# Vishnu Reshamwala

> Software developer at Linked2Pay, based in Los Angeles. M.S. in Computer Science from CSU Channel Islands, where my thesis connected GPT-4o to a Sawyer robot you can talk to.

I'm a Los Angeles–based software developer at Linked2Pay, where I build and maintain our CRM and APIs. I joined as an intern in August 2025 and went full-time in January 2026.

I did my master's in computer science at CSU Channel Islands with a 3.9 GPA. My thesis put a Sawyer robot arm on the other end of a conversation: you ask for something, GPT-4o finds it through a camera, and the arm moves it where you asked and talks back.

I also build things with AI. Bink is a shopping assistant you can describe things to, or just show a photo, and TinderJob brings swipe-right matching to hiring.

My team won Best Visualization Overall (graduate/alum) at CSUCI's Plot-A-Thon in 2026, and I won the CSUCI Mission & AWS Hackathon back in 2023.

## Links

- Website: https://v1shnucs.com
- Email: vishnureshamwala@gmail.com
- GitHub: https://github.com/v1shnucs
- LinkedIn: https://www.linkedin.com/in/v1shnucs
- Resume (PDF): https://v1shnucs.com/Vishnu_Reshamwala_resume.pdf

## Experience

### Software Developer, Linked2Pay (Oxnard, CA)
Jan 2026 – Present

Develop and maintain the CRM and APIs, keeping them accurate and secure, and build new features and integrations with the development team.

Tech: Java, JSF, PrimeFaces, JBoss, EJB

### Software Developer Intern, Linked2Pay (Oxnard, CA)
Aug 2025 – Dec 2025

Shipped production code for a payment integration, built automated JavaScript test flows, and ran manual test cases, bug tracking and integration testing across CRMs and APIs.

Tech: PHP, Docker, React

### IT Help Desk Student Assistant, CSU Channel Islands (Camarillo, CA)
Aug 2024 – Aug 2025

Provided technical support to students and faculty, troubleshooting hardware and software across campus and maintaining IT documentation.

## Education

- M.S. Computer Science, California State University Channel Islands, Camarillo, CA (Aug 2023 – Dec 2025). GPA 3.9 / 4.0.
- B.E. Computer Engineering, Bhagwan Mahavir College of Engineering and Technology, Surat, India (Jul 2018 – May 2022). CGPA 7.85 / 10.

## Projects

### SawyerSense
MS thesis · CSU Channel Islands · Advised by Dr. Bahareh Abbasi

SawyerSense is the system I built for my master’s thesis at CSU Channel Islands: an intelligent human-robot interaction system that lets people direct a Sawyer collaborative robot with their voice.

When it starts, the arm moves to a photo position and an Intel RealSense camera captures the workspace. GPT-4o handles object detection, recognizing the shapes and colors on the table, while a GPT service turns spoken commands into grab-and-place actions. The robot answers out loud through text-to-speech.

Sawyer runs on ROS1, which isn’t compatible with modern AI libraries out of the box. I wrote a FastAPI bridge between the two so the language and vision services could drive the robot, and added sensor-based retry logic for when the gripper misses a grab.

The GPT and vision services run as separate FastAPI apps alongside the ROS launch files, and the ROS deployment is containerized with Docker. I also experimented with several LLMs to balance reasoning quality against latency.

Stack: Python, ROS, Intera SDK, OpenAI GPT-4o, FastAPI, Intel RealSense, Docker
Page: https://v1shnucs.com/projects/sawyersense
Code: https://github.com/v1shnucs/SawyerSense
Thesis: https://scholarworks.calstate.edu/concern/theses/3r0754076

### Bink
AI · Full-stack

Bink started as a startup-competition concept, and I turned it into a working prototype: a shopping assistant with conversational, multimodal search. You can describe what you’re after, or upload a photo.

Google Gemini drives the conversation. It understands text and image input, makes fashion recommendations, and generates the search keywords. SerpApi then pulls real-time results from Google Shopping, with a general mode and a “thrift” mode for second-hand finds. It also has a virtual try-on.

I built the full stack: a React frontend deployed on Vercel, a Node.js backend on Render, and Supabase for user authentication and API rate limiting.

Stack: React, Node.js, TypeScript, Gemini API, SerpApi, Supabase, Vercel, Render
Page: https://v1shnucs.com/projects/bink
Live: https://v1shnu.vercel.app/
Demo: https://www.youtube.com/watch?v=RuH5prSioMQ

### TinderJob
Full-stack

TinderJob reimagines recruiting around a swipe interface: recruiters and job seekers swipe through profiles and match with each other, the way dating apps do.

Behind the cards are JWT authentication, real-time instant messaging and automated interview scheduling. The frontend is React, talking to a NestJS REST API backed by MongoDB.

Stack: React, NestJS, MongoDB, JWT, REST APIs
Page: https://v1shnucs.com/projects/tinderjob

### RAG AI Agent
AI · Full-stack

A chat app for asking questions about your own documents. Upload PDFs, ask anything, and every answer comes with citations to its sources, so you can check its work.

The backend is FastAPI with a LangChain pipeline: documents are embedded into a FAISS vector store for semantic retrieval, and Google Gemini writes the answers. Uploading a new PDF updates the vector store automatically. The frontend is a real-time chat interface built with Next.js and Tailwind CSS.

Stack: Python, FastAPI, LangChain, FAISS, Gemini, Hugging Face, Next.js, Tailwind CSS
Page: https://v1shnucs.com/projects/rag-ai-agent
Code: https://github.com/v1shnucs/RAG-AI-Agent

### Pong AI
Neuroevolution

Classic Pong with an AI opponent that wasn’t programmed to play. It was evolved.

Using NEAT (NeuroEvolution of Augmenting Topologies) through neat-python, a population of 50 neural networks plays against each other, and the best performers reproduce into the next generation. After training, the best network is saved and you can play against it with the W and S keys.

The game itself is built with pygame.

Stack: Python, NEAT, pygame
Page: https://v1shnucs.com/projects/pong-ai
Code: https://github.com/v1shnucs/Pong-AI

### Stock Forecasting App
Machine learning

A small Streamlit app for exploring stock forecasts. Enter a ticker and it downloads the price history with yfinance, then charts the closing price against its 50-, 100- and 200-day moving averages.

The model is a Keras network trained in the accompanying notebook, using the previous 100 days of prices to predict the next. The app plots its predictions against the actual prices to show how well the model performs.

Stack: Python, TensorFlow / Keras, Streamlit, yfinance, scikit-learn, Matplotlib, Jupyter
Page: https://v1shnucs.com/projects/stock-forecasting-app
Code: https://github.com/v1shnucs/Stock-Forecasting-App

### Amazon Stock Forecasting with LSTM
Deep learning

A deep-learning notebook that forecasts Amazon’s (AMZN) closing price with an LSTM built in PyTorch.

Each training example is a sliding window of the previous seven closing prices, scaled to the range −1 to 1, and the network learns to predict the next day’s close. Training runs in mini-batches through a custom PyTorch Dataset and DataLoader.

Stack: Python, PyTorch, pandas, NumPy, scikit-learn, Matplotlib, Jupyter
Page: https://v1shnucs.com/projects/amazon-stock-lstm
Code: https://github.com/v1shnucs/Amazon-Stock-Forecasting-with-LSTM

### Yelp Clone
Full-stack

A restaurant review app modeled on Yelp, built on the PERN stack: PostgreSQL, Express, React and Node.js.

You can add, update and browse restaurants, open a restaurant’s detail page, and leave reviews with star ratings. The React client talks to an Express REST API backed by PostgreSQL.

Stack: React, Node.js, Express, PostgreSQL, JavaScript
Page: https://v1shnucs.com/projects/yelp-clone
Code: https://github.com/v1shnucs/Yelp-Clone

## Recognition

- Best Visualization Overall, Graduate/Alum Team, Plot-A-Thon · CSU Channel Islands (Feb 2026). Team 17 · $100 award
- AWS Academy Graduate: Cloud Architecting, AWS Academy (Dec 2024)
- Machine Learning, Stanford University · Coursera (Mar 2024). Grade 100%
- AWS Academy Graduate: MLU Machine Learning through Application, AWS Academy (Dec 2023)
- Winner, CSUCI Mission & AWS Hackathon, CSU Channel Islands (Sep 2023)
- Active member, Artificial Intelligence Club, CSU Channel Islands (Sep 2023 – Present)

## Skills

- Languages: Java, Python, TypeScript, JavaScript, C/C++, PHP, SQL
- Web: React, Next.js, Node.js, Express, NestJS, FastAPI, JSF / PrimeFaces, REST APIs
- AI / ML: PyTorch, TensorFlow / Keras, scikit-learn, LangChain, FAISS, Hugging Face, OpenAI API, Gemini API, Ollama, SageMaker
- Data & infra: PostgreSQL, MongoDB, Supabase, Docker, AWS, GCP, Vercel, Render, JBoss, Linux, Git, CI/CD
- Robotics: ROS, Intera SDK, Intel RealSense