Education
Ph.D. in Computer Science (2024 - 2028)
University of Delaware
Advisor: Dr. Sunita Chandrasekaran
Focus: High Performance Computing, Compiler Validation, GPU Programming
Bachelor of Science in Electrical Engineering (2023)
University of Delaware
Honors & Awards
Professional Experience
Software Engineer
University of Delaware, Exascale Computing Project SOLLVE • May 2023 - December 2023 • Newark, DE, USA
- • Implemented critical bug fixes and performance optimizations in LLVM OpenMP offloading runtime, directly impacting compiler reliability for 15+ DOE exascale applications
- • Developed automated testing protocols for multi-GPU systems validation, reducing manual testing overhead by 60% across national laboratory computing facilities
- • Enhanced LLVM ecosystem sustainability through collaborative debugging with AMD and NVIDIA compiler teams, establishing best practices for heterogeneous computing compiler development
Teaching Assistant
University of Delaware, Computer & Information Sciences • August 2022 - May 2023 • Newark, DE, USA
- • Supported Computer Science courses through lab instruction, adapting communication to diverse learning styles
- • Provided technical assistance and contributed to coding projects with interactive in-class activities
- • Delivered tailored support empowering success of future engineers and computer scientists
Undergraduate Researcher
University of Delaware, Computational Research and Programming Lab • September 2020 - May 2023 • Newark, DE, USA
- • Led development of comprehensive OpenACC Validation & Verification testsuite ensuring correctness and reliability of both open-source and proprietary compiler implementations across multiple vendors
- • Developed functional testing framework covering OpenACC 3.0+ specifications, identifying critical compiler bugs and specification ambiguities that influenced OpenACC standard revisions
- • Coordinated cross-institutional collaboration with software engineers and researchers to establish industry-standard testing protocols for directive-based parallel programming models
- • Managed team utilization of national supercomputing resources (Summit, Frontier, Perlmutter) for large-scale compiler validation across heterogeneous CPU-GPU architectures
- • Delivered research outcomes through high-impact publications, conference presentations, and direct engagement with compiler vendor teams to improve OpenACC ecosystem quality
Undergraduate Researcher (REU)
Indiana University, Research Experience for Undergraduates • Summer 2021 • Bloomington, IN (Remote)
- • Managed and executed computational research workflows using Jetstream and XSEDE supercomputing cloud resources
- • Validated compiler and runtime compliance with parallel programming standards by developing and running test suites for OMP SOLLVE and OpenACC (Validation & Verification, V&V), ensuring conformance to specification definitions
Undergraduate Researcher (REU)
Indiana University, Research Experience for Undergraduates • Summer 2020 • Bloomington, IN (Remote)
- • Developed a Python-based web-scraping application to collect and rank high-performance computing systems, utilizing SPEC (Standardized Performance Evaluation Corporation) benchmarks
- • Leveraged Jetstream cloud computing resources to deploy, test, and maintain a performance ranking website for comparative analysis in HPC research
Professional Training
Argonne Training Program on Extreme-Scale Computing (ATPESC)
Argonne National Laboratory • Summer 2025 • St. Charles, IL, USA
- • Completed advanced training in extreme-scale computing through ATPESC 2025, gaining expertise in performance-portable programming across heterogeneous architectures (CPUs, GPUs, quantum processors)
- • Mastered state-of-the-art debugging, profiling, and visualization tools for large-scale scientific applications on DOE supercomputing facilities
- • Developed proficiency in community code development, software sustainability practices, and big data methodologies for computational science and engineering
- • Applied machine learning and AI integration techniques for scientific computing applications, with focus on scalable algorithms for next-generation exascale and quantum computing platforms
HenStreet Hacks
University of Delaware • Summer 2025
Competed in HenStreet Hacks, designing and presenting a technology-driven solution for SallieMae in a fast-paced hackathon environment, collaborating with peers to deliver impactful results and demonstrate innovative problem-solving skills.
UD + ATOM Hackathon
University of Delaware and ATOM • Summer 2024
Collaborated in the UD+ATOM Hackathon to develop innovative solutions in high-performance computing, leveraging cross-disciplinary teamwork and rapidly prototyping new technologies to address real-world challenges.
HenHacks - govAIde
University of Delaware • 2024
- • Developed govAIde, an AI-powered platform using Streamlit and OpenAI's GPT-3.5 that streamlines access to government aid, job opportunities, and housing for disadvantaged communities by providing personalized recommendations and demystifying complex eligibility processes
- • Led technical integration of advanced language models and user-friendly interfaces, prioritizing privacy, data security, and social impact, resulting in positive user feedback and adoption during early trials
Technical Expertise
Programming Languages
Tools & Technologies
Relevant Coursework (Graduate Level)
Advanced Topics of Quantum Information
Studied quantum computing models, quantum information theory, and their application to high-performance and GPU-accelerated systems, including quantum algorithms, error correction, and implications for next-generation AI and scientific computing.
Computer Systems: Architecture
Explored recent advances in computer architecture, including multicomputer and multiprocessor systems, and analyzed the impact of emerging parallel machine designs on modern architectural development.
Algorithm Design and Analysis
Developed expertise in algorithm design and analysis, including complexity evaluation, optimization techniques, and rigorous assessment of algorithmic efficiency across diverse computational problems.
Compiler Construction
Gained hands-on experience in compiler construction, covering lexical analysis, parsing, semantic analysis, and code generation, with practical implementation of language translation techniques and optimization strategies.
Artificial Intelligence
Studied foundational and advanced topics in artificial intelligence, including search algorithms, machine learning, reasoning, and problem-solving, applying AI techniques to real-world computational challenges.
Engineering Mathematics
Demonstrating proficiency in linear algebra, vector spaces, and differential equations with an emphasis on engineering applications.