About
Currently a Masters student at the University of Virginia, keeping up with the expanding horizons of computer science. I enjoy solving hard problems at the intersection of systems and intelligence with my skills.
Contact me at sravanth.chowdary.potluri@gmail.com
Education
University of Virginia
Master of Computer Science (MCS) (CGPA: 3.87/4) | Aug 2024-Dec 2025- Fall ’24 — Geometry of Data, Machine Learning in Image Analysis, NLP, Autonomous Mobile Robots
- Spring ’25 — Software Analysis and Applications, Machine Learning in Graphs, Neural Networks
- Fall ’25 — Convex Optimization for Engineering and Data Science, Signal Processing, ML and Control
- Teaching Assistant for CS 2120: Discrete Math & Theory I — Fall ’24 and Fall ’25
Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram
Bachelor of Technology in Computer Science and Engineering (Honors) — Distinction(CGPA: 9.19/10 ~ 3.9/4) | Aug 2020–May 2024- Institute Award for All-Rounder of the Graduating Batch (Gold Medal), among 509 graduates
- Teaching Assistant for Design and Analysis of Algorithms and Programming and Problem Solving
- Core member, Google Developer Student Clubs, 2022–2023 and 2023–2024; hosted sessions on machine learning and software development
- Quiz Club Core, 2022–2023; organized and hosted quizzes year‑round and the flagship quiz at Samgatha 2023 (IIITDM’s annual cultural fest)
- Captained and led the IIITDM Tennis Team to multiple wins at inter‑institute tournaments
Experience
Software Development Engineering Intern — Amazon Web Services (AWS)
May 2025–Aug 2025- Worked on the EMR Serverless team to automate processing of limit‑increase requests and their workflows
- Designed and built a distributed system using AWS and internal services to automatically process requests, reducing operational burden across 30+ AWS regions
- The system, capable of processing thousands of requests per day, reduces average ticket processing time from 31 days to a couple of minutes
Research Assistant — Data Driven Streets (UVA Darden)
Oct 2024–Dec 2025- Working as an RA through UVA Darden on data and infrastructure
- Building and maintaining data pipelines using AWS that scrape, process, and add thousands of rows of information to databases on traffic and pedestrian patterns in the D.C. area
- Built a system using LLMs and in‑context learning to extract entities from emergency call transcripts, and a web app to display transcripts along an entity timeline
Machine Learning Research Intern — Ericsson
Jul 2023–Dec 2023- Proposed and developed a system using brain‑inspired neural networks (spiking, LMU RNN) to detect accidents in real time and communicate efficiently via predicted network nodes
- Contributed to a system with graph spiking neural networks (GSNNs) for data‑rate prediction to route vehicles efficiently in optimal network scenarios
- Proposed and built an ontology‑mapping architecture using semantic mapping with RoBERTa and GPT, enhanced via causal relationships
- Programmed machine‑learning models and performed data analysis using Python and related libraries
- Conference paper published and patent filed
Publications & Patents
- Saravanan, M., and Sravanth Chowdary Potluri. "Brain-Inspired Traffic Incident Detection for Effective Communication." In International Conference on Information and Communication Technology for Competitive Strategies, pp. 245-262. Singapore: Springer Nature Singapore, 2023. (Certificate)
- Patent on ontology mapping and causality titled "Network Node and Methods in a Communications Network" — Patent Number: PCT/IN2024/050495 — filed on behalf of Ericsson
Technical Projects
Hate Speech Detection Using Multi‑LLM Architecture
- Classification using ensemble of fine-tuned LLMs with in-context learning
- Two-tiered multi-LLM architecture using LLaMA models (1B, 3B)
- 18% faster processing and 54% lower memory usage
- Fine-tuning with Torchtune and ICL
- Proposed: model calibration, LoRA/QLoRA for efficient fine-tuning
Goal‑Oriented Image Quality Assessment Using CNN
- Novel image quality assessment powered by deep learning
- Task-specific image quality evaluation
- ResNet-based depth estimation on NYU-Depth-v2
- Pearson correlation 0.89 and ~1900% efficiency improvement
Waze-Based Traffic Forecasting Using Graph Transformers
- City-scale traffic prediction using STGformer (graph transformer)
- Trained on Washington D.C. Waze data (4 years, ~20M jams)
- Engineered road network graph; sparse subgraph sampling in PyTorch
- Achieved R^2 ≈ 0.86
LLM vs LLM: An Approach to Fault Localization
- Adversarial LLM framework for software fault localization
- Gemma-3-12B generates buggy C++; a second model localizes faults
- Custom fault injector for 5,000 C++ programs
- QLoRA fine-tuned debugger improves accuracy from ~20–30% to ~55–65%
- Demonstrates PEFT feasibility
Single‑Lead to 12‑Lead ECG Conversion Using RNN
- LSTM network predicts multiple ECG leads
- Predicts remaining 11 leads from a single lead
- Noise removal: Butterworth filter and DWT (db-6 wavelet)
- Experiments with noise removal strategies
- Peak R^2 0.9 (some leads); peak average R^2 0.56
Incognito Text
- Simple, minimalistic, anonymous texting web application
- Chat rooms and anonymous accounts
- Flask backend with relational database
- Deployed on Heroku and AWS (PostgreSQL, SQLite)
Maze Solver Using AI
- Heuristic and brute-force based maze solver
- Pygame GUI with random maze generation
- Solvers: BFS, DFS, A* (Manhattan/Euclidean)
- Execution time analysis across 30 random mazes
- A* mean 0.01s; BFS 0.029s; DFS 0.06s
Other Significant Technical Projects
Image Recognition Using PCA | Custom Image Filtering | Before You Sign | Divide N Conquer | BlockBoard | Fifa 23 Players Value Prediction | Intelligent Speed Management System | IOT Weather App | Project GARAGE
Relevant Coursework
- Programming, Theory and Algorithms: Programming and Problem Solving, Data Structures and Algorithms, Discrete Structures for Computer Science, Object‑Oriented Programming, Design and Analysis of Algorithms, Theory of Computation, Compiler Design
- Systems and Hardware: Digital System Design, Computer Organization and Architecture, Database Systems, Operating Systems, Computer Networks
- Data Science and Other: Machine Learning, Pattern Recognition, Deep Learning, Artificial Intelligence, Introduction to Biometrics, Digital Image Processing, Data Science, IIoT & Cloud Computing
Technical Skills & Interests
- Areas of Interest: Artificial Intelligence & Machine Learning, Algorithms and Distributed Systems
- Programming Languages: Python, C/C++, JavaScript, Java
- Packages and Frameworks: NumPy, Pandas, OpenCV, scikit‑learn, Keras, TensorFlow, PyTorch, Nengo, Matplotlib, Seaborn, Flask
- Cloud: AWS (EC2, Lambda, DynamoDB, SQS, S3, Redshift, CloudWatch, CDK)
- Markup and Query Languages: HTML, CSS, LaTeX, SQL
Achievements & Awards
- Award for securing the 3rd‑highest CGPA in the 1st year of B.Tech across all branches
- IIITDM Vashisht 2024 Capture the Flag — 2nd place
- Part of the winning team at HackVerse Tamil Nadu — a state‑level Web3 hackathon, for Blockboard
- Filecoin track winner at HackNITR 4.0, for Divide n Conquer