Daksh Vashishtha — Aspiring AI & Software Engineer
Aspiring Software Developer and Machine Learning Engineer with a strong foundation in Data Structures, Algorithms, Machine Learning, and scalable full-stack development. Experienced in building AI-driven applications and collaborating within structured SDLC environments to deliver high-quality software solutions.
Andhra Pradesh, India · dakshvashishtha.16@gmail.com · +91 74281 56357
Projects
VibeUI — AI-powered UI Component Library
Technologies: React.js, FastAPI, LangChain, PostgreSQL, Firebase
- Standardized a React component library with brand-specific styles via NLP, increasing developer experience by 30%.
- Built a responsive dashboard enabling seamless brand on-boarding, component customization, and user-specific design workflows.
https://github.com/derangee/VibeUITarang — AI-based Calamity Detection & Alert System
Technologies: Next.js, FastAPI, Supabase
- Developed an AI-powered web platform for real-time calamity reporting using geo-tagged media with ML-based risk classification.
- Implemented automated zone-based alerting and disaster data ingestion from multiple public sources.
https://github.com/derangee/tarangNirbhay — Offline Women's Safety Network (MANET-based)
Technologies: Kotlin, Android SDK, FastAPI, Supabase, Google Cloud Run
- Architected an offline-first Android safety application using Mobile Ad-hoc Networks (MANET) to relay encrypted SOS signals device-to-device without internet connectivity.
- Implemented AI-based scream detection (YAMNet TFLite), fall detection, real-time GPS tracking, and a FastAPI backend deployed on Google Cloud Run with Supabase for multi-channel emergency alerts (Email + SMS) and risk scoring.
https://github.com/derangee/NirbhayWork Experience
Web Development Intern — Uniworld Studios Pvt. Ltd. (Jun 2025 – Aug 2025)
- Engineered and optimized JavaScript-based features to improve performance and scalability in client projects.
- Assisted in designing Entity-Relationship (ER) diagrams for 10+ entities and supported team tasks, improving efficiency.
- Collaborated within the Software Development Lifecycle (SDLC), ensuring adherence to best practices in coding, testing, and deployment for 2 client projects.
Machine Learning Research Intern — SRM University AP (May 2025 – Aug 2025)
- Evaluated 5 supervised ML classifiers on the Breast Cancer Wisconsin dataset (569 samples, 30 features).
- Built end-to-end ML pipelines with feature standardization, class balancing, and 5-fold stratified cross-validation, achieving ROC-AUC > 0.99.
- Benchmarked models using accuracy, F1-score, ROC curves, and confusion matrices, and deployed the best model using Joblib for reproducible inference.
Education
B.Tech, Computer Science & Engineering, SRM University, Andhra Pradesh (2023 – 2027) — CGPA 9.45 / 10.0
Relevant coursework: Data Structures & Algorithms, Object-Oriented Programming, Database Management, Machine Learning, Operating Systems, Computer Networks, Cloud Computing
Skills
- Programming Languages: C, C++, Python, Java, JavaScript, TypeScript, Kotlin
- Development Skills: Next.js, Node.js, FastAPI, TailwindCSS, WebSockets
- Databases: MongoDB, PostgreSQL, MySQL, Firebase, Supabase
- Developer Tools: Git & GitHub, Postman, Docker, Figma
- Libraries: PyTorch, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, Hugging Face
Achievements
- Received a 50% Merit Scholarship from SRM University AP for B.Tech in CSE.
- Associate in Norman Lab, Next Tech Lab — a QS award-winning multidisciplinary innovation lab.
- Tech Head of Google Developers Group (GDG) SRMAP, leading a 50+ member student community.
- 1st place in <Hack x MSC> Hackathon, 3rd place in 9-Hacks Hackathon, and qualified for the Internal Round of Smart India Hackathon (SIH) 2024.
Links