Los Angeles Metropolitan Area
Director of Applied Science, Generative AI at Oracle with 15+ years of experience in machine learning, neuro-computation, and human-AI interaction. Leading innovation in LLM-based services, Responsible AI, and secure code generation. https://docs.oracle.com/en-us/iaas/releasenotes/generative-ai/ai-guardrails.htm Architect of enterprise-grade LLM guardrails, automated red teaming, and explainable AI systems. Proven track record of building high-performing science teams, aligning AI strategy with business goals, and delivering scalable, compliant, and impactful GenAI solutions. Disclaimer: All views, opinions, and statements expressed here are solely my own. They do not represent, reflect, or imply the positions, strategies, or perspectives of my employer, any affiliated organization, or any entity with which I have a professional relationship. Nothing shared on this platform should be interpreted as official guidance, endorsement, or communication on behalf of any company or institution.
I lead the strategy, architecture, and deployment of advanced AI systems, driving enterprise innovation in generative and multimodal AI. As a Director, I combine hands-on technical leadership with organizational oversight—personally shaping system architecture, model design, and implementation while scaling AI capabilities across teams. My focus is on building high-performing, production-ready AI solutions grounded in strong safety, governance, and control frameworks. I design and implement responsible AI practices that ensure fairness, security, transparency, and compliance, while establishing robust validation pipelines and monitoring systems to manage risk in real-world environments. I partner closely with engineering, product, and business leaders to align AI innovation with strategic objectives, and I drive the development of vertical AI solutions tailored to industry-specific needs—delivering measurable, scalable impact.
Build smarter and faster. Scale your business with large language models (LLMs). A new era of productivity has arrived with generative AI.
Here at the OCI Vision Team, we offer a seamless and highly reliable experience in various computer vision-related applications for OCI clients by providing them with our cutting-edge, accurate, and customizable AI models and functionalities, including but not limited to: Image Classification, Visual Search with Few-shots, Image Tagging, Object Detection, Object Tracking, Face Detection and Recognition, Video Processing, and Document Analysis (OCR, Smart Content Detection). Team Lead and Principal Scientist – Launching Cloud-based Computer Vision Services ================================================================== • Collaborated with the Director to build the team from scratch by interviewing over 100 applicants and recruiting 20+ top data scientists. • Lead team of 20+ data scientists and working closely with the Director, Technical Program Manager, Product Manager, Engineering Lead, and assist them in launching our services promptly and with high quality • Key contributor in developing novel machine learning models, including but not limited to object detection, image classification, text recognition, few-shot learning for image and color tagging, automatic document type/ language detection. • Increased ML model predictions by (a) reducing/neutralizing cognitive biases, (b) using state-of-the-art models. • Lead the research track and publication • Main contributor and visionary member for designing new services and products. Leading Early Customer Engagement Effort ================================================================== • Secured internal and external customers by finding new customers, presenting them our beta products, understanding their needs, and providing them solutions. Team Liaison in Oracle-wide meetings ================================================================== • Present the developed services and achievements in Oracle’s internal meetings.
Led and managed a team of scientists to develop adaptive Human-Machine Interfaces, enabling AI to understand user intent and cognitive processes. Pioneered AI/ML innovations, including computational Theory of Mind, bio-inspired learning, and multisensory integration to enhance decision-making and adaptability. Improved AI-driven decision-making by mitigating cognitive biases, ensuring ethical alignment, and enhancing predictive accuracy. Designed human-centered AI systems to increase trust, usability, and adoption in autonomous technologies. Led groundbreaking research in biomarker discovery, advancing medically-differentiated therapies through cutting-edge machine learning and statistical modeling.
• Designed and implemented data ingest and processing pipeline for a $9 million contract by the National Institute of Mental Health for an ambitious effort to rapidly study promising new drugs that may help restore normal development and brain function in children with autism spectrum disorders. - Designed and developed new methods to explore how different regions in the brain communicate with each other: https://sites.google.com/site/bionectweb/home
I taught neuroimaging and electrophysiological signal processing. With the collaboration of Prof. Sandra Loo, I designed and developed the first electroencephalography signal processing course for UCLA.
I worked on a $9 million contract by the National Institute of Mental Health for an ambitious effort to rapidly study promising new drugs that may help restore normal development and brain function in children with autism spectrum disorders. The goal of the project, New Experimental Medicine Studies: Fast–Fail Trials in Autism Spectrum Disorders, was to determine within weeks rather than years ("fast") if a particular pharmacological compound is working or not ("fail"). Principal Investigators: James McCracken, MD Collaborators: UCLA, Seattle Children Hospital Former collaborators : MGH/ Harvard Medical School, Emory University
I worked on a $9 million contract by the National Institute of Mental Health for an ambitious effort to rapidly study promising new drugs that may help restore normal development and brain function in children with autism spectrum disorders. The goal of the project, New Experimental Medicine Studies: Fast–Fail Trials in Autism Spectrum Disorders, is to determine within weeks rather than years ("fast") if a particular pharmacological compound is working or not ("fail"). Principal Investigators : James McCracken and Sandra Loo https://www.ctsi.ucla.edu/news/item?item_id=88520
I worked on an NIMH grant and studying sensory processing, multisensory integration, and inter-hemispheric communication in children with autism spectrum disorders under the supervision of Dr. Clifford Saron. In collaboration with colleagues at the CMB and M.I.N.D. Institute, I utilized sensitive behavioral measures, eye tracking, and dense channel array event-related potentials to investigate possible deficits in these low-level processes which likely contribute to the complex phenotype of autism. Also, I developed a new method model to study multisensory integration and connectivity patterns in the brain.