cs orientation - fall 2004 the department of computer science at columbia university henning...

CS orientation - Fall 2004

The Department of Computer The Department of Computer Science at Columbia UniversityScience at Columbia University

Henning Schulzrinne, ChairDept. of Computer Science

Columbia University2004


Columbia Computer Science in Columbia Computer Science in NumbersNumbers

~33 full-time faculty and lecturers + visitors, postdocs, adjunct faculty,

joint appointments (EE, IEOR), … 110 PhD students (~20 new arrivals) 170 MS students (75 new arrivals) 170 CS undergraduate majors

+ 40 computer engineering students About 16 administrative staff

5 system administrators


Faculty: 34 (31 tenure track, 3 lecturers) + 3 jointFaculty: 34 (31 tenure track, 3 lecturers) + 3 joint

Aho Allen Carloni Feiner Gravano

Gross Grunschlag

McKeown

KenderKaiser

Nayar Ramamoorthi

Servedio

Schulzrinn

e

Ross Nowick

StolfoShortliffe

Keromytis

Nieh

MalkinHirschberg

Sklar

Rubenstein

Yemini

Misra

Wozniakowski Unger

Stein

Jebara

Belhumeur Edwards

Traub Yannakakis

Cannon Galil

Grinspun


Interacting withHumans

(7)

Interacting withHumans

(7)

DesigningDigital Systems

(4)

DesigningDigital Systems

(4)

Systems(10)

Systems(10)

Interacting withthe Physical World

(10)

Interacting withthe Physical World

(10)

ComputerScienceTheory

(8)

Research

Making Senseof Data

(9)

Making Senseof Data

(9)


Research areasResearch areasInteracting with the Physical World

graphics, robotics, vision Allen, Belhumeur, Feiner, Grinspun, Grunschlag, Jebara, Kender, Nayar, Ramamoorthi, Sklar

Interacting with Humans

user interfaces, natural language and speech processing, collaborative work, personalized agents

Feiner, Hirschberg, Kaiser, Kender, McKeown, Sklar

Systems networks, distributed systems, security, compilers, software engineering, programming languages, OS

Aho, Edwards, Kaiser, Keromytis, Malkin, Misra, Nieh, Schulzrinne, Stolfo, Yemini

Designing Digital Systems

digital and VLSI design, CAD, asynchronous circuits, embedded systems

Carloni, Edwards, Nowick, Unger

Making Sense of Data

databases, data mining, Web search, machine learning applications

Cannon, Gravano, Jebara, Kaiser, Ross, Servedio, Stolfo

Computer Science Theory

cryptography, quantum computing, complexity, machine learning theory, graph theory, algorithms

Aho, Galil, Gross, Malkin, Servedio, Traub, Wozniakowski, Yannakakis


CLASS: A Research Center in CSCLASS: A Research Center in CS

The Center for Computational Learning Systems (CLASS) 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. CLASS 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.


Anatomy of a research groupAnatomy of a research group

Typically, each faculty heads a research group consisting of 1 faculty sometimes 1-2 postdocs research visitors (industry, sabbatical) 1 to 10 PhD and MS graduate research

assistants typical: 5

a number of undergraduate and MS project students

COMS 3998, 4901, 6901 sometimes an administrative assistant (AA)


Columbia research economics 101Columbia research economics 101

For each GRA, a faculty needs to attract roughly $60k for 12 months, $48k for 9 months 12*$2,226 = $26.7k stipend $15,130 for tuition $1,000 for computing support 61% overhead (on almost everything except

tuition, including equipment and travel) University only pays 9 months of faculty

salary summer salary needs to be funded out of

grants


Participating in researchParticipating in research

Take 4000 or 6000-level classes MS: take 4901 or 6901 project course with faculty MS: do 15-credit thesis 4995 and 6998 are “topics” courses often offered

only once, on research topic of local faculty or adjunct from local research labs (IBM, Bell Labs,…)

Attend departmental talks typically, Mo or We, 11—12.30 faculty talks (research summaries), invited distinguished

speakers and faculty candidates (spring) Attend research group talks in vision/robotics,

networking, theory, … Participate in research group meetings

often, students and visitors discussing current research sometimes pizza


Social life in CUCSSocial life in CUCS

Departmental BBQ in fall and spring CS@25 celebration on Oct. 21-23 Coffee hour on Thursdays at 4 pm in

CS lounge Activities organized by ACM,

Department and graduate school roughly once a month

Movie nights in lounge


Volunteering or How to Become a Volunteering or How to Become a Czar(ina)Czar(ina)

Department needs your help to make it a nice place to study and work

Volunteer positions include webmaster photo czar space czar copier czar help with departmental BBQ grad student representative ACM

Contact PhD representative (Knarig Arabshian, Edward Ishak) for details


Student groupsStudent groups

Women in Computer Science (WICS) http://www.cs.columbia.edu/wics/

ACM http://www.cs.columbia.edu/acm/


Faculty to knowFaculty to know

Prof. Gail Kaiser PhD program director (phdczar@cs)

Prof. Yechiam Yemini MS program director (yemini@cs)

Prof. Betsy Sklar TA issues (sklar@cs)


Important people to know: staffImportant people to know: staff

Alice Cueba receptionist: mail, fax, packages

Simon Bird, Remi Moss, Twinkle Edwards graduate program and records

Mary van Starrex department administrator: swipe card problems, GRA

appointments Patricia Hervey

budgets and finances, e.g., travel reimbursements Elias Tesfaye

keys, purchase orders Daisy Nguyen

CRF (Computing Research Facility): heads systems support (sys admin) group


MICE (Managing Information in Computer MICE (Managing Information in Computer SciencE)SciencE)

https://www.cs.columbia.edu/mice Services:

Find people and their contact information, office hours Select MS advisor Track your MS and PhD progress: courses, publications,

exams, community service PhD Black Friday

Get notified of packages and faxes Jobs (posting and listings) Equipment tracking for research groups

You will get password once you obtain a CS account

but different password! if you forget password, MICE will send you a new one


MICEMICE


Getting into the buildingGetting into the building

Need to get swipe card access enabled to get access to CEPSR and CS building

Apply in MICE (under “Access”) Some labs have keys contact your

advisor for details


PhD student resourcesPhD student resources

http://www.cs.columbia.edu/~phdczar

Program details Hints on writing and other “how to

succeed in graduate school” items


Projects (MS)Projects (MS)

Can do research projects with most faculty CS 4901, 6901

Usually, unpaid (but there are exceptions) Good way to get to know a research area and

faculty ( recommendation letters…) One (typically) or two semesters in length May lead to publication or CS technical report 1-6 credits, with 3 typical Should be equivalent to one or two courses in

effort, e.g., 9 hours/week for 3-credit project


Research groupsResearch groups

Sampling of research groups in department

Sampling from … Graphics, robotics, vision Agent systems Networks and distributed systems Digital Systems Databases Theory

CS orientation - Fall 2004 Mobile RoboticsRobotic Crystal Mounting

3-D Site Modeling

Graspit! Simulator

Computer AidedSurgery


Current Projects:1. 3-D Modeling: Combining laser scanning and computer vision to

create photorealistic models. Current NSF ITR project includes scanning Beauvais Cathedral in France and ancient ruins in Sicily

2. Robotic and human hand simulation using our Graspit! simulator which includes full dynamics, grasp quality measures, and grasp learning

3. Microscale protein crystal mounting using visual control. Microscope camera used to track/pick up very small crystals for x-ray diffraction

4. AVENUE mobile scanning robot: automating the site modeling process using GPS, wireless network, computer vision and range scanning

5. New insertable stereo cameras with pan, tilt and translation for minimally-invasive surgery

People:• Postdocs: Atanas Georgiev and Andrew Miller

• GRA’s: Paul Blaer, Alejandro Troccoli, Ben Smith• M.S.: Rafi Pelosoff, Alex Haubald

Prof. Peter Allen


Goal: Creating intelligent machines and systemsCollaborative Research: Currently working with:• Molecular Biology (crystal mounting)• Art History (3D Modeling)• Biomechanics (human hand simulation)• Surgery (next-generation surgical imaging)One of the labs affiliated with CVGC (Columbia Vision and

Graphics Center)Research opportunities include a wide range of software, hardware and systems projects.

Expertise in robotics, graphics, or vision is helpful


Computer Graphics and User Interfaces LabComputer Graphics and User Interfaces LabS. Feiner, B. Bell, H. Benko, G. Blaskó, S. Güven, D. Hallaway,S. Feiner, B. Bell, H. Benko, G. Blaskó, S. Güven, D. Hallaway,E. Ishak, S. Lok, T. Okuma, A. Olwal, T. ZhouE. Ishak, S. Lok, T. Okuma, A. Olwal, T. Zhou

Wearable UIs Augmented reality Virtual reality


Computer Graphics and User Interfaces LabComputer Graphics and User Interfaces LabS. Feiner, B. Bell, H. Benko, G. Blaskó, S. Güven, D. Hallaway,S. Feiner, B. Bell, H. Benko, G. Blaskó, S. Güven, D. Hallaway,E. Ishak, S. Lok, T. Okuma, A. Olwal, T. ZhouE. Ishak, S. Lok, T. Okuma, A. Olwal, T. Zhou

Automated generation of graphics

Display layout Coordination with

text generation


Prof. Elizabeth Sklar's Agents LabProf. Elizabeth Sklar's Agents Labhttp://agents.cs.columbia.eduhttp://agents.cs.columbia.edu

• Relationship learning in humans and learning in agents (both virtual and embodied)

• Ways in which these can co-evolve: learn from each other, by interacting

• Learning in humans = • Virtual agents help humans learn by acting as learning partners,

adapting behavior based on its interactions with human users.• Embodied agents help humans learn by providing a hands-on

means for experiencing technology through educational robots RoboCupJunior (LEGO Mindstorms).

• Learning in agents = discovering ways in which virtual and embodied agents can learn by interacting with each other, with humans and with their environment…

• Virtual agents learn in simulation by interacting with each other and by sensing data inputs; a primary focus is on mechanism design.

• Embodied agents learn in real-time by interacting with humans, with the environment and with virtual agents (Sony Aibo).


Prof. Tony Jebara Risi KondorAndrew HowardAnshul KundajeDarrin Lewis

www.cs.columbia.edu/learning

a1 a2 a3 a4

s1 s2 s3 s4

w1 w2 w3 w4


TopicsSupport Vector Machines and Kernel Methods

Representation Learning

( )0,P Q g

The Admissible Set

( ),P Q g

xxx

’*( )|p x q 1x

1s

2x

2s

3x

3s

4x

4s

0x

0s

1u 2u 3u 4u0u


Computer Vision, Tracking People and Understanding Video

Discriminative Graphical Models

Topics

20y

30y

40y

11y

21y

31y

41y

10y

20x

30x

40x

11x

21x

31x

41x

10s

10x

20s

30s

40s

11s

21s

31s

41s

1,20s 3,4

0s3,41s

1,21s

0s 1s


Gail Kaiser:Gail Kaiser:Programming Systems LabProgramming Systems Lab

Main research goal: Develop methodologies and technologies to aid teams working together on large scale software engineering projects and other business, education and social endeavors

PhD Students: Jean-Denis Greze Rean Griffith Phil Gross Suhit Gupta Gaurav Kc Janak Parekh Dan Phung Alpa Shah Peppo Valetto

Details at http://www.psl.cs.columbia.edu


Gail Kaiser: Programming Systems Gail Kaiser: Programming Systems LabLab

Main topics: autonomic computing (self-healing applications & systems), collaborative work, team-oriented user interfaces (from large screens to PDAs), security, Web-based information management, applied AI, software development environments and tools

Seeking MS project students interested in:

Publish/subscribe content-based event systems

Complex event correlation for autonomic computing and security applications

Applications of machine learning to context-based individual & collaborative work

Extensions of XML and Web Service technologies for collaborative computing

Details at http://www.psl.cs.columbia.edu


Networking research at Columbia Networking research at Columbia UniversityUniversity

Columbia Networking Research Center

spans EE + CS 15 faculty – one of the largest

networking research groups in the US

about 40 PhDs spanning optical networks to

operating systems and applications theory (performance analysis) to

systems (software, protocols)


Columbia Intrusion Detection Lab (Sal Columbia Intrusion Detection Lab (Sal Stolfo)Stolfo)

Attackers continue to improve techniques undeterred – Present COTS security defenses are porous and suffer

from the false negative problem There is no one monolithic security solution; security is

a design criteria at all layers of the stack Behavior-based computer security will substantially

raise the bar Columbia conducts a broad spectrum of research

related to securing critical infrastructure in close collaboration with industry and government with attention to practical and deployable results

Visit: http://www.cs.columbia.edu/faculty http://www.cs.columbia.edu/ids http://www.sysd.com


Columbia Intrusion Detection Lab: Email Misuse Columbia Intrusion Detection Lab: Email Misuse and Stealthy Surveillanceand Stealthy Surveillance

Malicious Email Tracking An online tool for detecting

new viruses, SPAM and misuse

Behavior-based detection of “abnormal” traffic

Email Mining Toolkit Forensic analysis of email

logs for profile and model generation

Comparison of profiles/models

Detect malicious users/groups and aliases

Surveillance Detector Orders of magnitude

improvements over COTS IDS scan/probe detection

Deployed externally by System Detection, Inc.


Columbia Intrusion Detection Lab Columbia Intrusion Detection Lab ProjectsProjects

Goals: Advance the state of the art in Intrusion Detection and

Prevention using Machine Learning technology Why? Current IDS detect what is known, they do not

detect was is new until damage has already been done. Scale up to high bandwidth analysis Reduce False Positive rate Increase security analyst productivity

Student Lab Projects Teams of Graduate students working with ugrads

develop algorithms, test environments, and perform careful experiments

Weekly and bi-weekly meetings where all team members present their work

Several undergrads have co-authored papers, two having won best paper awards, and two undergrads have won honorable mention awards from the National Computer Association


Network Computing LaboratoryNetwork Computing Laboratoryhttp://www.ncl.cs.columbia.eduhttp://www.ncl.cs.columbia.edu

Operating Systems Distributed Systems Scheduling and Resource

Management Thin-Client and Network

Computing Web and Multimedia Systems Performance Evaluation


Network Computing LaboratoryNetwork Computing LaboratoryRecent Research ProjectsRecent Research Projects

Zap: Transparent process migration VNAT: Mobile networking GR3: O(1) proportional share

scheduling Thinc: WAN remote display protocol Certes: Inferring web client response

times


Network Computing LaboratoryNetwork Computing Laboratory

MS research projects available for 4000-level and 6000-level course credit

Bi-weekly systems seminar lunch meetings

Information: Prof. Jason Nieh ([email protected])


Tal Malkin: CryptographyTal Malkin: Cryptography

Crypto group Theory group Secure Systems Lab Crypto = construct computation and communication efficient

schemes maintaining desired functionality even in adversarial environment

(e.g., public key encryption, secure computation, authentication, contract signing, voting, e-commerce, …)

Motivation and Goals security, privacy, social, financial, political needs

Solutions rigorous, theoretical approach Research themes:

Definitions (identify, conceptualize, formalize goals) Protocol design (efficiency and provable security) Foundations (complexity, assumptions, limits) Search for both positive and negative results


Tal Malkin: Examples of Research Tal Malkin: Examples of Research TopicsTopics

Protecting against temporal or partial key exposure: key-evolving (e.g., forward-secure) schemes to mitigate damage of key leakage.

Protecting against key manipulation or tampering attacks: algorithmic defense against physical attacks on keying material.

Private information retrieval: keep user’s interests private even from database holder.

Relations among cryptographic primitives: reductions and oracle separations; minimal assumptions for cryptographic tasks.

Secure computation of approximations, completeness for multi-party computation, multicast encryption, anonymous routing, intrusion detection, steganography, …

For more information: take crypto class this fall, contact Prof. Malkin, check out http://www.cs.columbia.edu/~tal


Network Security LabNetwork Security LabDirector: Prof. Angelos D. KeromytisDirector: Prof. Angelos D. Keromytis

[email protected]@cs.columbia.edu

Applied research in security, networking, operating systems Efficient cryptographic mechanisms/protocols Denial of service Software security Network viruses/worms

Currently 5 graduate students (Cook, Locasto, Burnside, Stavrou, Hu) Several "affiliated" (Kc, Sidiroglou, Channing)

http://nsl.cs.columbia.edu/


NSL ProjectsNSL Projects

Network Worm Vaccine Limit worm infection rate via anomaly detection engine and automatic

patching of vulnerable software Software Randomization

Protection against injected code Resilience Against Denial of Service Attacks

Graphical Turing Tests combined with Secure Overlay Services to provide resilient services

High-speed I/O: The Operating System As a Signaling Mechanism New OS architecture - remove memory and CPU from data path

Efficient Cryptography Design and implementation of ciphers for specific environments - use

of graphics cards, variable size block ciphers, IXP processor Collaborative Distributed Intrusion Detection

Identifying global attack activity as well as “low and slow” scans via shared intrusion alerts across administrative domains


IRT real-time laboratory (IRT)IRT real-time laboratory (IRT)http://www.cs.columbia.edu/IRThttp://www.cs.columbia.edu/IRT

Internet multimedia protocols and systems Internet telephony signaling and services Ubiquitous communication

Wireless and ad-hoc networks Quality of service

multicast, scalable data plane signaling, … Service discovery and location-based

services Content distribution networks DOS prevention and traceback


IRT Projects & group meetingsIRT Projects & group meetings

Projects available in multimedia systems, location-based services and related topics

Weekly research group talks (Tuesday, 6 pm) open to project students


Asynchronous Circuits & Systems GroupAsynchronous Circuits & Systems Grouphttp://http://www.cs.columbia.edu/~nowick

Prof. Steven Nowick ([email protected]) Research in clockless digital systems

Most digital systems are synchronous = have a global clock

Potential benefits of asynchronous systems: Modular “plug-and-play” design: assemble components,

no global timing concerns Low power: no burning of clock power, components only

activated on demand High speed: not restricted by fixed clock speed

Challenges: new techniques needed New “CAD” (computer-aided design) software tools to

aid designers New circuit design styles


Asynchronous Circuits & Systems Asynchronous Circuits & Systems GroupGroup

CAD Tools: Software tools + optimization algorithms Allow automated ‘push-button’ circuit synthesis +

optimization For individual controllers (state machines), for entire

systems (processors) Circuit Designs:

New techniques to design asynchronous circuits (adders, multipliers)

Interface circuits: for mixing synchronous + asynchronous subsystems

Very high-speed pipelines: several GigaHertz Group Meeting (tentatively): Weds. 5:30-7:00pm (CS

4th floor conf. room) – contact Prof. Nowick


Columbia’s Database GroupColumbia’s Database Grouphttp://www.cs.columbia.edu/databasehttp://www.cs.columbia.edu/database

FacultyLuis GravanoKen Ross

Ph.D. StudentsEugene AgichteinWisam DakkaPanos IpeirotisAmélie MarianJingren Zhou

•Weekly group meetings; all welcome

•Contact [email protected] or [email protected] if interested in attending


Some Projects in Gravano’s “Subgroup” Some Projects in Gravano’s “Subgroup” http://www.cs.columbia.edu/~gravano

Snowball, an information-extraction systemhttp://snowball.cs.columbia.edu

QProber, a system for classifying and searching “hidden-web” text databaseshttp://qprober.cs.columbia.edu

SDARTS, a protocol and toolkit for metasearchinghttp://sdarts.cs.columbia.edu

RANK: “top-k” query processinghttp://rank.cs.columbia.edu

PERSIVAL, personalized search and summarization over multimedia informationhttp://persival.cs.columbia.edu

For-credit research projects available;contact [email protected]


Theory Group ActivitiesTheory Group Activities

Profs. Malkin, Servedio, Stein Weekly seminar/reading group

http://www1.cs.columbia.edu/~tal/theoryread.html


Quantum ComputationQuantum Computation

Profs. Wozniakowski, Traub, Aho Weekly seminar, to be announced

to department Projects available


Quantum ComputingQuantum Computing

MotivationMoore's Law, which has held for some 40 years, states that the number of elements on a chip doubles about every 18 months. In 10-15 years,features will be about the size of an atom andcurrent silicon technologies will no longer track Moore's Law. Quantum computing is one of thepossible future technologies.


Quantum Computing ResearchQuantum Computing Research

If physicists can build quantum computers, what are the killer applications?

How much more powerful is a quantum computer than a classical computer;that is, compare quantum computational complexity with classical complexity.

How should compilers for quantum computers be constructed?


People involved in QC ResearchPeople involved in QC Research

Faculty and Researchers Al Aho Anargyros

Papageorgiou Rocco Servedio Joseph Traub Henryk

Wozniakowski

Students Alp Atici Arvid Bessen Eden Yian Chee

Hoo Marek Kwas Krysta Svore


Background for Quantum Background for Quantum ComputingComputing

To work on quantum computing you must know:

Linear algebra Basics of quantum computing Knowledge of quantum mechanics is

useful but not necessary


To learn more about QCTo learn more about QC

Linear Algebra, CS3251, offered Fall 2003

Introduction to Quantum Computing - new course to be offered Spring 2004

Weekly seminar on quantum computing - Fall 2003 - time and place TBA

For information on the Columbia-MIT project on quantum computing see http://quantum.cs.columbia.edu


Rocco Servedio: Theory of Rocco Servedio: Theory of ComputingComputinghttp://www.cs.columbia.edu/~rocco

Main research goal: design and analyze provably correct and efficient learning algorithms for interesting and important classes of functions

Boolean formulas

+

+++

+

-- - --

-

-- -- -

- --

-

AND

OR OR OR

AND …………………………..

x1

AND

xn

………………………………………….

+

geometric concepts

v4

v2 v6

v1 v2 v3

0

0

1 1 0 0 1

decision trees


Rocco Servedio: Theory of Rocco Servedio: Theory of ComputingComputing

Main approach: explore & exploit connections between computational learning theory and other areas of CS theory

Complexity theory: representation schemes studied in complexity theory (Fourier representations, polynomial threshold functions) are useful for learning

Cryptography: basis for robust hardness results for learning problems

Quantum computation: quantum algorithms can efficiently solve learning problems which classical algorithms provably cannot


Registration HintsRegistration Hints

MS/PhD students should register for 15 points exactly. Up to 6 points, in very rare cases up to 9 points, should be in regular courses (4000 or 6000 level only), with the rest in E9911 Graduate Research II (ignore E9910 Graduate Research I).

PhD students (post-MS) should register for one RU. No points are necessary, unless taking regular courses (4000 or 6000 level). Again, usually at most 6 and rarely up to 9 points in regular courses.

MS GRAs must consult with their faculty advisors before registering, for 12-15 points, in most cases restricted to max 6 points in regular courses and the rest in some combination of 6900/6901/6902.

Get faculty advisor approval for all regular course registrations!

PhD students without advisors should contact Prof. Kaiser ([email protected])


CRF (Computing Research Facilities)CRF (Computing Research Facilities)http://www.cs.columbia.edu/~crf/http://www.cs.columbia.edu/~crf/

Director: Daisy Nguyen Senior system administrator

Mark Yeun Dennis Shim

Primary support system administrator Sarmistha (“Manu”) Dutta Anupam Mohanty (“Sonu”)


CRF supportsCRF supports

Desktops:

Windows Linux dual boot Windows + Linux Solaris on Sun workstations we do not support Macs

Servers: file servers (NFS, Samba) mail (IMAP, POP, Unix mail) DNS web print services Sun and Linux research servers Windows Domain Controller SMS

Mail readers: pine, mh, Netscape, Mail, mail,

mulberry, etc.

Software: Matlab, Mathematica, Splus,

CVS, Acrobat Reader, Distiller, ghostview,Winzip, MS Office, Virus checker, ssh, X environment, Emacs, etc.


CRF systemsCRF systems

RAID file servers

DNS

webmail server NIS

Domain Controller

SMS

dynasty

playdisco

diamondflame

Solariscluster

Research Machines

cluster-pc

Linux

compute server


CUCS Computer Labs and CUCS Computer Labs and FacilitiesFacilities

Compute servers for remote login (ssh): cluster (Solaris) cluster-pc (Linux)

No VPN needed – just use ssh CRF does not offer modem dial-in use

Columbia facilities or commercial ISP Two laboratories for classes and projects:

CLIC (CSB 486) 30 Linux workstations

MRL (across from receptionist) 30 Windows 2000 workstations

Teaching laboratory for networks INTEREST lab routers, nodes, Ethernet switches


Contacting CRFContacting CRF

Send request (“ticket”) to [email protected] Check status of tickets on CRF web page:

http://www.cs.columbia.edu/~crf Normal ticket: daily requests

install new software or machine non-critical software or hardware problems send ticket, will get response and updates

Urgent ticket: requests that need attention ASAP your machine is down send ticket, then call CRF

Emergency ticket: mail down power lost entire computing system down call us immediately anytime


CRF contact informationCRF contact information

Hotline (working hours): x7174Daisy: x7140, x7039, 347-782-2345

(cell), 908-286-1139 (home)Mark: x7036, 917-449-4139 (cell)Dennis: x7035, 646-286-9769 (cell)Manu: x7034, 973-713-7583 (cell)Sonu: x7032, 917-538-5909 (cell)

cs orientation - fall 2004 the department of computer science at columbia university henning...

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