I am an AI researcher and engineer focused on making AI systems reliable, efficient, and accessible. My work
spans in-context learning, AI system evaluation, and language model authoring and training. My goal is to
enable
deploying high-quality AI systems across all industries, not just tech. Most of my work is open source and
available on my GitHub.
I will join CMU SCS as a PhD student in August 2026, where my research will focus on
self-improving AI systems and AI for software engineering (AI4SE).
I am currently a Member of Technical Staff (Research Engineer) at Unconventional AI. Previously, I spent
7+ years at Google and Databricks, working mainly on open source projects, including Keras, DSPy, and MLflow.
Research Interests
- Self-improving AI systems: Systems that learn from their own traces and feedback,
including automatic prompt optimization, self-refinement loops, and continual improvement of compound AI
pipelines with minimal human supervision.
- AI for software engineering (AI4SE): Reliable AI systems for real-world software
engineering tasks, including code generation, debugging, refactoring, and end-to-end agentic development.
- AI system evaluation: Benchmarks and evaluation frameworks for domain-specific
applications (hardware design, scientific reasoning, finance), with a goal of minimizing human effort during
the evaluation process.
- Compound AI systems: Architecture for AI agents and enhancing retrieval quality in AI
systems.
- Efficient training and inference: Reducing communication overhead in distributed systems
and new model/layer architectures for computational efficiency.
Work Experience
Carnegie Mellon University - PhD Student (Incoming)
August 2026 -
Joining CMU as a PhD student. Research focus on self-improving AI systems and AI for software
engineering (AI4SE).
Unconventional AI - Member of Technical Staff (Research Engineer)
2026 - Present
Working on the next generation of AI systems at Unconventional AI.
Databricks - AI Engineer
July 2023 - 2026
Worked on DSPy and MLflow in the AI Open Source team. Co-led the development of DSPy 3 as primary
maintainer. Integrated DSPy into Databricks AI products like agent bricks. Led MLflow improvements for deep
learning workflows, including large-experiments compatibility and system metrics. Migrated all Databricks
training workloads from Weights & Biases to MLflow.
Google - Machine Learning Engineer
January 2021 - July 2023
Worked on the Keras team. Founding engineer of Keras 3, unifying multi-backend API across TensorFlow, PyTorch,
and JAX. Founding engineer of KerasNLP (rebranded to KerasHub in 2024). Led Keras optimizer rewriting and
migrated Google's entire Keras optimizer codebase to the new optimizer.
Google - Backend Engineer
August 2018 - January 2021
Worked on Google Local Services Ads team. Led the effort of phone/message support for i18n. Led the effort of
smart geo targeting.