I am driven by a passion for AI and software development along with data analytics, with a strong foundation in building scalable and secure applications. I thrive on innovative projects, leveraging technologies like machine learning, deep learning, natural language processing and the latest technological trend Agentic AI and Generative AI leveraging LLMs to solve complex challenges and build robust AI powered applications.
- Programming: Data Structures, Object-Oriented Programming.
- AI & ML: Machine Learning, Deep Learning, Natural Language Processing, Signal Processing.
- Systems: Operating Systems, Computer Networks, Linux.
Here are some of my projects:
QueryMind: Sql AI Agent
- Description: A Streamlit-based web interface for interacting with SQLite databases using natural language queries. Features include user authentication, chat session management, and a neon-themed UI with a cyberpunk aesthetic.
- Tech Stack: Python, Streamlit, SQLite, LangChain, bcrypt, CSS
User Wallet System
- Description: A secure user wallet application utilizing blockchain technology and data structures for robust cryptography. Implements SHA-256 for password hashing and features a user-friendly web interface for secure transactions.
- Tech Stack: Python, Flask, HTML, CSS, MySQL, DSA
RAG-based Knowledge Extraction for Material Science
- Description: Developed a domain-specific Retrieval-Augmented Generation model using MatSciBERT and LLaMA 3.1 for precise knowledge retrieval in material science, with a chatbot interface for seamless access to insights.
- Tech Stack: Python, Transformers, MatSciBERT, LLaMA 3.1
Emotion Classification on EEG Signals
- Description: Built a 7-emotion classifier using the EMO-DB dataset, achieving 93% accuracy with Variational Mode Decomposition and PyTorch-based deep learning models.
- Tech Stack: Python, PyTorch, Matlab
Data Analysis for Healthcare and Entertainment
- Description: Structured complex healthcare datasets and analyzed MovieLens data using SparkSQL and Scala, extracting actionable insights with visualizations.
- Tech Stack: MySQL, SparkSQL, Scala, Python
Design of High Entropy Alloys for High Temperature Applications using ML-driven Bayesian Optimization
- Details: Manuscript submitted to the 5th International Conference on Current Trends in Materials Science and Engineering (2025). Applied XGBoost, GPR, and Bayesian optimization to design high-performance HEAs, with advanced featurization and bootstrapping for uncertainty validation.
- Email: ashwindevan9@gmail.com
- LinkedIn: Connect with me
Feel free to contact and explore my repositories to see more of my personal work! and lets Build things Diffrent


