SG
Director & Distinguished Engineer, Enterprise Data & Governance for AI Models
Almaden
IBM Research – Almaden is IBM's Silicon Valley innovation lab. Scientists ranging from chemists to physicists, as well as mathematicians, engineers and designers at Almaden are pioneering breakthroughs across disruptive technologies including AI and machine learning, hybrid cloud, quantum computing, security and storage. Their published works and contributions to the scientific community cross several industries, including healthcare, semiconductors, sustainable energy, renewable materials, retail and data privacy. Accomplishments are recognized through thousands of publications, citations, invited talks, industry and academic partnerships and conference chair appointments.
Meet the team
The team's work builds on a rich history of breakthroughs at Almaden’s unique campus in San Jose, California that include innovations in data storage technology, novel material discovery for sustainability, the distributed relational database, the ability to position individual atoms, and the first data mining algorithms.
TS
IBM Fellow, Chief Scientist, Multimodal Bioinspired AI
LP
Principal Research Scientist
JP
Strategy Co-lead -- Sustainable Materials
MD
Senior Research Scientist, Manager - core language and conversational technologies
DM
IBM Fellow; IBM Chief Scientist, Brain-inspired Computing
News
IBM Research Blog
IBM Research Blog
IBM Research Blog
IBM Research Blog
IBM Research Blog
Think Lab
The role of the Global Think Labs is to make what’s next in computing actionable for our clients. We offer a stimulating environment to explore future technologies and their transformational impact on business and society. Together with our leading scientists and experts, we offer deeper innovation discussions, enable small group exchanges and host hands-on technology demonstrations. The main focus of client meetings in Almaden is in the areas of materials sciences, AI hardware, sustainability and federated learning.
Projects
Scaling AI technologies for NLP and text data to a large variety of users.
Making Deep Neural Network systems more capable and energy-efficient.
Securing AI models with the Adversarial Robustness Toolbox
Developing a general knowledge representation framework to facilitate effective reasoning over multiple sources of imprecise knowledge.
