Race.....! Defending Champions of GKDC 2020
