I am an AI Engineer and Full-Stack Developer bridging the gap between complex data and actionable intelligence. I specialize in building secure LLMs, reinforcement learning models, and scalable microservices.
I'm a Computer Engineering student at NMIMS (MPSTME) with a relentless drive to solve difficult problems. My journey began with simple scripts and has evolved into architecting Enterprise-grade AI systems.
I focus on building complete ecosystems—from the Big Data pipelines that process information to the Mobile interfaces users interact with.
2020 - Present
B.Tech Integrated (Computer Engineering)
MPSTME, NMIMS University.
2024 - 2025
Machine Learning Research
Developed "PromptFence" (LLM Security) and "CitizenSafe" (Smart Policing) focusing on multimodal AI and safety guardrails.
2024
Big Data Analytics
Engineered a Supply Chain Analytics platform using Apache Hive and Hadoop. Processed large-scale datasets to optimize logistics and visualize risk.
2023
Mobile App & AI Development
Built NutriTrack, a diet recommendation mobile app. Personalizes meal plans based on user health metrics, AI scanner to determine nutritional value.
2023
Full Stack Architecture
Designed a Travel Itinerary Generator using Spring Boot Microservices. Handled complex role-based auth and booking transactions.
02. Technical Arsenal
AI & Machine Learning
TensorFlow & PyTorch
LLMs (BERT, GPT)
Computer Vision (OpenCV)
Reinforcement Learning
NLP & Sentiment Analysis
Languages & Core
Python (Expert)
Java
SQL (MySQL, PostgreSQL)
JavaScript (ES6+)
HiveQL
Backend & Data
Spring Boot (Microservices)
Big Data (Hadoop, Hive)
AWS & Google Cloud
RESTful APIs
Docker & Kubernetes
Web & Tools
React & React Native
Git & GitHub
UiPath (RPA)
Tableau
Linux/Unix
03.Showcased Projects
Capstone Research
CitizenSafe: AI Crime Analytics
A comprehensive proactive policing framework. Features Spatiotemporal Crime Prediction, real-time Voice Sentiment Analysis for emergency calls, and Fake Report Detection using NLP. Integrated into a React Native app.
Python
TensorFlow
BERT
GCP
React Native
Cybersecurity & AI
PromptFence
A semantic security guardrail for Healthcare LLMs. Defends against Prompt Injection Attacks by using contrastive fine-tuning on BERT embeddings to detect malicious intent with 92% accuracy.
LLM Security
Contrastive Learning
BERT
Python
Reinforcement Learning
Dynamic Pricing Engine
An intelligent pricing system for retail. Combines Supervised Learning (CatBoost) for demand forecasting with Reinforcement Learning (DQN, DDPG) to optimize revenue dynamically based on market conditions.
Reinforcement Learning
CatBoost
Pandas
Scikit-Learn
Other Noteworthy Projects
Automated Receipt Processor
Serverless pipeline using AWS Lambda, Textract, and SES to extract financial data from emails automatically.
AWS Lambda
Textract
Python
Supply Chain Big Data
Analyzed the DataCo dataset using Apache Hive (Hadoop) to optimize logistics and detect shipping fraud.
HiveQL
Hadoop
HDFS
Travel Microservices
A distributed backend for travel planning. Handles User Auth, Itineraries, and Bookings via REST APIs.
Java
Spring Boot
Microservices
RPA Movie Classifier
Automated bot using UiPath and AI Center to classify movie review sentiment from Excel sheets.
UiPath
AI Center
Automation
NutriTrack
A diet recommendation mobile app. Personalizes meal plans based on user health metrics, AI scanner to determine nutritional value.
Python
Scikit-Learn
Streamlit
04. Publications & Research
PromptFence: A Semantic Guardrail for Healthcare AI
IEEE Format • Cybersecurity & AI
Defending Large Language Models against prompt injection attacks using BERT-based contrastive fine-tuning.
I am actively seeking opportunities in AI Engineering and Data Science. Whether you have a question about my research or just want to say hi, my inbox is open.