About
Highly accomplished AI Director and Technical Leader with a Ph.D. in Neuroscience, specializing in full-stack AI product development, large language models, and advanced machine learning. Proven ability to lead cross-functional engineering teams, drive innovation, and translate complex research into high-impact, compliant solutions, as demonstrated by a 40% increase in feature adoption and significant efficiency gains.
Work
Houston, TX, US
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Summary
Spearheaded full-stack AI product development and strategic AI integration for hazardous waste profiling, leading a team of engineers and fostering an AI-first culture.
Highlights
Developed and deployed full-stack AI products, leveraging agentic workflows, fine-tuned LLMs, and web-crawling tools to ensure customer compliance with federal hazardous waste regulations.
Managed a cross-functional team of AI engineers and software developers, successfully delivering key roadmap features and enhancing product capabilities.
Championed and integrated an AI-first culture across WasteLinq, identifying and implementing AI solutions to significantly improve operational efficiency and drive innovation.
Initiated a comprehensive documentation culture, standardizing company philosophy and technical design to enhance organizational clarity and efficiency.
Drove customer-centric product development through continuous interviews and live iteration sessions, ensuring product-market fit and user satisfaction.
Chicago, IL, US
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Summary
Co-founded and led technical strategy for an AI startup, driving product innovation, achieving 40% feature adoption increase, and securing accelerator recognition.
Highlights
Secured selection into the prestigious Techstars’23 accelerator, gaining critical industry insights and validating the startup's potential.
Drove product innovation by conducting extensive AI literature reviews, leading to development decisions that boosted feature adoption rates by 40% and established a competitive market advantage.
Engineered and launched an AWS-based video generation pipeline, slashing video production time by over 97% (from 48 hours to under 1 hour per project) and accelerating content delivery.
Developed and deployed advanced AI models, including fine-tuned LLMs, Diffusion models, custom LORAs, and bespoke video generation pipelines, leveraging state-of-the-art image and video technologies.
Chapel Hill, NC, US
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Summary
Conducted advanced neuroscience research, developing novel ML models and large-scale data processing pipelines for medical imaging and Alzheimer's disease.
Highlights
Authored and published research in four peer-reviewed journals, contributing significant findings to the neuroscience and AI communities.
Developed and trained machine learning models using medical imaging data to accurately predict Alzheimer's disease progression and sub-types.
Pioneered the application of Natural Language Processing (NLP) to natural language data, exploring its potential for early Alzheimer's disease diagnosis.
Designed and implemented large-scale pipelines for the pre-processing and analysis of medical imaging datasets, optimizing research workflows and facilitating downstream analysis.
Richardson, TX, US
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Summary
Contributed to groundbreaking genome editing research, engineering viral vectors and gaining extensive laboratory experience, resulting in a highly cited publication.
Highlights
Engineered a novel AAV-based viral vector for genome editing, leading to a publication recognized by the scientific community with over 80 citations.
Developed comprehensive laboratory expertise, including cell-culture techniques, animal handling, plasmid construction, and critical data analysis and interpretation skills.
Education
Publications
A robust core architecture of functional brain networks supports topological resilience and cognitive performance in middle-and old-aged adults.
Published by
Proceedings of the National Academy of Sciences
Summary
Research on the core architecture of functional brain networks and its role in resilience and cognitive performance in aging adults.
The development of an AAV-based CRISPR SaCas9 genome editing system that can be delivered to neurons in vivo and regulated via doxycycline and Cre-recombinase.
Published by
Frontiers in Molecular Neuroscience
Summary
Development of an AAV-based CRISPR SaCas9 system for in vivo neuronal genome editing with regulatable expression.
Skills
Languages
Python, SQL, JavaScript, HTML, Typescript, BAML.
DL Models
Transformer, LLM, RAG, Agents, Diffusion Models, Knowledge Graphs.
Soft Skills
Technical Leadership, Product Leadership, Self-Learner, Scientific Writing, Team Management, Strategic Planning, Customer-Centric Design, Innovation, Problem-Solving, Data Analysis, Research.
Platforms
AWS, Vertex AI, Azure, Docker, Linux, Google Cloud.
Methodologies
MLOPS, LLMOps, DevOps, CI/CD, Shape up.
Frameworks
MCP, A2A, LangChain, Pydantic AI, llamaIndex, Pandas, PyTorch, TensorFlow, Scikit-Learn, Jax.