Bisti Potdar
About Me
Hi! I'm Bisti.
I am a Computer Science student at Purdue University, with a passion for AI/ML and building intelligent systems. I am dedicated to creating technology that makes a tangible impact.
In my free time I like pursuing content creation, music, and reading! Learn more about me OUTSIDE of my work here.
Skills
AI / ML
GANsLLMsRAGAgentsPytorchRLDeep LearningNumpyPandasSQLNoSQL
Languages
C/C++JS/TSReactKotlinPythonJavaHTML/CSS
Misc
REST APIGitLinuxDockerJenkinsCI/CD
Relevant Coursework
Completed
CS251: Data Structures and AlgorithmsCS250: Computer ArchitectureMA265: Linear AlgebraCS240: Programming in CCS176: Data Engineering in PythonCS180: Object Oriented ProgrammingCS252: Systems ProgrammingCS211: Competitive ProgrammingCS471: Introduction to Artificial IntelligenceCS307: Software Engineering I
In progress
CS373: Data Mining & Machine LearningCS348: Information SystemsCS354: Operating Systems
My Experience
May 2025 – Present
ML@Purdue Vice President
Machine Learning at Purdue
- Organized CatapultHacks, Purdue's biggest AI and Entrepreneurship hackathon of 150+ participants. Developed the CatapultHack.com website.
- Led outreach operations by recruiting new members, coordinating faculty partnerships, organizing technical workshops, and managing the organization's website and sponsor communication
ΚΘΠ
Nov 2025 – Present
Vice President of Membership
Kappa Theta Pi (ΚΘΠ) – Purdue
- Founding member of Purdue's premiere technology fraternity
- Helped orchestrate and plan events focused on member involvement and engagement
Jan 2026 – Present
Undergraduate Researcher
Eli Lilly and Company
- Working under Dr Brett Meyers in the LRPC Image Enhance Team as part of the Vertically Integrated Projects program
- Building a full stack application to perform pupillometry
Jan 2026 – Present
Campus Ambassador
World
- Selected for the Brand Ambassador Programs initiative and representing World on campus
Jan 2026 – Present
Undergraduate Researcher
The Data Mine - Purdue University
- Collaborating on AI agentic workflows for the Johnson and Johnson Corporate Partners project
March 2025 – Present
Web Developer
InnovateHER Hacks
- Used React Native to develop the website for InnovateHer, Purdue's flagship women-centric hackathon
May 2025 – Aug 2025
Computer Vision Researcher
Purdue University AIM Lab
- Collaborated with a research team under Dr. Lu to design a mobile app improving string musicians' posture and bow hold through advanced computer vision and machine learning models
- Integrated on-device YOLOv11 bounding box models, enabling real-time feedback within a user-friendly mobile application
Projects
CatapultHack Website
January 2026
Designed and built the official website for CatapultHack, a hackathon organization.
Goaly - Accountability Coach
October 2025
Built an MCP-compliant goal tracking server utilizing agentic workflows and LLM integration to decompose high-level objectives, leveraging multi-modal analysis to verify daily progress and enable AI agents to autonomously manage user accountability.
JavascriptPythonExpoGORESTful APIPoke.aiSupabaseRender
BudgetBuddy
June 2025
Developed a budget generation system that converts draft documents and templates into clean, auto-filled spreadsheets, reducing manual work and errors. Includes in-browser template editing via cell-to-text mapping using key value pairs.
TypeScriptNext.jsxlsmMongoDB Atlas
BetterBytes
February 2025
Created for Boilermake 2025, BetterBytes is a web application with in-built barcode scanning functionalities. Using computer vision and LLMs, we built a platform where users can make better choices on which foods to eat based on their own personalized food goals.
AIComputer VisionLLMsUX/UIWeb Applications
Eve. - Menstrual Product ScannerWinner
January 2025
Won first place at InnovateHER hackathon in the health & fitness category. Created a web app that scans menstrual products using the user's web camera and provides health and safety information about the product using the GROQ API. Aimed to solve the lack of transparency women face regarding menstrual products.
LLMComputer VisionCNNData AnalysisGROQ API
Research
GLEAM: GAN and LLM for Evasive Adversarial Malware
October 2023
Published paper in the 2023 14th International Conference on Information and Communication Technology Convergence (ICTC) division of IEEE, receiving first authorship, invited to present at the conference in Korea. Worked alongside a team to create a state-of-the-art machine learning model, coined "GLEAM," to test the creation of evasive malware for cybersecurity systems.
GANLLMMachine LearningCybersecurityIEEE Publication
AIM Lab: Computer Vision Research for String Musicians
May 2025 – Aug 2025
Collaborated with a research team under Dr. Lu to design a mobile app improving string musicians' posture and bow hold through advanced computer vision and machine learning models. Integrated on-device YOLOv11 bounding box models, enabling real-time feedback within a user-friendly mobile application.
YOLOv11Computer VisionMobile AppMachine LearningResearch
RED40GAN
2024
Built RED40GAN, a custom Generative Adversarial Network (GAN) using TensorFlow/Keras to generate synthetic UV-Vis spectrometry data for a Beer–Lambert Law calibration curve. Integrated machine learning with experimental chemistry to model Red 40 concentration, producing synthetic data that closely matched real lab measurements. Reduced experimental percent error from 376% to 38%, demonstrating how generative AI can improve lab accuracy and reduce human error in chemical analysis.
TensorFlowGenerative Adversarial Networks (GANs)UV/Vis SpectroscopyKerasMachine Learning