Hi! I am Abhigyan.

I am currently pursuing my masters in Information Science at the University of Pittsburgh. I am interested in data science and distributed systems.

Experience

Telementoring system for open surgeries

Software development intern
SEP 22 – MAY 23

  • Successfully developed and deployed a telelhealth SAAS platform in collaboration with Hamad Medical Corporation, utilizing Azure Kinect SDK, C++ and PostgreSQL.
  • Designed scalable front-end modules to visualize on Oculus using unity, C# and Azure DK cameras.
  • Reduced bandwidth and latency reduction by 30% by implementing ETL pipelines over WebRTC.
  • Performed extensive testing to evaluate data transfer functionality between hospitals situated 2 miles apart.
Qatar Computing Research Institute (QCRI)

Data analytics intern
Qatar, MAY – JUL 22
2nd place, best summer internship project, for a large-scale flood detection pipeline.

Satellite Image Downloader and Flood Detection Pipeline:

  • Overcame GEE’s 30MB download limit by dividing images into smaller tiles, enabling downloads up to 15GB in one call.
  • Achieved up to 20x faster download speeds on clusters using parallel downloads with asyncio and multiprocessing.
  • Improved performance by up to 70% in large areas by optimizing tiling to existing satellite image footprints.
  • Seamlessly integrated the downloader with flood detection models in collaboration with supervisors.
  • Developed a user-friendly ARCGIS front-end, connected to a REDIS database for efficient queries and real-time output.
  • Commended by United Nations Development Program (UNDP) experts at the QCRI-UNDP workshop.

Course Projects

Cloud Computing (INFSCI 2750), Blockchain assisted data storage

Cassandra, Ethereum, Python
FEB - MAR 24

  • Designed and developed a blockchain-assisted verifiable data storage system using Cassandra, Ethereum and Merkle Trees
  • Configured CAssandra and Ethereum to run on 3 remote machines and on local Docker container
  • Demonstrated verification for data integrity under normal and tampered scenarios
Machine Learning (INFSCI 2595), Regression and classification of paints, PPG

RStudio
NOV-DEC 23

  • Developed and evaluated 20 linear models for regression and classification tasks including bayesian models, linear models, neural networks and XGBoost models.
Database Management (INFSCI 2710), E-commerce platform

Django, Bootstrap 5, SQLite

  • Designed and implemented a multi-tiered e-commerce system with hierarchical user roles using Django and Bootstrap 5.
  • Developed a robust backend infrastructure with SQLite, Django.
  • Implemented effective testing, error handling, and identified system limitations for future improvements.
Semantic Tooth Segmentation using CycleGAN

Pytorch
NOV – DEC 22

  • Implemented Synseg-Net for instance segmentation on tooth X-ray images using Pytorch, with 93% accuracy, 96% SSIM index and 98% PSNR index

Skills

Languages: Python, R, Java, C++, JavaScript
ML/AI tools: TidyVerse, OpenCV, TensorFlow, Pytorch, XGBoost, Collab
CI/CD: Github, Git actions, Docker
Web dev: HTML, CSS, React, Django, Bootstrap 5, Hugo
Database: MySQL, Hadoop, Cassandra, REDIS, AWS
GIS: ARCGIS, QGIS, Google Earth Engine

Awards & Certifications

Awards
QCRI Summer Internship Project, 2nd place
Huawei, Seeds for the Future, 1st place
Google, Foobar challenge, 4/5 Levels
QU, Dean’s list, 2020-2023

Certifications
DP-900 : Microsoft Azure Data Fundamentals
AZ-900 : Microsoft Azure Fundamentals
CCNAv7: Introduction to Networks
HCIA : Huawei Cloud Service Associate