# Rishabh Mahesh > Computer Science @ Purdue University Location: Livermore, California, United States Profile: https://flows.cv/rishabhmahesh ## Work Experience ### Software Project Manager @ Purdue Momentum Jan 2026 – Present | West Lafayette, Indiana, United States - Leading the StockScope project as Project Manager and guiding the team to explore new implementations of novel algorithms to determine minute relationships between stocks - Building relational graphs and visual explanations for investors of all skill levels utilizing NLP and lag time prediction algorithms - Completely revamping the frontend and working on secure user login with OAuth with JWT web token communication and full backend integration with PostgreSQL ### Software Engineer @ Purdue Momentum Jan 2025 – Jan 2025 | West Lafayette, IN - Building StockScope, a FinTech solution with constructive NLP integration to create an interactive investment platform, influenced by 24/7 data streams and algorithm-based analyses on stock/ETF/crypto performance and news - Custom sentiment analysis developed in-house and fine-tuned to provide an optimal user experience - Marries accurate medium-long term stock prediction through MACD, RSI, and Bollinger Band predictor factors with spontaneous influences using web scraping and live news analytics, and provides advice for investors - React.js frontend, Flask backend, Alpha Vantage/Yahoo Finance API, custom Python-based sentiment analysis, plotly/D3.js interactive charting - Part of a team of 10 developers with a focus on building an all-encompassing MVP and expanding further to adjust sentiment-analysis and adjusting the weightage of predictors through Agile-based sprints ### Software Engineer @ Purdue Aerial Robotics Jan 2026 – Present | West Lafayette, Indiana, United States - Competing in the C-UAS competition and am working on software for both competition (traditional two wing) and R&D (VTOL) teams - Building software in Rust for the Purdue Aerial Robotics Team to control the on board camera and gimbal to take photos at certain times and build dynamic logic to point towards certain targets several hundreds of feet away - Designed, fixed, and interfaced key components of the gimbal control API within the main software suite running on the drone and built new functions and control logic to streamline camera priority queue and improved communication speeds to 100 HZ for faster data parsing and actionability within avionics - Built an internal tool with Leaflet.js and Python to pull data directly from the PostgreSQL database live and update points in a map interface to track drone movement with coordinate points and log/iterate on accuracy of the drone's movement and targetting - Helping with development and training of a custom YOLO/DFine target detection model for the specific target descriptions as described by the C-UAS 2026 Competition guidelines with number based distinction ### Undergraduate Student Researcher @ The Data Mine-Purdue University Jan 2025 – Present | West Lafayette, Indiana, United States - Working with R and Python to solve data-based problems and applying data science fundamentals to scalable datasets, mainly from csv and csv2 files - Conducting advanced data organization operations and plotting/visualization on meaningful topics - Writing documentation and code breakdowns to convey data-science techniques learned and applied for each project - Participate in Professional Development workshops and advance knowledge through career-first interactive events ### Undergraduate Artificial Intelligence Researcher @ Purdue Vertically Integrated Projects (VIP) Jan 2025 – Jan 2025 | West Lafayette, Indiana, United States - Developing a custom-trained, validated, and tested machine learning model to analyze images from social media and news to categorize and consolidate natural disaster information in real-time to provide accurate and timely reports for first responders and FEMA to act upon - Creating data filtering and cleaning methods for images through vectorization and HSV breakdowns for use in from-scratch Decision Tree and Random Forest algorithms with distinct hyperparameter adjustments to better fit the data and adjust for imbalance - Developing a decision tree tracking visualization algorithm to accompany the model for direct insight into the inner workings of the image "binning" and decision tree creation process - Mainly using data from the CrisisMMD disaster information dataset, with a goal of expanding the model to include multimodal capabilities - Working in a team with guidance from PhD candidate Soudabeh Taghian and building off of previous publications in the field ### Computer Science Researcher/Intern (Science Internship Program @UCSC) @ Baskin Engineering at UCSC Jan 2024 – Jan 2024 | Santa Cruz, California, United States As predicted by academia and industry, wireless fidelity (Wi-Fi) technology suffers from the limited radio frequency (RF) spectrum issue. That being said, with this massive growth in Wi-Fi-connected devices and high demand for downloading large data packets, such as AR and VR applications, Wi-Fi will no longer be able to provide a good Quality of Service (QoS). I worked under my mentor, Firouz Vafadari, a distinguished PhD student at UC Santa Cruz's Baskin Engineering and co-founder of Light Links, the only VLC startup in the Silicon Valley/Bay Area. This project aimed to focus on the challenges of designing a VLC system by re-building the Medium Access Control (MAC) layer and Physical Layer (PHY), employing modulation techniques that can provide a high data rate with low Signal Noise Ratio (SNR)—eventually, writing the code to send a binary packet over our testbed equipment. Python and MATLAB were used heavily throughout the research period and at the end of research we were able to implement a custom packet structure with OOK modulation that was able to successfully send over 5-bit length data payloads at a time. With the correct hardware, our transmitter and receiver code would achieve VLC, which could be compounded with a pre-existing Wi-Fi solution to provide higher bandwidth freedom. ### Student Ambassador Leader @ Snowflake Jan 2023 – Jan 2024 | San Francisco, CA Planned monthly syncs for the larger Student Ambassador group, which focused on covering new Streamlit releases, highlighting Student Ambassadors who have made contributions to the Streamlit community, and sharing Streamlit-related opportunities with the larger group. Directed hundreds of Student Ambassadors in advancing their software and machine learning careers across 75+ top universities in 6+ countries, and worked with my manager to advance education for future titans of the software industry. Developed an internal web-based platform for ambassadors to log their network, detail events they've hosted at their universities/in their communities, track their outreach, manage their resources, and provide reports to me and the other managers, mainly using React.js, Node.js, MongoDB, and Express.js. Conducted webinars on Streamlit-related topics and career-focused panels with full-time employees from Snowflake. ### Computer Science/Machine Learning Intern @ #GoBeyond Jan 2023 – Jan 2023 | Los Angeles, California, United States At GoBeyond I worked with other interns and my supervisor to work towards developing various groundbreaking software-based technologies catered to aiding the autoimmune disease community with the use of Machine Learning and software development in Python. ### Research Intern @ Aspiring Scholars Directed Research Program (ASDRP) Jan 2022 – Jan 2022 | Fremont, California, United States I researched under the Downing research group on the "Searching for mini-Black Holes using Stellar Radial Distortion" research project. We focused on using Python and R to analyze data collected from various sources regarding astral phenomena that may help us document more information using signals from the visual portion of the EM spectrum. ### Computer Science Research Intern @ Aspiring Scholars Directed Research Program (ASDRP) Jan 2022 – Jan 2022 | Fremont, California, United States Worked with a group under the Subramaniam Research Group regarding an application for individuals that are hard of hearing or have a speech disability. The tool incorporated a TFlite Machine Learning model trained and taught by us which translated hand signals used by the user in ASL into words that could be spoken through a TTS service. We presented our work in a symposium consisting of industry experts and fellow researchers and received positive feedback. ## Education ### Bachelor of Science - BS in Computer Science Purdue University ### High School Diploma Granada High School ### Mission San Jose High School ## Contact & Social - LinkedIn: https://linkedin.com/in/rishabhmahesh --- Source: https://flows.cv/rishabhmahesh JSON Resume: https://flows.cv/rishabhmahesh/resume.json Last updated: 2026-04-10