Amit Raj Reddy Dharam

About Me

I'm Amit Raj Reddy Dharam, a Computer Science Master's student at Arizona State University, graduating in May 2026. My coding journey began during my undergrad at BITS Pilani, where I pursued a dual degree in Computer Science and Mathematics. It was there that I discovered my passion for machine learning and AI, diving deep into data structures in C/C++, object-oriented programming in Java, and eventually deep learning with Python.

Over the past few years, I've evolved from writing my first "Hello World" to building production ML systems, winning hackathons, and working as a Machine Learning Engineer at TELUS Digital. Today, I am focused on cloud computing, GenAI applications, and creating AI-powered solutions that make a real impact.

Hobbies & Interests

Hackathon enthusiast: I love the thrill of building projects under pressure and have won multiple competitions including Sunhacks 2025 and InnovationHacks 2025
Tinkering with AI projects: from personal smart assistants to computer vision applications
Cloud computing: deploying scalable systems on AWS
Continuous learner: always exploring new ML frameworks, tools, and techniques
Open source contributor: giving back to the community and collaborating on projects that matter
ASU sports fan: catching Sun Devil games when I can
Watching anime when not debugging: convinced that the One Piece is real!!

Get In Touch

Email

reddy.amitraj@gmail.com

Location

Tempe, Arizona, USA

Resume

View my resume to learn more about my experience, skills, and accomplishments.

View Resume

Education

Arizona State University

August 2024 – May 2026

Masters in Computer Science

GPA: 4.00/4.00

Relevant Courses

Artificial Intelligence Statistical Machine Learning Data Mining Cloud Computing Natural Language Processing

BITS Pilani, Hyderabad Campus

August 2018 – July 2023

Dual Degree: B.E. in Computer Science and M.Sc. in Mathematics

Relevant Courses

Data Structures and Algorithms (C/C++) Object Oriented Programming (JAVA) Machine Learning and Deep Learning (Python) Database Management Systems (SQL) Computer Networks

Experience

AI Data Science Analyst (Part-Time)

September 2024 - June 2025

Enterprise Technology at Arizona State University

Key Achievements

Implemented the backend for a NL2SQL conversational agent using Python, FastAPI allowing users to query, filter and display data from multi-table databases using conversational inputs, with query execution accuracy over 85%
Optimized natural language to SQL module responses by incorporating team lead and engineer feedback into prompt engineering, fine-tuned LLMs, and GraphRAG implementation, leading in a 5% increase in accuracy
Integrated LangChain for fast orchestration and Neo4j for efficient semantic search using embeddings; utilized AWS EKS for scalable inference; and reduced response time by 30% over 100+ questions per session

Software Development Engineer 1 - Machine Learning

July 2023 - June 2024

Telus International AI CV

Key Achievements

Instruction-tuned open-source LLMs with PyTorch on scientific topics using PEFT-based methods for synthetic data creation using a RAG pipeline. Increased manual question generation throughput by 50%, reducing generation time by 40%
Evaluated a custom trained 3D object detection (Voxel-based) and tracking models(DeepSORT) on the KITTI benchmark, achieving around 90% precision for object detection and 70% MOTA (Multi Object Tracking Accuracy) for tracking
Mentored an intern to test the LLM against conventional NLP benchmarks (MATH, MMLU) and internal domain-specific datasets, achieving a +6% improvement in benchmark scores and 50% faster evaluation timeframes

Software Development Engineer Intern - Machine Learning

August 2022 - July 2024

Telus International AI CV

Key Achievements

Prototyped DeepSORT and ByteTrack algorithms for bounding box tracking over video sequences resulted in 80% mAP object recognition and 75% IDF1 multi-object tracking accuracy, as confirmed against MOT17 benchmarks
Improved image segmentation precision by 23% across 15,000+ annotated frames by uptraining U-Net and Mask R-CNN architectures using the CityScapes dataset, reducing manual annotation time from 8 hours to 5 hours per dataset batch
Deployed ML APIs serving 15+ active projects with sub-200 ms response times by establishing FastAPI and TorchServe endpoints, containerizing the segmentation models with Docker, and hosting on AWS EC2 with JWT authentication

Projects

Hackathon Winners & Academic Projects

Accio (GraphRAG based Chat Agent)

Semantic web mining project, Nov 2025

Technologies

Python streamlit Neo4j Docling FastAPI Hugging Face Google Gemini LLM Docker GitHub

Key Features

A simplified PDF knowledge extraction and Q&A chatbot system for college demo. Extracts knowledge from pre-ingested company PDFs, builds a Neo4j knowledge graph with vector embeddings, and provides a Streamlit chat interface with grounded citations

H1b wage Viewer (Interactive Dashboard)

Personal project, Nov 2025

Technologies

Python streamlit Plotly GitHub-copilot GitHub

Key Features

An interactive Streamlit dashboard that visualizes H1B prevailing wage data across US geographical regions with filtering capabilities for job roles and wage levels.

WardrobeAI (Reccomendations and Image Generation)

Winner Sunhacks, Sept 2025

Technologies

Python Next.js React NLP FastAPI MongoDB Google Vertex AI Amazon Web Services Google Cloud Platform GitHub

Key Features

Built a Python backend that integrates with MongoDB and AWS S3, linking Gemini chat API and Gemini Nano-Banana models across 5+ microservices to provide virtual try-ons and outfit recommendations for over 3000 clothing items
Coordinated a 4-person team to architect and deploy a LinUCB based recommendation engine with conversational chatbot, generating personalized outfit suggestions for 10+ occasions like birthdays, weddings etc

Tom-Riddle's Diary (AI Chatbot agent)

Winner - InnovationHacks 2025

Technologies

Python MCP-Chroma NLP FastAPI ChromaDB CrewAI Git Google Cloud Platform

Key Features

Engineered and integrated a python, FastAPI backend using ChromaDB to enable long-term semantic memory and efficient information retrieval, reducing response time by 35% and supporting contextual AI reflections
Integrated Google Gemini LLMs into a conversational backend pipeline, enabling natural language queries and persona based tone generation handling over 1,000 personalized interactions with >90% response relevance

Social Impact & Volunteer Projects

Neurologic Music Therapy Services of Arizona

Opportunity Hack Fall 2025

Technologies

Next.js React Typescript TailwindCSS Sanity.io Vercel GitHub-copilot GitHub

Key Features

Our team was inspired by NMTSA mission to make music therapy accessible to everyone in the community. We noticed that their existing site could be more engaging, modern, simpler to work with, and easier to maintain. We wanted to create a new digital experience that reflects the heart of NMTSA as a place of compassion, creativity, and connection through music.

Heritage Square Foundation - Phoenix, Arizona

Opportunity Hack Summer 2025

Technologies

Python LangChain Google Cloud Platform FastAPI React FAISS GitHub

Key Features

Our team developed an AI agent with Google Drive using Python, Langchain and RAG to assist in document organization, tagging, and retrieval. Implementing AI-driven document categorization, suggesting reorganization strategies, for enhanced prompting capabilities. The nonprofit organization we developed for is Heritage Square Foundation.

Vizards (Natural language Query agent)

Opportunity Hack Fall 2024

Technologies

Python Ollama Pandas Flask NLP GitHub AWS

Key Features

Programmed the backend of a nonprofit-focused CRM using Flask and MySQL, integrating surveys, Excel uploads, and manual inputs into a unified system, reducing data silos and improving internal data consistency by 30%
Developed RESTful APIs and incorporated a small language model (SLM) query agent, allowing non-technical users to query data in real time, reducing dependency on manual SQL lookups, and increasing data accessibility by 40%

Technical Skills

Languages and Technologies

Python JAVA JavaScript TypeScript GO C C++ C# HTML Flask FastAPI PostgreSQL MongoDB Neo4j ChromaDB

ML Frameworks and Libraries

PyTorch TensorFlow Pandas PySpark Scikit-Learn NumPy Matplotlib Open3D OpenCV XGBoost

Natural Language Processing (NLP)

Hugging Face Transformers LangChain CrewAI OpenAI/OpenRouter APIs FastText FAISS Google Agent Development Kit (ADK)

Cloud and Developer Tools

Amazon Web Services (AWS) Google Cloud Platform (GCP) Microsoft Azure Docker Kubernetes Grafana Terraform Github Copilot Cursor GitHub

Proficiency Areas

Backend Development Machine Learning Data Engineering AI Engineering Cloud development and deployment