Aakash Kulkarni

Graduate Research Assistant | Full Stack Developer

📧 aakashkulkarni36@gmail.com 🔗 linkedin.com/in/aakashkulkarni36 💻 github.com/aakashkulkarni36

Academic Background

Oregon State University

Mar 2023 - Mar 2025

Master of Science in Computer Science (GPA: 3.91/4.00)
Coursework: High Performance Computing, Deep Learning, Parallel Programming
Research Focus: Heterogeneous bug detection in HPC systems under Dr. Manish Motwani

Jawaharlal Nehru Technological University

Jul 2018 - Aug 2022

Bachelor of Engineering in Computer Science (GPA: 7.25/10.00)
Core Studies: Data Structures, Operating Systems, Database Management

Professional Experience

Graduate Research Assistant

May 2024 - Present

Oregon State University College of Engineering, Corvallis, OR
Leading research in software testing methodologies for high-performance computing systems.

Software Developer Intern

Feb 2022 - Apr 2022

Zemoso Technologies, Hyderabad, India
Contributed to enterprise web application development using modern software practices.

Mobile Application Developer

Jul 2021 - Sept 2021

FindMind Analytics (Remote)
Spearheaded development of financial application for adolescent users.

Technical Proficiencies

Languages & Frameworks

  • Python · Java · JavaScript · C++
  • Spring Boot · React · Node.js · Flutter

Systems & Platforms

  • AWS (EC2, S3, RDS)
  • Google Cloud · Firebase
  • HPC Job Scheduling

Methodologies

  • Agile Development
  • CI/CD Pipelines
  • Software Testing

Research Publications

"Automatically Detecting Heterogeneous Bugs in High-Performance Computing Scientific Software"

Davis, M., Kulkarni, A., et al. arXiv preprint arXiv:2501.09872 (2025)

Access Full Publication ↗

Professional Certifications

AWS Cloud Certification

AICTE & Edu Skills Foundation

Oct 2021 - Jan 2022

AWS Cloud Essential Skills

Coursera

Jun 2021

Oracle SQL Certification

Oracle Corporation

Apr 2020

Key Achievements

1st Place Winner

OSU Winter 2024 Hackathon

Mar 2024

Developed "Guitar Hub" - A web application featuring AI-powered song analysis tools using OpenAI and Hugging Face models, combined with real-time pitch detection capabilities.

Published Researcher

Peer-Reviewed Conference Paper

Jan 2025

Contributed to groundbreaking research in HPC software testing methodologies, resulting in publication in top-tier computer science conference proceedings.