Curriculum Vitae

Profile

Machine Learning Engineer working on Large Language Models, with a focus on interpretability and AI safety. My work includes building Retrieval-Augmented Generation and knowledge-guided NLP systems, along with three IEEE publications and experience designing and evaluating LLM-driven applications. I aim to develop intelligent and reliable systems that translate research into responsible real-world use. Alongside technical work, I have led professionals across corporate Toastmasters clubs, strengthening my communication and collaborative skills.

Technical Skills

• Core: Data Structures & Algorithms, Software Engineering, Agile Software Development
• AI/ML: Machine Learning, Deep Learning, NLP, RAG Systems
• Languages: Java, Python, C++, C
• Tools/Tech: TensorFlow, SQL

Education

• B.Tech in Computer Science and Engineering (Sept 2021 - July 2025)
  • Amrita Vishwa Vidyapeetham University
    • CGPA: 8.65, First Class with Distinction.
• Exchange Program (Feb 2025 - July 2025)
  • University of Twente
    • Conducted research on utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to generate engaging historical narratives.
    • Evaluated Semantic, Hybrid, and Graph-Based RAG approaches to optimize narrative coherence and mitigate hallucinations.

Professional Experience

• Standard Chartered
  • Apprentice- Technology (Sept 2024 - Present)
    • Worked on building an internal Retail & Wealth Banking (RW) Tool enabling admins to approve subscriber requests and operations teams to fetch reports, built using React and Spring Boot.
    • Designed and integrated PostgreSQL database schemas to support efficient data retrieval.

Publications & Projects

• Weaving Stories: using LLMs to generate historical narratives (Feb 2025 - July 2025)
  • Engineered a Beyond-Vanilla RAG system using a custom Knowledge Graph (NetworkX/GML) and Hybrid Semantic Search (FAISS) to enable multi-hop reasoning over historical narratives.
  • Developed sophisticated Memory Orchestration pipelines including entity-centric query expansion and NLP-driven topic extraction to provide high-quality, long-context awareness to Gemini 1.5 Pro.
  • Optimized the intersection of Structured Memory (Knowledge Graphs) and Unstructured Data to improve narrative faithfulness and reduce hallucinations in streaming LLM environments.
• Parkinson’s Disease Diagnosis from Patients Speech Analysis (IEEE) (Oct 2023 - Dec 2023)
  • Achieved 95% diagnostic accuracy using Random Forest and XGBoost, utilizing SHAP to identify the top 6 most influential features.
• Deep Learning-Based Analysis of Pediatric Pneumonia Detection in Children using Fine-tuned NasNetMobile Model (IEEE) (Mar 2024 - May 2024)
  • Achieved a 92% F-score in pediatric pneumonia detection by fine-tuning a NasNetMobile CNN architecture with Mish activation on a dataset of over 5,000 chest X-rays.
• Comparative Image Analysis of Chest X-RAY Image Encryption using Symmetric and Asymmetric Key Encryption Algorithms (IEEE) (Mar 2024 - May 2024)
  • Identified AES with RSA as the optimal multilayer encryption strategy for medical images, delivering the best decryption speed while guaranteeing Confidentiality, Integrity, and Authentication (CIA).

(For a detailed view of my work, please visit my Publications page.)

Leadership & Experience

• Toastmasters International
  • Area G3 Director (July 2024 - June 2025)
    • Served five corporate clubs with ~130 professionals and leaders across the industry.
    • Achieved 100% club retention, and Select Distinguished Status.
  • Organized Feb 2024 Leadership Conclave with a team of four, over the course of three months, securing a keynote address and two executive-led panel discussions in a corporate venue. (2023-24)
  • Revitalized an underperforming club through targeted strategic planning. (2023-24)