I am a Masters student in the Department of
Computer Science at University of Southern
California with Honors. (Expected Graduation Date: December
At USC, I have been working in Information Sciences
as a research assistant where my work is centered around language models and various aspects of knowledge graphs.
At the same time, I have been a Teaching Assistant for CSCI 561 and CSCI 570.
Recently, I was as a Machine Learning Engineer Intern at Bill.com where I worked on Optical Character Recognition for amount detection from invoices and statements. I have previously worked as a Software Developer at Barclays Global Service Centre, India where I had worked on a wide variety of tech stacks including Natural Language Processing and Web Development.
I had completed my Bachelors with Rank 1 from K. J. Somaiya College of Engineering, Mumbai majoring in Computer Engineering. My final year project - Sign Language Translation was aimed at recognizing the signs and gestures demonstrated by the hearing- and speech-impaired and translate into voice. Apart from my academic endeavours, I play the Guitar and Harmonium. You can find my Resume here and papers or reports for all the above work in the publications section.
MS in Computer Science, Dec 2022
University of Southern California
BTech in Computer Engineering, 2018
K. J. Somaiya College of Engineering, Mumbai
For a complete list, kindly see my CV
CNN was trained for detecting Pneumonia given Chest X-Rays. After training the model, test accuracy of 94.56% and a recall score of 0.97 was achieved.
An Android application designed to translate the signs and gestures performed by the hearing- and speech-impaired into voice using Image Processing, Segmentation and Machine Learning algorithms KNN and HMMs. Paper published in IEEE.
Contributed to the development of Machine Learning Lab on behalf of K J Somaiya College of Engineering, Mumbai and hosted on IIT Bombay's Virtual Labs website. As part of this, I developed simulations of neural networks, optical character recognition using Tesseract JS, Hebbian, Perceptron Learning Rules.
Working on designing bots capable of understanding communication and strategizing for the board game – diplomacy under the supervision of Dr. Jon May
Increased the win rates by an average of 5% for the powers in the game by generating and understanding DAIDE messages and using rules on top of the pre-trained reinforcement learning based Dipnet bot
Generated a dataset of 1 million invoices and statements from user data after sanity checks for improving the amount OCR model
Leveraged an ensemble of document classification models to fix the imbalanced data distribution of statements in training dataset
Improved the amount prediction test accuracy from 75.5 to 77.6% with 50% confidence threshold
Constructed a framework for identifying low quality statements in Wikidata knowledge graph amongst 1.1 billion statements on the basis of deleted, deprecated statements and constraint violations
Enhanced the graph embeddings of nodes using retrofitting based on BERT embeddings and structural, textual properties extracted from Wikidata, Probase and DBPedia datasets increasing Spearman correlation from 0.66 to 0.73 on WordSim353 benchmark
Devised a prototype fraud detection pipeline using Kafka queues, Cassandra DB and PySpark servers having an ensemble of ML models
Designed a real-time tweets sentiment analysis engine to enable quick customer service response achieving an accuracy of around 90 % in pilot runs
Created a classifier application utilizing ML algorithm LDA to extract insights from iOS and Android application reviews and customer complaints
Deployed a system that helps in connecting the colleagues with available bandwidth and skillsets with the colleagues needing assistance in their work, using AngularJS, Java, MySQL, saving more than 900 man-hours annually
Implemented dashboards for automated generation of real-time delivery metrics of more than 30 teams from Agile Central and Jira data sources which have been saving around 150 man-hours annually. Bagged the Barclays Award of Stewardship for this initiative
Led a team of three to develop a Virtual Lab for the online demonstration of machine learning concepts such as neural networks, learning rules and optical character recognition
This lab has won the Global Online Laboratory Consortium International Lab Award
Courses Included: 1) Neural Networks and Deep Learning, 2) Improving Deep Neural Networks:
Hyperparameter tuning, Regularization and Optimization
3) Structuring Machine Learning Projects, 4) Convolutional Neural Networks, 5) Sequence
Please feel free to reach out to me for any query