B-Tech in Computer Science and Engineering | Specializing in AI & Data Analytics
I am a highly motivated engineering student with a robust theoretical and practical foundation in Machine Learning, Deep Learning, and Natural Language Processing (NLP). My passion lies in leveraging cutting-edge AI technologies—specifically Transformer-based models and OCR systems—to solve complex business problems and enable multilingual support.
- 🎓 Education: Currently pursuing B-Tech in CSE (Artificial Intelligence and Data Analytics) at Sri Ramachandra Faculty of Engineering and Technology, Chennai.
- 📈 Academic Standing: Current CGPA of 9.65 (Expected Graduation: May 2027).
- 🏆 Recognition: Recipient of the Chancellor's Cash Prize Award (2023) for achieving the highest marks in university examinations.
- 💡 Interests: I am eager to apply analytical skills to building intelligent systems, ranging from scientific simulations to advanced recommendation engines.
| Category | Skills |
|---|---|
| Languages | Python, Java, JavaScript, HTML, CSS, SQL (MySQL) |
| AI & ML Frameworks | TensorFlow, PyTorch, Pandas, Gensim, Scikit-learn (implied by PCA/ML) |
| Web Development | Node.js, Express.js, Flask, Tailwind CSS, React (implied context) |
| Tools & Platforms | VS Code, GitHub, Google Colab, IntelliJ, Notion, Tableau, MS Excel |
| Core Concepts | Deep Learning, NLP, Text Analytics, Data Mining, Unix Commands |
A sophisticated system for extracting and summarizing insights from unstructured academic documents.
- Overview: Developed an end-to-end pipeline integrating Tesseract OCR for text extraction and Hugging Face Transformers (LLMs) for natural language understanding.
- Key Features:
- Named Entity Recognition (NER): Precise extraction of critical entities from text.
- Keyword Ranking: Utilized TF-IDF to identify relevant keywords.
- Automated Summarization: Generates key insights to reduce manual review time.
- Tech Stack: Python, OCR, LLMs, NLP techniques.
Research-driven project focused on optimizing Collaborative Filtering systems.
- Overview: Conducted a comparative study to benchmark the impact of Principal Component Analysis (PCA) on recommendation accuracy and efficiency.
- Impact: ADDRESSED challenges of data sparsity and scalability in E-commerce by applying dimensionality reduction to large-scale datasets.
- Methodology: Designed experiments for explicit rating prediction and Top-N recommendation list generation using real-life customer purchase data.
- Achievement: Won First Prize at Research Day 2025 for this work.
An interactive educational tool bridging physics and web development.
- Overview: A web-based simulation demonstrating complex physics concepts like conservation of momentum and energy.
- Key Features:
- Real-time user controls for adjusting pendulum count and impact speed.
- Frame-by-frame CSS animations for realistic motion physics.
- Tech Stack: HTML, CSS, JavaScript.
- 🥇 First Prize, Research Day 2025: Awarded for the paper "Enhancing Recommender System Performance with Principal Component Analysis," showcasing expertise in Dimensionality Reduction.
- 🗣️ Special Mention, TechExpo 2025: Recognized in the Technical Debate competition for critical thinking and articulating complex technical arguments.
- 🎓 Chancellor's Cash Prize (2023): Academic excellence award for topping university examinations.
I am open to collaborations on AI/ML projects and data analytics challenges.
- 📧 Email: jaswantraj150@gmail.com
- 💼 LinkedIn: linkedin.com/in/jaswantrajgv
- 📱 Phone: +91 86108 29053