Columbia’s Vision for Tomorrow’s Global Intelligent Systems
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Columbia’s Vision for Tomorrow’s Global Intelligent Systems Henning Schulzrinne, Chair Department of Computer Science October 13, 2005 PowerPoint PPT Presentation


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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 October 13, 2005

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Columbia s vision for tomorrow s global intelligent systems henning schulzrinne chair department of computer science

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

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


Interacting with humans newsblaster

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


Interacting with humans detecting deceptive speech

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


Interacting with humans learning to match authors

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


Systems distributed channel allocation in mobile mesh networks

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


Systems creating new services for voip

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


Systems self healing software

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


Conclusion

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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