About
Hi there! My name is Abhijit Chebiyam, and I am a graduate from the University of Illinois at Urbana-Champaign with a Bachelors of Science in Computer Engineering. I am currently doing my Masters in Computer Science at the University of Illinois at Urbana-Champaign while working as a full-stack engineer at J.P. Morgan Chase.
Full-Stack Software Engineer
- Birthday: January 5th, 2001
- Email: abhichebiyam@gmail.com
- City: New York, NY
- Phone:+1 (408)-499-6252
My interests lie in Maching Learning, Artificial Intelligence, and Data Science. I have practical experience working with several programming languages, frameworks, and technologies including Python, Java, React, and AWS. I am also experienced in working with databases such as MySQL and PostgreSQL. If you would like to learn more about me, feel free to reach out to me via email or phone number.
Skills
This section details the languages and technologies I'm most experienced in.
Resume
Education
University of Illinois at Urbana-Champaign
Masters in Computer Science
May 2023 – Present
Coursework: Data Visualization, Applied Machine Learning, Database Systems, Cloud Networking, Software Engineering, Theory and Practice of Data Cleaning
University of Illinois at Urbana-Champaign
Bachelors of Science in Computer Engineering
Aug. 2019 - May 2023
Coursework: Data Structures, Models of Computation & Algorithms, Artificial Intelligence, Computer Systems Engineering
KTH Royal Institute of Technology
School of Electrical Engineering and Computer Science (Study Abroad)
Jan. 2022 – June 2022
Coursework: Internetworking, Internet of Things, Modern Software Development, Robust and Probabilistic Design
Projects & Certifications
Illinois Scholar Undergraduate Research Program
- Developed a stock prediction machine learning algorithm using Python and TensorFlow, leveraging historical stock data and technical indicators to forecast future stock prices, achieving an 85% accuracy rate in backtesting
CS416 Data Visualization Final Project
- Created a website using HTML, CSS, and the D3 library to explain Netflix’s viewership through interactive data visuals, resulting in a 30% improvement in data comprehension, and a 50% reduction in page rendering time
Professional Experience
Nuro
Software Engineering Intern - Mountain View, CA
Jun. 2022 - Aug. 2022
- Developed a comprehensive requirements document specifying fault definitions at the system level and built a verification plan using C++, improving fault detection accuracy by 30% and reducing system downtime by 20%
- Designed a Python script based on the gRPC framework to find correlations between module exits and latency kickouts, leading to identification of 12 critical latency issues and a reduction in average latency by 70 milliseconds
- Implemented continuous integration of fault-detection scripts using Jenkins and improved GoogleTests coverage by over 80% to ensure QA testing of system-level faults related to memory usage, disk space and link speed
- Utilized SQL to extract Log IDs from BigQuery, analyzing data to identify extraneous error thresholds for safety-critical faults. Developed a React-based dashboard to enable real-time monitoring of these thresholds
Intel
Software Engineering Intern - Folsom, CA
May 2021 - Aug. 2021
- Instituted implementation of Movidius VPU through Python, leveraging PyTorch’s extensive library to improve processing speed by 20 milliseconds and enhanced computing performance through the Pandas library
- Integrated Infer Request API within OpenVINO Inference Engine to run image classification sample in asynchronous mode, containerized the application using Docker, and deployed it on a Kubernetes cluster, resulting in a 4x improvement in consistency of development/production environments and deployment cycles
Technical Skills
- Languages: Java, Python, C/C++, SQL, Scala, Javascript/Typescript, HTML/CSS, R, Terraform, MATLAB, HCL
- Frameworks: Pytorch, Pandas, Tensorflow, Spring Boot, NumPy, React, Node.js, Flask, Hadoop, OpenCV, Sckit-learn
- Technologies: Kubernetes, Docker, Jenkins, Postman, VS Code, Jira, Swagger, Git, Azure, BigQuery, Microsoft 365
- Amazon Web Services: EC2, S3, RDS, Lambda, CloudFront, SNS, SQS, VPC, Redshift, IAM, KMS, Athena, EBS