Sangam Shrestha
PhD Student, Computer Science
Montana State University
PhD Student, Computer Science
Montana State University
I am a PhD student in Computer Science with research interests in programming languages, formal methods, automated reasoning, program synthesis and verification, and trustworthy software systems. My current work explores domain-specific languages and formal approaches for building transparent and reliable decision-support systems.
Before starting my PhD, I earned my Master’s degree in Computer Science from East Tennessee State University. I also have professional experience in software engineering, with a background in full-stack development, cloud computing, and machine learning.
Researching trustworthy decision-support systems for prescribed fire through the SMART FIRES project. Investigating domain-specific language (DSL) design for formalizing regulatory policies and best-practice guidelines, with emphasis on automated policy checks, human-in-the-loop judgment, partial evaluation, policy analysis, and auditable burn/no-burn decisions.
Applied research on reliable tracking infrastructure for the College of Nursing, combining software engineering with field safety constraints. Investigating fault-tolerant communication and offline synchronization; collaborating with faculty and graduate students on research software for publication.
Translating a legacy CMS into a Next.js modular architecture with real-time data and AI interfaces for education research content. Contributing to UX and system evaluation for accessibility and performance.
Supported 100+ undergraduates in programming and web development through labs, mentoring, curriculum materials, and grading. Mentored and onboarded 3 new TAs; helped raise student averages from C− to B.
Built a cross-platform real-estate ERP (Spring Boot, Angular, MySQL) and migrated on-premise infrastructure to AWS. Optimized high-traffic queries (15s → <3s), added multilingual UI, and improved uptime with CloudWatch monitoring.
Open to research collaborations, internships in software engineering, programming languages, formal methods, and verification of AI/LLM-generated code.
Email: [email protected] · Phone: +1 (423) 672-8789