Timeline

• Jan 2022
• Sr. Data Engineer @ Core Digital Media
• May 2021
• Sr. Software Engineer @ Leaf Group
• Aug 2018
• Data Engineer @ Leaf Group
• May 2018
• Master of Science in Computer Science

  CGPA: 3.55

• Spring Semester, 2018

  GPA: 4.0

  -Deep Learning Systems

• April 2018
• Large-Scale Landmark Recognition using Deep Learning

  -Recognized landmarks belonging to about 15,000 classes from the largest worldwide landmarks dataset (multi-TB) with Deep CNNs and Siamese Networks using Python, TensorFlow and NVIDIA Tesla V100.

  -Fine-tuned AlexNet and Inception v3 architectures with transfer learning using pre-trained ImageNet weights and achieved an accuracy of 96.88% for top 100 classes.

• Speech Denoising

  Implemented a speech denoiser using LSTMs and compared their performance with shallow neural networks.

• February 2018
• Winner @ HackIllinois 2018 Devpost

  Won the Social Good Prize for "Hacking socio-technical challenges in our community" presented by US Ignite as part of the Reverse Pitch challenge.

• December 2017
• Fall Semester, 2017

  GPA: 3.5

  -Advanced OS

  -Advanced NLP

  -Exploratory Data Analysis

• Ubiquitous Sensing: Towards the Future of IoT Operating Systems

  Presented an analysis on the requirements of an OS for IoT devices along with a comparitive study on some of the current IoT OSs.

• November 2017
• Augmenting Alexa'a capabilities using NLTK Wrapper and Clause Detection @ Linguist List, Indiana University

  Built an NLTK wrapper along with WordNet’s word sense disambiguation and CoreNLP’s dependency parser to extract key linguistic features from text into a unified data object for knowledge representation in a graph database.

• Boosting Betting Odds on Soccer Matches

  -Performed exploratory data analysis on Premier League data using R and ggplot to visualize relevant features, identify correlation between team attributes and increase quality of the feature space for match outcome prediction, thereby maximizing odds of winning bets.

  -Attained an accuracy 6.95% higher than bookies who take bets using a Proportional Odds Logistic Regression model.

• May 2017
• Spring Semester, 2017

  GPA: 3.43

  -Algorithm Design and Analysis

  -Machine Learning

  -Social Media Mining

• December 2017
• Fall Semester 2016

  GPA: 3.67

  -Elements of AI

  -Advanced Database Concepts

  -Music Information Processing: Audio

• Monophonic Musical Instrument Identification

  -Employed multinomial logistic regression to classify monophonic audio samples of instruments into one of 3 instrument families using R and the libraries tuneR, caret, nnet and obtained an accuracy of 77% after stratified 10-fold cross-validation.

• November 2016
• SAT Solver

  Wrote a SAT solver for propositional logic in Python that checks if a given CNF statement is satisfiable or not using the Davis–Putnam–Logemann–Loveland (DPLL) algorithm.

• September 2016
• Connect Four

  -Built an adversarial search AI in Python to play Connect 4 using negamax search and alpha-beta pruning.

  -Optimized search time using iterative deepening so that the player doesn't take more than 3 seconds to make a move.

• May 2016
• Bachelor of Engineering in Computer Engineering

  Graduated with Distinction

• Diabetic Retinopathy Detection using Deep Convolutional Nerual Networks @ CUDA Teaching Center, Sardar Patel Institute of Technology

  -Designed a model consisting of GPU accelerated CNNs which classifies high resolution retinal images into one of the 5 stages of Diabetic Retinopathy and an ensemble of 3 models resulted in a quadratic weighted kappa of 0.3996 on green channel images.

  -Programmed the model using Python, Theano and Lasagne with the help of NVIDIA GeForce GTX 780 GPU .

• October 2014
• Virtual Stock Exchange

  Developed an online virtual stock exchange and portfolio management website using ASP.NET and Microsoft SQL Server that allows users who have registered on the website to buy and sell stocks.