Information Sciences Institute, University of Southern California
Oct 2011 - present, Sr. Computer Scientist
Researcher in social media analytics focused on personalized information management. I look at problems such as extracting and linking entities and concepts from user generated content, learning about users based on their posts and reading behaviors, trending and clustering of users and communities over time. I use techniques from statistical relational learning, machine learning, social network analysis, data mining, text mining, information extraction and integration, and record linkage.

Fetch Technologies
Oct 2008 - Oct 2011, Director, Fetch Labs
Oct 2007 - Oct 2008, Principal Scientist
Sep 2005 - Oct 2007, Senior Research Scientist
Leading and directing government- and industry-funded research at Fetch Technologies. This includes formulating research directions as well as pushing developed and appropriate technologies towards transition into Fetch products. Research areas include relational learning, record linkage, social network analysis, graph mining.

Department of Computer Science, University of Southern California
Sep 2007 - present, Assistant Adjunct Professor
Spring 2006, Lecturer
Teaching the graduate-level machine learning course (CS-567) as well as advanced machine learning seminars on a semi-regular basis.

Stern Business School, New York University
Jan 2003 - Aug 2005, Associate Research Scientist
Studied classification and learning in networked data. This included an in-depth study of network-only classification which uses only class-labels or related instances to estimate the class of a given instance (e.g., classify research-papers based on citation links knowing the category of only a few research papers in the citation graph.) Developed, as part of this study, an open-source Network Learning Toolkit (NetKit). Other research has included applying network learning techniques in various domains, active acquisition of secondary data to improve performance and methods for generating confidence bounds on ROC curves.

Information Architects, 70 Hudson St, 2nd floor, Hoboken, NJ.
2/1999 - 12/2000, Internet Technologist
Chief Architect and Designer for an agent framework for the web as well as an event- and messaging- driven communication model. The agent framework, available as part of the SmartCode product, and built entirely in Java, uses an event- and messaging- driven model and include work on distributed computing using the HTTP, FTP and SMTP protocol levels. This framework empowers applications to track resources easily and transparently with minimum amount of cpu and network traffic. No spidering is involved unless strictly necessary.

Center for Computer Aids for Industrial Productivity(CAIP), Rutgers University
9/1992 - 7/1994, System Programmer III
Developed and maintained a beta-release of an Inter-Process-Communication (IPC) package between Unix and MacIntoshes using the AppleEvent(AE) protocol. The package was developed using the MPW and ThinkC environments on the MacIntosh. Compared three different environments: Prograph, SmallTalk, and SmallTalk Agents(beta-tested) and advised on which environment would be better suited for the research-group. Particular attention was made to ease-of-use and extensiveness of libraries for Graphics and Math.

Relational Learning, Stern Business School, New York University
Jan 2003 - Aug 2005
Worked on baseline methods, such as the Relational Neighbor classifier (RN), to which relational learners should be compared when assessing how well they have extracted a useful model from the given relational structure.

Information Triage, Rutgers University, PI: Haym Hirsh
Fall 2000 - Dec, 2002
Introduced a new framework for applying machine learning techniques to do ranking of information based on user interest and multiple information sources. The framework incorporates new and novel techniques for getting a user's interest, a learning methodology for acquiring a complementary user model and finally uses a new technique for analysing the user model for user comprehensibility.

Information Valets, Rutgers University, PI: Haym Hirsh
Winter 1998 - Fall 2000
Worked on techniques for unsupervised learning of user interest using relevance feedback in a variety of domains. Initial work has focused on creating a generic framework, the Information Valet Framework, to work with multiple wireless devices and multiple information sources. The EmailValet was the first instantiation of this work. The EmailValet learns to predict whether to forward a new email message to a user's pager based on past email reading behavior of the user on the pager.

Text Classification with Numerical Data, Rutgers University, PI: Haym Hirsh
Winter 1998 - Fall 2001
A new technique for incorporating numerical features into text classification systems (e.g. vector spaced models that use tokens and have no knowledge of numbers; The Naive Bayes classifier and TFIDF vector-based methods are two such systems). This technique works by converting numerical features into sets of tokens, using a method much like the "Thermometer Coding" representation, having close numbers have much overlap in their sets while distant numbers have less overlap. We have shown that by using this method, standard text classifiers can perform comparably to numerical methods on purely numerical datasets.

Department of Computer Science, University of Southern California, Los Angeles, CA

• Fall 2009: Statistical Relational Learning Seminar (CSCI-599).
• Fall 2008: Machine Learning (CSCI-567).
• Fall 2007: Machine Learning (CSCI-567).
• Spring 2006: Machine Learning (CSCI-567).

Department of Computer Science, Rutgers University, New Brunswick, NJ
Courses:

• Second-semester undergraduate course in data structures
  Instructor, (Fall 1996, Spring 1997)
  Teaching Assistant (Spring 1995, Spring 1996)
• Graduate course in data structures
  Teaching Assistant (Fall 1995)
• Introductory course to Computers for non-CS majors
  Teaching Assistant (Fall 1994)

Pencom Web Works, 40 Fulton St., New York, NY
9/1997 - 2/1999, Web Developer
Chief Architect and Designer for a prototype web-agent framework. Did initial performance experiments for proof of concept. Started on the design of the next generation of the framework, which realized a commercial release at Information Architects.

Ward Six Entertainment,
Spring 1997 - Spring 2000, AI/Interface Programmer
Created a flexible Non-Deterministic Finite State Machine simulator, a dialogue framework with a UI, as well as various utility classes, all developed in C++.

• Editorial Board:
  Machine Learning
  Journal of Artificial Intelligence Research
• Organizing committee:
  ECML/PKDD-2013, SIGKDD-2012, ICWSM-2012, SIGKDD-2011, MLG-2010, WSDM-2010, Fourth workshop on evaluation methods in machine learning (2009), Third workshop on evaluation methods in machine learning (2008), Second Workshop on Evaluation Methods for Machine Learning (2007), The Third Workshop on ROC Analysis in ML (2006), Second workshop on ROC Analysis in ML (2005), Second ML, IR and UM Workshop (2003), Third ML4UM Workshop (2001)
• Area Chair or Senior PC:
  SDM-2013, AAAI-2012 (AI & Web), ICWSM-2011, AAAI-2011 (AI & Web), ICML-2009
• Program Committee:
  KDD-2013, ICML-2013, ICML-2012, ECML/PKDD-2012, ICWSM-2012, AAAI-2012, Appification of the Web (AppWeb2012), IJCAI-2011, ICML-2011, AAAI-2011, ILP-2010, WWW-2010, KDD-2009 (research and industrial track), SRL-2009, Workshop on Grand Challenges for Reasoning from Experiences, CNIKM-2009, KDD-2008 (research and industrial track), K-CAP 2007, WPRSIUI-2007, AAAI-2006, WPRSIUI-2006, WPRSIUI-2005, ICML-2003
• Journal Reviewer:
  I am a regular reviewer at various journals, including:
  Journal of Machine Learning Research (JMLR), IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Intelligent Systems, ACM Transactions on Information Systems (TOIS), User Modeling and User-Adapted Interaction (UMUAI), Machine Learning Journal (ML), International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), Data Mining and Knowledge Discovery (DMKD), Decision Support Systems (DSS), International Conference Information Systems (ICIS), International Journal of Business Intelligence and Data Mining (IJBIDM).

• Invited talk, "Mining Social Media: The Importance of Combining Network and Content," The 8th International Conference on Data Mining (DMIN), July 2012.
• Invited talk, "Social Media Analytics: links, user generated content, and more.", Information Sciences Institute, USC, February 2011.
• Invited talk, "Social Media Analytics: links, user generated content, and more.", Rutgers University, September 2010.
• Invited talk/workshop, "Efficient Machine Learning on Large Networks by Leveraging Homophily," Networks and Network Analysis for the Humanities Workshop at UCLA, August 2010.
• Invited speaker, "Learning with Networked Data," Navy Research Labs, May 2010.
• Invited speaker, "Efficient Machine Learning on Large Networks by Leveraging Homophily," Lawrence Livermore National Labs, November 2009.
• Invited speaker, "Semi-supervised Learning in the context of networked data," University of Washington, April 2008.
• Invited speaker, "Semi-supervised Learning in the context of networked data," University of California, Irvine, October 2007.
• Invited speaker, "Improving learning in networked data by combining explicit and mined links," NASA Ames Research Center, August 2007.
• Invited speaker, "NetKit-SRL: A Toolkit for Network Learning and Inference," USC Information Sciences Institute AI Seminar Series, November, 2005.
• Invited speaker, "NetKit-SRL: A Toolkit for Network Learning and Inference," Google Mountain View, November, 2005.