Hey there! 
I’m Rugved, a passionate Computer Engineering and Deep Learning enthusiast currently pursuing my Masters at New York University (NYU) set to graduate in May 2025.
With a robust background of over two years in DevOps at Oracle and a Bachelor’s degree in Electronics Engineering from the University of Mumbai, my journey in technology has been dynamic and invigorating.
I’m excited to share my experiences, insights, and explorations here!
I’m Currently Studying…
- High Performance Machine Learning
- Advanced Topics In Computer Vision
- Real-time Embedded Systems
I have previously taught…
Here are a few things I have worked on…
-
Multimodal Sentiment Analysis - This project explores different methodologies, focusing on fusion techniques that integrate information from three modalities (audio, language, vision) to enhance sentiment analysis performance, and the various architectures that employ them. [Read More]
-
Continual Learning for Autonomous Vehicles - Applying the continual learning framework to Autonomous Vehicle setting: predicting steering angles based on the captured images. Experimented with various approaches - Elastic Weight Consolidation, Experience Replay and Temporal Consistency Regularization. [Read more]
-
Vector Processor Simulator - A Python-based Vector Processor (VMIPS) functional and performance simulator evaluated on dot product, fully connected layer, and convolutional layer test bench. [Read more]
-
ResNets - Explored ResNet Models trained to classify images on CIFAR-10 dataset. Finetuned hyperparameters, experimented with ResNet depths and strategies like dropout layers and learning rate schedulers acheiving a test accuracy of 95.37%. [Read more]
-
Semantic Image Segmentation for Autonomous Vehicles - This project utilizes semantic image segmentation to enhance autonomous vehicle perception, accurately identifying and segmenting critical elements like drivable surfaces. By leveraging a U-Net model trained on the CARLA dataset, the project achieves an impressive 96% accuracy [Read more]
