Ashutosh Jadhav

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Graduate Research Assistant - Kno.e.sis - Ohio Center of Excellence in Knowledge-enabled Computing
Ph.D. Candidate - Computer Science and Engineering Wright State University
Advisor - Dr. Amit Sheth

Kno.e.sis gave me an opportunity to work on various interesting projects and problems. I have contributed in developing a social media analysis and research platform Twitris. My other past projects are Disaster Data Informatics for Situational Awareness and Knowledge Acquisition from Community-Generated Content . In summer 2011, I did research internship at HP Labs, CA. I worked with HP Services Research team on a context-aware computing project. Based on my internship work HP filed a patent on Context-Aware Information Recommendation. During internship, I collaborated with Claudio Bartolini (manager) and Hamid Motahari (mentor).

Currently I am working on Social Health Signals project (Computer Science + Social Media + Healthcare). Objective this project is to understand and satisfy users need for keeping track of new information in healthcare and well-being domain. The project harvests collective intelligence to identify high quality, reliable and informative healthcare content shared over social media.


Research Projects

Twitris- social media analysis and research platform

I have been one of the mainstays of the Twitris project at Kno.e.sis. Twitris facilitates understanding of social perceptions using semantic processing of massive amounts of event-centric data. Twitris addresses challenges in large scale processing of social data and information overload in social media. Twitris 2.0 also covers context based semantic integration of multiple Web resources and expose semantically enriched social data to the public domain. Specifically, I contributed to text analysis, information extraction and information integration components of the system. Kno.e.sis won a NFS research grant and patent based on Twitris work. Articles on Twitris has been featured on semanticweb.com, mashable.com etc.

Social Health Signals

Objective this project is to understand and satisfy users need for keeping track of new information in healthcare and well-being domain. The project harvest collective intelligence to identify high quality, reliable and informative healthcare content shared over social media. SHS analyze the act of health information sharing over social media by understanding who (People analysis) share what (Content analysis) when (Temporal analysis) in what context (Semantic analysis) on which channel/website (Reliability analysis) with what social effect (Popularity analysis).

Disaster Data Informatics for Situational Awareness

I have worked on an AFRL funded project to create Geo-Social Mash-up for situational awareness in a disaster response situation. Current objective of this project is to expedite decision-making process in the disaster situation by identifying useful/actionable information from social media.

Knowledge Acquisition from Community-Generated Content

This project aims at generating or extracting a domain model from Wikipedia or other similarly structured knowledge sources. My contribution: I worked on extraction of links (wikipedia links and web URLs) mentioned on whole corpus of Wikipedia articles as a part of Doozer, a tool for automatically creating topic domain model using Wikipedia corpus.

Context-aware Content Recommendation in Enterprise Social Network

Research Internship at HP Services Research Lab, HP Labs, CA
Claudio Bartolini (manager) and Hamid Motahari (mentor)

(Due to confidentiality reasons, limited information is provided)
During internship, I worked with HP Services Research team on a context-aware computing research project titled ‘Context-aware content recommendation in enterprise social network’. Objective of the project is to expedite Request For Proposal (RFP) response process by making right content recommendation (past deal documents) at right time. We developed a document recommender system using semantic document similarity approach taking into account information about content (current and past documents), enterprise social network (people and their role) and different stages of enterprise RFP process.

Based on my internship work, HP Labs filed a patent (83138852) on Context-Aware Deal Recommendations with myself being primary inventor.


Technical Skills

  • Programming Languages: JAVA, C, PHP, HTML, XML, Scheme
  • DBMS  : MySQL, MS Access, Virtuoso triple store
  • Semantic Web  : OWL, RDF, SPARQL
  • Tools  : Weka, Protege
  • Operating Systems  : Mac OS, Linux, MS Windows


Publications

  • Twitris: Socially Influenced Browsing
    • Ashutosh Jadhav, Wenbo Wang, Raghava Mutharaju, Pramod Anantharam, Vinh Nguyen, Amit P. Sheth, Karthik Gomadam, Meenakshi Nagarajan, and Ajith Ranabahu
    • Semantic Web Challenge 2009, 8th International Semantic Web Conference, Oct. 25-29 2009, Washington, DC, USA
  • HP patent on Context-Aware Information Recommendation, filed in January 2013
    • Patent filled based on HP summer 2011 internship work
    • Ashutosh Jadhav, Hamid Motahari, Susan Spence, Claudio Bartolini


Professional Activities


Education and Work Experience

Education


Work Experience

Contact Information

  • Ashutosh Jadhav
    • Email: ashutosh@knoesis.org
    • 380, Joshi Research Center, Wright State University, 3640 Colonel Glenn Hwy, Dayton, Ohio 45435-0001
    • LinkedIn


Curriculum Vitae (CV)

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