Michigan State University computer science student building AI engineering tools, backend automation, and database-driven software. My work spans LLM-based symbolic regression research, Python benchmarking pipelines, API integrations, and secure systems workflows.
I am a Computer Science student at Michigan State University focused on AI engineering, backend development, database systems, and LLM-based symbolic regression research.
I build Python systems that connect research ideas to usable software: model-evaluation pipelines, API-driven automation, secure data workflows, and backend services that make machine learning projects easier to test, measure, and deploy.
Research, backend operations, IT systems, and leadership roles aligned with applied artificial intelligence and reliable computing workflows.
Redesigned device intake and quality-control workflows, improving hardware sorting accuracy by 30% and reducing disposal costs by 20% by identifying reusable assets. Installed, configured, and diagnosed operating systems and hardware while enforcing drive sanitization and data-security standards across high-volume device processing.
Researching LLM-based symbolic regression under Dr. Pang-Ning Tan to test whether generative AI models can discover interpretable mathematical equations from scientific datasets. Built a Python benchmarking pipeline that scores model-generated expressions against ground-truth formulas across 10 experimental configurations, improving repeatability and accelerating evaluation cycles.
Directed a 30-person student team supporting a nonprofit computer refurbishment effort, managing donation intake, diagnostics, and distribution. Maintained a 98% first-contact repair success rate and streamlined the refurbishment pipeline, cutting processing time by 30% through SOP documentation and team coordination.
Michigan State University coursework and minors connecting machine learning, backend systems, algorithms, and quantitative computing.
Academic focus includes machine learning, operating systems, software engineering, algorithms, probability and statistics, and mathematically grounded computing.
High School Diploma completed in 2023. Built an early foundation in computing, technical problem-solving, and leadership through school and nonprofit technology work.
2026 2nd International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI)
8–9 May 2026 · Greater Noida, India
Publisher: IEEE · Added to IEEE Xplore: 18 August 2026
2026 IEEE 5th World Conference on Applied Intelligence and Computing (AIC)
29–30 August 2026 · Jabalpur, India
Publisher: IEEE · Added to IEEE Xplore: 6 October 2026
An agentic AI system in development that discovers interpretable equations from numerical datasets through iterative refinement.
A multi-agent system in development that analyzes market data, news, and sentiment to generate structured trading signals.
An offline authentication system that uses QR challenges and acoustic chirps to authenticate Android devices.
An AI-powered app that extracts tasks and deadlines from PDFs and syncs them with Microsoft To Do.
An AI-powered CLI that scans GitHub repositories for potential security vulnerabilities and generates structured reports.
I’m looking for internship, research, and engineering opportunities where I can contribute Python, machine learning, API integration, and data systems work to products or research teams.
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