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Hello, I'm Naveen, a passionate computer scientist specializing in Intelligent Systems. I'm currently pursuing a Master of Science in Computer Science at The University of Texas - Dallas building upon my strong educational foundation from the Indian Institute of Technology Madras (IIT-M), where I earned a Bachelor + Master of Technology degree in Mechanical Engineering with a Minor in Artificial Intelligence and Machine Learning.

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My experience

AI Engineer

Kahana Inc Group

Engineered a LangChain-based generative AI assistant, integrating it with backend services to enable natural language commands, which improved user workflow efficiency by 25%.
Developed and deployed scalable RESTful APIs for real-time data analytics, supporting a product strategy pivot that led to a 16% increase in subscription revenue.
Built and maintained full-stack UI/UX features using React.js and FastAPI, creating a highly responsive interface that improved user engagement by 12%.

Feb 2025 - Present

Software Engineer

Quantitative Brokers

Automated code quality and security analysis by integrating SonarQube and BlackDuck into a Jenkins CI/CD pipeline, reducing critical vulnerabilities in production by 20%.
Engineered a low-latency, high-throughput backend messaging system for real-time financial data processing, which eliminated manual processes and streamlined core operations.
Enhanced a core messaging platform to support complex data structures (Multi-Leg orders), which boosted operational efficiency by 15% and expanded product capabilities.
Optimized decentralized PostgreSQL database solutions for high-performance trading applications, reducing query latency by 10% to support real-time data access.

Jun 2021 - Jun 2023

Machine Learning Engineer - Intern

Big Data Science Research

Developed and deployed a machine learning pipeline using Python and scikit-learn to predict urban traffic patterns, enhancing model accuracy by 15% through the integration of geospatial data features.
Implemented a novel map-matching algorithm to refine GPS data, significantly improving the precision of traffic flow models and reducing prediction error by 20%.

Apr 2020 - Jun 2020

Machine Learning Engineer - Intern

Alphabt & TVS Motors Ltd

Designed and deployed an end-to-end computer vision system on the assembly line using OpenCV and TensorFlow, improving manufacturing validation accuracy by 3%.
Trained and optimized a custom CNN model for text engraving recognition, achieving 99% accuracy and enhancing the automated quality control process.

May 2019 - Jun 2019

My projects

Personal Assistant Bot

Made with:

Fine-tuned the Mistral LLM with QLora on a custom dataset to build a specialized and efficient personal assistant bot. Integrated a Retrieval-Augmented Generation (RAG) pipeline to query personal documents, ensuring precise answers.

GitHub

LLM-Powered Mac Automation Tool

Made with:

Developed a LangChain system for LLM Mac control, replicating core functionalities of Anthropic's Computer Control. Implemented tools for text simulation, mouse automation, image analysis, application management & web navigation.

GitHub

AI-Powered SQL Injection Detection System

Made with:

Developed a secure PHP-based web system with login, access control, and DistilBERT-powered SQL injection prevention. Achieved 99% detection accuracy using supervised fine-tuned LLMs; performed log analysis and penetration testing with SQLMap. Hardened the system using input sanitization, HTTPS setup, Apache WAF simulation, and prepared statements for robust security.

GitHub

BrainScanNet: MRI-Based Brain Tumor Detection with CNNs

Made with:

Built a CNN-based classification pipeline using VGG-16 and DenseNet to detect brain tumors from cropped MRI images. Preprocessed data via cropping and augmentation; VGG-16 model achieved highest accuracy among tested architectures. Designed an assistive tool aimed at enhancing radiologist efficiency and diagnostic consistency in tumor identification.

GitHub

Trajectory-Aware Human Feedback for Hierarchical RL

Made with:

Proposed a novel Hierarchical Reinforcement Learning framework to improve subgoal generation in complex tasks. Deployed the Deep-RL framework in the FetchReach environment, resulting in a 10% increase in task success rates

GitHub

Chatbot

Made with:

Built comprehensive knowledge base by web scraping & advanced NLP techniques enabling efficient data retrieval. Engineered an LSTM-based model with an attention mechanism, improving response relevance and context by 25%

GitHub

Surface Texture Analysis

Made with:

Systemized an approach in identifying machined surface textures with CV & ML techniques, achieved 99.6% accuracy. Built Neural Network employing statistical features from GLCM for texture classification improving accuracy by 44%

GitHub

Analysis of Optimization Algorithms

Made with:

Assessed the performance of various Stochastic Optimization algorithms on control agents created using OpenAI gym environment. Developed and applied multiple Gradient Descent algorithms to optimize Deep Q-Network which achieved a 15% boost in agent’s return

GitHub

Multi Agent Cricket Game - Reinforcement Learning

Made with:

Formulated cricket game as Markov Decision Process for optimal decision-making of actions in dynamic system. Modeled a 2-player Monte Carlo Tree Search algorithm for better action selection which elevated match outcomes

GitHub

Hangman Game

Made with:

Designed an algorithm for Hangman game where player has to guess letters of a word with limited number of guesses. Augmented N-gram language model for capturing letter patterns to improve prediction & achieved an accuracy of 62%

GitHub

Bike Tour Recommendation

Made with:

Optimized bike tour recommendations through exhaustive data preprocessing, data binning and feature engineering. Drafted an ensemble of XGB, LGBM and CatBoost with meticulous hyper-parameter tuning yielding a 0.71 accuracy

GitHub

Loan Default Prediction

Made with:

Developed loan default classifier using SMOTE and KNN Imputer for data pre-processing, achieving robust predictive accuracy. Achieved F1 score of 0.95 by rigorously tuning hyperparameters in Random Forest Classifier, significantly enhancing learning outcomes

GitHub

DIC’s Terrace Farming Robot

Made with:

Won Silver prize in DIC's Terrace Farming Robot for hilly areas challenge in Inter IIT Tech Meet among over 20+ teams. Designed an Autonomous agricultural robot that is capable of ploughing, seeding and harvesting by climbing up and down steps in hills. Programmed the bot with Arduino to follow the wall by a PID control system (Proportional-Integral-Derivative) using ultrasonic sensors

Unmanned Ground Vehicle

Made with:

Developed a program for UGV bot using ROS that transmits sensor & video feed to a remote system and tracked its path in the given map. Programmed the bot to create a 3D map of surrounding using kinect-360 and localize itself in the given map by Monte Carlo Localization

GitHub

Water Levitation Project

Made with:

Developed a program to control frequency of strobe lights and water pumps for levitating the water using the principle of Stroboscopic effect. Designed a PCB (Printed Circuit Board) using Eagle and fabricated the circuit along with Arduino to control pumps & lights to make patterns