I'm a Computer Science student at the University of California, Davis, with a passion for machine learning, sports analytics, and software development. Expected graduation: June 2027.
- 🏫 GPA: 3.60/4.0
- 🏆 Dean's Honor List
- 🚀 prev. Systems Engineering Intern @ Nothrop Grumman
- 📊 Machine Learning Researcher @ LARA
- 🏀 Software Engineer @ Aggie Sports Analytics
- 🚀 Vice President of Engineering @ Product Space
- 🌐 Marketing Director @ HackDavis
- 🌐 Former Marketing Director @ Google Developer Student Club
• Built a RAG-based conversational agent using LangChain and FAISS to provide real-time fantasy sports advice, creating a robust retrieval pipeline that reduces hallucination by anchoring responses in live news and injury reports. • Engineered a low-latency Streamlit frontend coupled with time-series forecasting (Statsmodels ARIMA) on 5+ seasons of NBA and NFL data to project player performance trends. • Deployed the application to a user base of 30+ active monthly users and conducted A/B testing with 50+ beta testers to refine the recommendation algorithm based on user feedback. • Awarded 1st Place in the Winter 2024 ASA Case Competition for innovation in data-driven UI and AI integration.
• Developed a full-stack web application capable of classifying brain MRI scans into four tumor types (glioma, meningioma, pituitary, healthy) using a TensorFlow/Keras CNN deployed via a RESTful Flask API. • Engineered a modular React frontend featuring drag-and-drop MRI upload, color-coded prediction visualization, and secure user authentication/persistence using Supabase. • Integrated Google Gemini API to generate personalized, context-aware treatment recommendations based on patient vitals. • Authored a technical research report and conducted user testing with 15 American Cancer Society club members, validating the tool’s utility for educational and preliminary diagnostic contexts
• Developed a full-stack web application using Flask to serve a REST API with React as the frontend. • Implemented a mock draft board that streams live player updates and information. • Leveraged historical draft patterns, player biometrics, current league data, and Twitter sentiment analysis to build an interactive UI showing player rankings and projected draft slots. • Scraped NBA.com and prospect sites to create clean CSV datasets for ML preprocessing.
• Conducted surveys and user interviews with 55 + UC Davis students during the SacHacks hackathon to validate pain points around degree tracking and course similarity. • Built a TF-IDF + cosine-similarity pipeline in Scikit-learn to recommend courses based on semantic similarity of descriptions and degree requirements. • Developed a Schedule Builder–style React/Next.js frontend that displays personalized course suggestions, real-time unit tracking, waitlist status, and core/GE requirement fulfillment. • Integrated backend APIs (Flask/FastAPI) with Supabase for storing user histories and MyDegree/OASIS data aggregation, enabling end-to-end personalized scheduling. • Ran usability tests on early UCD students cohorts—iterated on UI flow and info hierarchy based on System Usability Scale feedback, achieving a 4.2/5 overall satisfaction score
• Led a cross-functional squad of 5 (UX, backend, data) to deliver a player-development dashboard for UC Davis Badminton Club, driving a 15% increase in match win rates and logging 30 + daily user interactions • Ran 12 targeted user interviews, synthesized findings into prioritized roadmaps in Jira/Kanban, and built two high-fidelity A/B prototypes on Figma and tested with 10 beta users on a ngrok public localhost server—iterating weekly on features • Integrated performance data ingestion from Yolov8 CV models (shuttlecock and pose detection) to auto-generate player insights and weekly progress reports
• Mobile FinTech & GenAI (Divvit Project): [React Native, TypeScript, Gemini API, Supabase] Architected a cross-platform bill-splitting app. Engineered a multimodal pipeline using Gemini API to parse physical receipts into itemized digital objects. Implemented algorithmic tax/tip distribution and Venmo/CashApp deep-linking for seamless P2P transaction settlement.
- Advanced machine learning techniques
- Full-stack web development
- Sports analytics and data visualization
- Email: [email protected]
- LinkedIn: linkedin.com/in/raquib-alam
- Phone: (858) 943-1836
- Contribute to open-source machine learning projects
- Develop more sports analytical projects through computer vision (Utilzing YoloV8)
- Publish a research paper in AI/ML
- Secure an internship in software engineering or data science
⭐️ From raquibalam