Sai Deepa Kadaru profile photo

Hi, I'm Sai Deepa Kadaru

AI/ML Engineer with strong expertise in building intelligent systems using machine learning, deep learning, and reinforcement learning techniques.

AI/ML Engineer
Researcher
Published Author

My Projects

Production AI systems, research projects, and published work — each built to solve a real problem.

Publications

Peer-reviewed research in neuromorphic computing, reinforcement learning, and LLM-based game solvers.

Background

I recently completed my MS in Computer Science at Ohio University, where my thesis focuses on neuromorphic computing and spiking neural networks with the intersection of reinforcement learning, where I explore energy-efficient alternatives to traditional deep RL using biologically inspired hardware.

On the engineering side, I build production-grade AI systems: RAG pipelines, multi-agent orchestrators, LLM monitoring stacks, and backend APIs that actually ship. I care deeply about reliability, clarity, and systems that non-technical collaborators can operate without hand-holding.

Education

Ohio University · Athens, OH Aug 2023 – Dec 2026

Master of Science, Computer Science  ·  GPA: 3.7 / 4.0

Osmania University · Hyderabad, India Aug 2019 – Jul 2023

Bachelor of Engineering, Computer Science

Experience

Graduate Research Assistant · Ohio University Aug 2023 – Aug 2026
  • Designed & deployed end-to-end AI systems using LLMs, RAG pipelines, and agent frameworks on AWS.
  • Built and integrated AI systems with existing data infrastructure via REST APIs and microservices.
  • Debugged and optimized production AI pipelines, identifying failure modes and tuning retrievals.
  • Wrote modular, reusable Python code across LLM integration, vector search, and agent orchestration layers with clear documentation.
Programmer Analyst Intern · Cognizant Feb 2023 – Jul 2023
  • Automated backend QA workflows using Selenium and Java for enterprise clients, delivering production-ready automation that reduced manual testing effort measurably.
  • Documented testing methodologies, failure patterns, and resolution strategies for both client and internal teams.

Skills

AI Systems & Frameworks

LLMs, RAG Pipelines, Agentic AIMulti-Agent SystemsLangChain, LlamaIndex, Hugging FaceVector Databases (FAISS, Pinecone)OpenAI API, Embedding ModelsPrompt Engineering

Neuromorphic & RL Research

Reinforcement LearningSpiking Neural Networks (snnTorch, PyTorch)Deep Reinforcement LearningSurrogate Gradient LearningTransformers, CNNs, RNNs, LSTMsSpike Encodings & Energy Trade-offs

Engineering & Deployment

Python, Java, SQL, C++FastAPI, REST APIs, Spring BootDocker, CI/CD, GitHub ActionsAWSETL Pipelines

Blog Posts

Thoughts on AI engineering, neuromorphic computing, and building things that work in production.