ADVAITTAHILYANI
Computer Science student from UIUC with expertise in full-stack development, machine learning, and high-performance computing. Currently advancing research in parallel programming and compiler optimization.
About Me
I'm a passionate Computer Science student at the University of Illinois at Urbana-Champaign, specializing in software engineering, machine learning, and distributed systems. My experience spans from developing high-performance computing solutions to creating user-friendly mobile applications.
Currently, I'm advancing research in parallel programming frameworks and compiler optimizationwhile maintaining a strong focus on practical applications that solve real-world problems.
Work Experience
Research Intern
Parallel Programming Lab
April 2025 – Present
- • LiveViz Development: Architected and implemented real-time aggregated visualizations across distributed computing nodes within Charm++, enabling researchers to monitor large-scale parallel applications
- • NumPy Enhancement: Extended Charm++-based NumPy abstraction by implementing intuitive unary, binary, and ternary operators, improving developer productivity by 40%
- • Infrastructure Contribution: Contributed to Reconverse, a comprehensive rewrite of Charm++'s core infrastructure, significantly improving performance and maintainability
- • Research Impact: Collaborated with PhD students and faculty on cutting-edge parallel programming research, contributing to publications and conference presentations
Software Development Intern
Glance
June 2024 – August 2024
- • Full-Stack Development: Architected and developed comprehensive web solutions using Java Spring Boot, React.js, Redis, and PostgreSQL, serving 4.5M+ monthly active users
- • E-commerce Platform: Deployed critical features and performance improvements to Glance's e-commerce platform (Roposo Clout), directly impacting revenue generation and user experience
- • Search Implementation: Designed and implemented an efficient search autocomplete system with Redis caching, reducing search response time by 60% and improving user engagement
- • System Architecture: Enhanced microservices architecture and configured Confluent Kafka for real-time data streaming, enabling seamless integration across distributed systems
- • Performance Optimization: Optimized database queries and implemented caching strategies, resulting in 35% improvement in application response times
Tech Consulting Intern
Ernst & Young LLP
June 2022
- • Client Solutions: Led implementation of Microsoft Dynamics 365 to enhance a Fortune 500 client's customer service system, improving case resolution time by 45%
- • ML Model Development: Designed and deployed a sophisticated machine learning model using NLP techniques to analyze emails and automatically assign support cases with 89% accuracy
- • System Analysis: Conducted comprehensive analysis of Dynamics 365's model training process and underlying neural network architecture, identifying critical performance bottlenecks
- • Strategic Recommendations: Presented actionable findings and recommendations to Microsoft engineering teams to improve model accuracy and streamline training processes
- • Process Optimization: Developed automated workflows that reduced manual case assignment by 70%, saving approximately 20 hours of manual work per week
Virtual Student Developer
Microsoft Technology Center
June 2021
- • AI Model Development: Leveraged Microsoft's Custom Vision API and developed a robust TensorFlow model to identify and classify lettuce plants in agricultural settings
- • Disease Detection: Implemented computer vision algorithms to assess plant health with 95% precision, enabling early disease detection and prevention in crop management
- • Spatial Analysis: Designed coordinate transformation system to convert image coordinates into agricultural field grid patterns (rows and columns) for precise location mapping
- • Integration Ready: Structured output data as JSON APIs for seamless integration with farming management systems and mobile applications
- • Agricultural Impact: Created a scalable solution that could potentially reduce crop loss by 30% through early disease intervention
Research Experience
Research Assistant
Adapt Lab
May 2025 – Present
- • Designed a rule-based DNN operator fusion layer for Google's XLA compiler (Accelerated Linear Algebra)
- • Used mapping-type taxonomy, reducing compilation latency and significantly improving element-wise kernel performance
Research Assistant
Shajahan Lab
January 2025 – May 2025
- • Trained a YOLOv8 segmentation model to detect corn ears in agricultural footage
- • Achieved high-confidence predictions and implemented an object tracking system that counts corn ears in video sequences
- • Developed automated yield estimation system for agricultural applications
Education & Achievements
University of Illinois at Urbana-Champaign
Bachelor of Science in Computer Science
Minor in Electrical Engineering
3.98
GPA
May 2027
Expected Graduation
Academic Roles
CS 124 Tutor
January 2024 – Present
Host office hours, assisting over 200 students with Kotlin fundamentals and Android development
Leadership & Organizations
Illinois Semiconductor Student Alliance
Software Team Lead • August 2024 – Present
Leading development of educational tools and RF transceiver design
Nand2Tetris Project
May 2024 - Present
Built CPU and compiler from scratch, created Snake game in custom language
Projects & Leadership
CS 124 Tutor
Host office hours, assisting over 200 students by clarifying concepts and debugging programs. Help teach Kotlin fundamentals as well as Android App development concepts to students.
Illinois Semiconductor Student Alliance
Developed an interactive 3D game in Unity to educate high school students about the semiconductor manufacturing process. Designed and implemented a Radio Frequency (RF) transceiver using Bipolar Junction Transistors (BJTs).
Nand2Tetris
Constructed simulated components including the CPU and compiler from scratch for the Nand2Tetris course. Designed a primitive version of the Snake game using a custom-created programming language.
NoteTaker
Developed a Swift app integrating Whisper and Phi-3 for local transcription and summarization of recordings. Expanded it to run on a RPi server where users can upload recordings and have summaries uploaded to their Google Drive.
Hack Illinois - Roomie Match
Developed a web app designed for college freshmen to find compatible roommates. Implemented advanced features using React, including filters, chat, and recommendation systems.
Aether
Developed a fully functional AI-powered email client emphasizing privacy and convenience using React Native and Postgres. Leveraged a lightweight local LLM to provide quick summaries, context-sensitive responses, and intelligent search offline.
Technical Skills
Programming Languages
Frameworks & Libraries
Databases & Tools
Specializations
Let's Connect
I'm always interested in discussing new opportunities, innovative projects, and potential collaborations. Feel free to reach out!