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Columbia’s Vision for Tomorrow’s Global Intelligent Systems Henning Schulzrinne, Chair Department of Computer Science Oc

Columbia’s Vision for Tomorrow’s Global Intelligent Systems Henning Schulzrinne, Chair Department of Computer Science October 13, 2005. Bill Gates/CS Faculty Roundtable. Columbia Computer Science Research. Interacting with Humans (5 faculty). Interacting with The Physical World (9).

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Columbia’s Vision for Tomorrow’s Global Intelligent Systems Henning Schulzrinne, Chair Department of Computer Science Oc

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  1. Columbia’s Vision for Tomorrow’s Global Intelligent Systems Henning Schulzrinne, Chair Department of Computer Science October 13, 2005 Bill Gates/CS Faculty Roundtable

  2. 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

  3. 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

  4. Interacting with Humans: Detecting Deceptive Speech • Problem: • Can we detect deception from spoken language cues only? • Method: • Collect corpus of deceptive & non-deceptive speech • Extract acoustic, prosodic and lexical features automatically • E.g., disfluencies, response latency, high pitch range, lower intensity, laughter, personal pronouns • Run machine learning experiments to create automatic prediction models and test on held-out data • Results: • Baselines: • Best general human performance in literature ranges from criminals (65% accuracy) down to parole officers (40%) • Majority class, our data (predict truth): 61% • Mean human performance with our data: 60% • Our (automatic) results: 69% Faculty: Julia Hirschberg Columbia CS

  5. 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

  6. 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

  7. 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, … • “FrontPage for service creation” • Based on presence, location, privacy preferences • Learn based on user actions Faculty: Henning Schulzrinne Columbia CS

  8. Systems: Self-healing Software Problem: zero-day attacks Approach: Enable systems to react and self-heal in response to unanticipated attacks and failures, via: Coordinated access control in large-scale systems Block-level system reconfiguration Self-healing software systems Application communities: enable large numbers of identical applications to collaboratively monitor their health and share alerts Shared intrusion detection for stealth scanning Prototypes: worms, software survivability Faculty: Angelos Keromytis, Sal Stolfo Columbia CS

  9. 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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