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Dr Melinda Gervasio

Principal Scientist
Artificial Intelligence Center

SRI International
Room EJ209
333 Ravenswood Avenue
Menlo Park, CA 94025-3493
USA

Phone:  (650) 859-4411
Fax: (650) 859-3735

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Biography and Interests

Melinda Gervasio, Ph.D., is a Principal Scientist in the Artificial Intelligence Center at SRI International, where she is focused on developing technology that combine combines human and machine intelligence. Her research interests include intelligent assistants, machine learning for autonomous agents, adaptive personalization, interactive machine learning, end-user programming, and intelligent training systems. As the technical lead on a number of government-funded projects, Gervasio has developed technologies for learning from demonstration, adaptive assistance, proactive decision support, and recommendation for informal learning. Before joining SRI, Gervasio co-founded MindShadow, where she played a key technical role in the development of a software platform for personalized, content-based recommendation. She was also a research scientist at the Institute for the Study of Learning and Expertise, where she worked on adaptive personalization. Gervasio has a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign and a B.S. in Computer Science from the University of the Philippines Diliman.

Current Projects

PACT

Policy-directed Autonomy for Coordinated Teams

PACT seeks to support coordination of mixed-autonomy teams that combine both autonomous platforms and humans for integrated problem solving.

Past Projects

CALO

Cognitive Assistant that Learns and Organizes

As part of DARPA’s Personalized Assistant that Learns (PAL) program, SRI and team members are working on developing a next-generation "Cognitive Agent that Learns and Organizes" (CALO).

Integrated Learning

Integrated Learning

The Integrated Learning project is focused on developing machine learning technology that would enable a system to learn general planning knowledge from user demonstrations of processes.

SAVE

Semantically Enabled Assessment in Virtual Environments (SAVE)

The SAVE framework supports training in virtual environments through automated assessment of learner performance and tools for content authoring.

TransPAL

TransPAL: Transitioning PAL Technologies

The TransPAL project is transitioning a number of technologies developed on the DARPA PAL program for use by various members of the Armed Services.

Publications

The following are in reverse chronological order of publication.
Showing most recent 5 out of 31 [View All]

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