B.Tech in Electrical Engineering
Data Science · Cloud Engineering · Quantum Communication · Software Developement · Cryptography · Quantitative Finance & Business · Signal Processing
I’m an undergraduate at IIT Jodhpur, pursuing Electrical Engineering with a deep interest in how intelligence can be built, understood, and applied — across systems, signals, and society.
I love working on interdisciplinary problems that blend theory with engineering — whether it's training machine learning models from scratch, decoding brain signals, modeling credit risk, or building explainable AI systems for communication signals.
My curiosity spans across Signal Processing, AI/ML, Software Developement & system Design, Finance, Quantum Communication, and Cybersecurity — and I’m always excited to work on projects that challenge conventional thinking.
I'm currently open to remote internships and collaborative research roles, especially in areas like machine learning, applied AI, and emerging tech.
- Software Engineering & Competitive Programming (DSA, Algorithms, Problem Solving, System Design)
- Signal Processing & Communication (MATLAB, SDR)
- Quantum Information, Communication & Cryptography
- Quantitative Finance & Business Intelligence (Time Series, Risk Modeling, Market Microstructure)
- Data Science & Cloud Engineering (Machine Learning, Big Data, Scalable Pipelines)
| Project | Description | Stack |
|---|---|---|
| NeoGraphDB | In-memory graph database inspired by Neo4j, built for scalable, high-performance graph data management and flexible query-based operations | C++, Data Structures, OOP, Algorithms, Graph Databases |
| CreditScoreAI | Behavioral scoring model to predict credit card user risk profiles using transactional patterns | Python, Scikit-learn, Pandas, XGBoost |
| Music Genre Classifier | Music genre classification using GMM & ANN from scratch | NumPy, PyTorch |
| SignalSight | Dataset generation & classification of 20+ RF signals with explainable AI | MATLAB, Python, GNU Radio, PyTorch, GradCam |
Languages
Python, MATLAB, C++, SQL, Bash, LATEX
Frameworks & Libraries
PyTorch, Scikit-learn, Apache Spark, HuggingFace Transformers, XGBoost, NumPy, Pandas, Matplotlib, Seaborn, OpenCV
Infrastructure & Tools
Google Colab, Jupyter, Git, GitHub, Notion, VS Code, GNU Radio, ROS
Applied Concepts
Artificial Neural Networks (ANNs), Variational Autoencoders (VAEs), Gaussian Mixture Models (GMMs), Low-Rank Adaptation (LoRA), Retrieval-Augmented Generation (RAG), Signal Processing, SDR, GradCAM, MinHash & LSH, Quantum Information Theory, Time Series Forecasting, Risk Modeling
“Each day, the known intertwines with the unknown, forging the man I strive to become...”