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Columbia University Department of Computer Science Henning Schulzrinne, Chair

Columbia University Department of Computer Science Henning Schulzrinne, Chair Department of Computer Science. IBM CAS. Columbia Computer Science in Numbers. ~34 full-time faculty and lecturers + visitors, postdocs, adjunct faculty, joint appointments (EE, IEOR), …

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Columbia University Department of Computer Science Henning Schulzrinne, Chair

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  1. Columbia University Department of Computer Science Henning Schulzrinne, Chair Department of Computer Science IBM CAS

  2. Columbia Computer Science in Numbers • ~34 full-time faculty and lecturers • + visitors, postdocs, adjunct faculty, joint appointments (EE, IEOR), … • 125 PhD students (~10 new arrivals) • 221 MS students (120 new arrivals) • 100 CS undergraduate majors (juniors, seniors) • + 20 computer engineering students Columbia CS

  3. Faculty: 34 (31 tenure track, 3 lecturers) + 3 joint Carloni Edwards Feiner Aho Allen Belhumeur Bellovin Cannon Galil Gravano Grinspun Gross Grunschlag Hirschberg Jebara Kaiser Kender Keromytis Malkin McKeown Misra Nayar Nieh Nowick Ramamoorthi Ross Rubenstein Yannakakis Schulzrinne Servedio Shortliffe Stolfo Stein Unger Traub Wozniakowski Yemini Columbia CS

  4. Columbia Computer Science Research Interacting with Humans (5 faculty) Interacting with The Physical World (9) Systems (11) Computer Science Theory (8) Making Sense of Data (7) Designing Digital Systems (4) UI, NLP, collab work graphics, robotics, vision networks, security, OS, software eng quantum computing, crypto, learning, algorithms databases, data mining, machine learning CAD, async circuits, embedded systems Columbia CS

  5. Research areas Columbia CS

  6. CCLS: A Research Center in CS The Center for Computational Learning Systems (CCLS) aims to be a world leader in learning and data mining research and the application of this research to natural language understanding, the World Wide Web, bioinformatics, systems security and other emerging areas. CCLS will emphasize interdisciplinary efforts with other departments at Columbia, and will leverage Columbia's CS Department's strengths in learning, data mining and natural language processing, extending the effective size and scope of the Department's research effort. Columbia CS

  7. Interacting with Humans: Newsblaster Automatic summarization of articles on the same event Generation of summary sentences Tracking events across days Foreign news  English summaries Faculty: Kathy McKeown Columbia CS

  8. Working with IBM Text-to-Speech Synth. Group • Joint work between Michael Picheny’s TTS group and Julia Hirschberg and students at CU • Issue: IBM’s Research TTS system one of the best, but even the best TTS systems often do not sound like humans: • intonation • ability to convey human emotion to a listener • Our joint goal: to enhance the IBM system to improve naturalness and expressiveness via • Better assignment of intonational prominence and phrasing • Additional flexibility to produce ‘emotional’ speech (certainty/uncertainty, anger/frustration) Columbia CS

  9. Interacting with Humans: Learning to Match Authors Error rate 1 3 2 Columbia Entity Resolution of Anonymized Publications 7 Teams: UMass, Maryland, Fair-Isaac, Illinois, Rutgers, CMU, Columbia Key 1 - Permutational Text Kernels 2 - Permutational Clustering 3 - SVM Source: 2005 KDD Challenge Faculty: Tony Jebara Columbia CS

  10. Systems: Distributed Channel Allocation in Mobile Mesh Networks Windows XP Channel Allocation Protocol TCP/IP MCL* NDIS** DevCon 802.11card A 802.11card B CEPSR research building • Multi-radio mesh node • Channel scarcity  need automated channel allocation in 802.11 mesh networks • Allocates radios by self-stabilizing algorithm based on graph coloring • Results • First self-organizing mechanism & implementation • Network self-organizes in seconds • Network throughput improvement of 20-100%cf. static channel allocation Collaborators: Victor Bahl and Jitendra Padhye @ MSR Faculty: Misra/Rubenstein Columbia CS

  11. Systems: Creating new services for VoIP • Old telecom model: • Programmers create mass-market applications • new service each decade • Our (web) model: • Users and administrators create universe of tailored applications • Incorporate human context: • location, mood, actions, … • “Eclipse for service creation” • Based on presence, location, privacy preferences • Learn based on user actions Faculty: Henning Schulzrinne Columbia CS

  12. Self-healing Software Systems • Novel techniques for software that repairs its failures based on Observe-Orient-Decide-Act (OODA) loop • Demonstrated concept with two experimental prototypes • One aimed at the problem of worms • One aimed at software survivability in general • Application Communities: enable large numbers of identical applications to collaboratively monitor their health and share alerts Columbia CS

  13. Self-patching Architecture • Systems approach to creating software that: • Detects new attacks/failures • Automatically generates and applies appropriate fixes • Developed error virtualization as a generic “band-aid” technique • Prototypes for open-source and binary-only environments • Efficient security and high availability mechanism with little performance penalty • Spin-off: Revive Systems Inc. Columbia CS

  14. Computer Graphics and User Interfaces Lab (Prof. S. Feiner) Cursorless Input for Wearable UIsGábor Blaskó • Minimize need for visual feedback in wearable user interfaces • E.g., watch bezel serves as “tactile landmarks” to guide user’s finger Columbia CS

  15. Columbia/FSTC Relationship • A group of 6 CS faculty manage the Security Standing Committee • The CS department hosts the FSTC executive director, and provides facilities for meetings • Members include most of the largest banks and financial institutions and IT security vendors • Industry collaborative R&D Projects dealing with security of the IT infrastructure Columbia CS

  16. Conclusion • Broad-based research motivated by real problems • Breaking new ground in several key areas, e.g.: • Natural language processing • New network services and models • Network security • Graphics & vision • Columbia has a growing impact on computer science as demonstrated in successfully bringing new technology to the field • Start-ups • Standardization • Education Columbia CS

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