top of page

Resume

Experience

May 2022 - May 2023

Machine Learning Research Assistant

Cyberinfrastructure for Network Science Center at Indiana University

Indiana, Bloomington

Created a Kidney Blood Vessel Image Segmentation pipeline as a part of the Human Bio-molecular Atlas Program, focused on Kidney, Colon, Lung, Spleen, Prostrate and Heart. Conducted thorough research on latest papers for image segmentation on various human body organ cells. Hosted Kaggle Competitions in the computer vision domain to boost R&D in machine learning for Biomedical Image Analysis. Trained Large Deep Learning Models on a High Performance GPU Cluster hosted on the CNS Linux server [Quadro RTX 5000].

Oct 2021 - June 2022

NLP Research Assistant

Indiana University Cognitive Laboratory

Indiana, Bloomington

Worked on BERT and GloVe word embeddings on PyTorch to find similar word pairs using cosine similarity.Created a web scrapper to extract 1000 sentences per vocabulary word from Wikipedia.Performed Model Inferences on High Performance GPU cluster[Nvidia Tesla V100] hosted on the Indiana University linux server for fast data processing.

May 2020 - July 2021

Computer Vision Intern

Indian Space Research Organization

Vellore, India

Speckle noise removal in RISAT-1 SAR satellite images using wavelet transform and POAC techniques implemented via PyTorch, GDAL and SNAP sentinel software.

Achieved significant speckle suppression (PSNR of 44 and SSIM of 0.97) compared to conventional filters for speckle noise removal. A GUI software created for an interactive satellite image processing tool.

May 2020 - July 2020

Machine Learning Intern

Wikilimo

Remote

Prediction of pests and diseases in cotton and rice crops based on 8 weather features like rainfall, temp, sunlight, water vapor etc. using Long-Short Term Memory(LSTM) based Deep Learning Models. Analyzed crop pest data across 10 regions of India to draw insights into pest infestation patterns. Optimized Deep Learning Models to run for mobile platforms. Achieved over 90% accuracy after quantization of Deep Learning models.

June 2019 - July 2019

Summer Academic Intern

National University of Singapore

Singapore

Project 1 (NUS) - Tyre Defect Detection using CNN: Created a web-app using Flask to classify tire defects using Convolutional Neural Networks (CNNs) on a custom dataset of 500 images created from Google images. Achieved an accuracy of 82% on the test set.

Project 2 (HP)- Stock Market Analysis using Hadoop and Kafka Cluster: Created a Hadoop based stock market price predictor to help investors take an informed decision. Used APIs to fetch real time stock market data to create an analysis report on Starbucks vs Microsoft stock price trend. Won Scholarship from National University of Singapore for outstanding performance in GAIP during the internship program.

Education

2017 - 2021

Vellore Institute of Technology

B.Tech in Computer Science

Vellore, India

Courses: Machine Learning, Artificial Intelligence ,Statistics, Calculus, Linear Algebra, Programming.

 

Won Special Achiever's Award for representing the institute at an International Conference.

2021 - 2023

Indiana University Bloomington

Master's in Data Science

Bloomington, Indiana, USA

Courses: Deep Learning Systems, Elements of Artificial Intelligence, Introductions to Statistics, Computer Vision, Usable AI, Machine Learning for Signal Processing, Exploratory Data Analysis, Management Access of Big Data, Autonomous Robotics

Professional skillset

Python (NumPy, Pandas, Matplotlib, Scikit, Flask)

Deep Learning (PyTorch, TensorFlow)

Machine Learning

Time Series Analysis

Data Modelling and Optimization

Database Management(SQL, NoSQL, MongoDB)

Front End Web Development (HTML, CSS, JS, Django)

Remote Sensing and Computer Vision

Natural Language Processing

Model Deployment and MLOps (AWS, GCP, PySpark, Kubeflow)

Git and GitHub

Leadership

Languages

English (native)

Hindi (proficient)

Marathi (proficient)

Follow

  • LinkedIn
  • GitHub-Mark
  • Circled_Medium_svg5-512
bottom of page