Research Staff Member

Research Liaison, Global Innovation Outlook

Research lab: Watson Research Center (Hawthorne)

Engaging Research in a worldwide conversation about innovation that matters...

I graduated from the University of Illinois at Urbana Champaign in 2001 with a Masters and a Ph.D. degree in Electrical Engineering and then joined the Intelligent Information Analysis Group at IBM Research. My research interests include representing, learning and abstracting semantic information from multiple heterogeneous data sources. Towards this end I have worked in content analysis, information extraction, statistical machine learning and graphical modeling as well as in bio-surveillance, and business informatics. I am also interested in enabling marketplaces for content, services and solutions.

At the IBM Thomas J. Watson Research Center, I am helping engage IBM's research division in a worldwide conversation about innovation that matters. In my new role as the Research Liaison on the Global Innovation Outlook core team, I am working with clients, academia, partners, governments, NGOs and fellow IBMers to create a platform for an entire innovation ecosystem that could join together to surface new and unforeseen opportunities for business and societal innovation

Before taking over the role of Research Liaison, I pioneered the application of scalable generic learning for semantic multimedia retrieval and as a founding member I was responsible for enabling the semantic learning capabilities of IBM's MARVEL technology. This technology won the Wall Street Journal's Technology Innovation Award in the Multimedia category in 2004.

The scalable semantic learning technology I designed has been validated for several years and has also topped performance evaluation for several years at the NIST TRECVID concept detection benchmark. This work has also inspired the adoption of similar approaches for scalable and generic learning based multimedia retrieval across many other research sites worldwide.

In 2005-2006 I led a team of over 50 experts from various academic institutes, governmental agencies, and industrial research laboratories to design the largest multimedia ontology as part of the DTO Challenge Workshop project titled A Large Scale Concept Ontology for Multimedia Understanding -- LSCOM. This collaboratively designed ontology of over 1000 visual semantic concepts is the largest publicly available ontology which also comes with annotations for the TRECVID corpus .

I was a key member of IBM's VACE Phase II project and I am a co-principal investigator of IBM's VACE Phase III project on an Analyst Centric Workbench for Large Scale Cross Domain Video Intelligence.

My doctoral research was also in the area of scalable generic machine learning for modeling concepts and context and this work won the IEEE Circuits and Systems Society's Outstanding Young Author Award in 2004.

I am a senior member of the IEEE. I am also actively involved in several community-wide activities in multimedia and machine learning including organizing and program committees for several conferences and journal issues. I also enjoy teaching and have been part of summer schools in Italy and Greece. In the process I have been fortunate to be part of a rich social network of colleagues in several areas of expertise and this social capital is the most rewarding aspect of life as a researcher at IBM.
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Last updated 23 May 2007