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Dr Melinda Gervasio

Principal Scientist
Artificial Intelligence Center

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Biography and Interests

Melinda Gervasio, Ph.D., is a principal scientist in SRI’s Artificial Intelligence Center. She focuses on developing technology that combines human and machine intelligence.

Gervasio’s 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, she 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 developing 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


Learning from Experience to Enable Proactive Decision Support

The ELF project seeks to develop an experience-based learning framework that mines information from prior problem-solving activities to enable proactive information gathering in support of current tasks. This framework employs machine learning methods that generalize from past activities to identify preferred sources for specific information needs, to provide mechanisms for retrieving data required to support decision making, and to suggest processes in support of current tasks.


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


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.


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: 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.


The following are in reverse chronological order of publication.
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