Transcript MIS Future - Artificial Intelligence Laboratory

MIS Research:
Past, Present and Future
(My Biased View)
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My Background
 NCTU  SUNY Buffalo  NYU  U Arizona (MIS #4)
 MS, MIS, Design Science, AI, Search Engine, Digital
Library, Medical Informatics, Intelligence & Security
Informatics, Business Intelligence
 AI Lab, 25+ researchers; $25M funding ($1.5M/year), 180
top SCI papers (20+ papers/year); DL (#1), MIS (#8);
Scientific Advisor: NLC, NLM, Academia Sinica; Chair,
ICADL, IEEE ISI
 AE in ten top SCI journals, IEEE and AAAS Fellow
 DL/SE; GeneScene & BioPortal; COPLINK & Dark Web
(NYT, USA Today, Associated Press, etc.); Knowledge
Computing Corporation ($100M)
Management Information
Systems
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What is MIS?
 It’s in the name!
 Management
 Information
 Systems
 Not simply computer science, management
science, organizational behavioral, economics
modeling, etc…
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MIS Past: Departments and Founding
Fathers
 University of Minnesota, founded in 1975
 University of Arizona, founded in 1977
 Dr. Gordon Davis, U of Minnesota  Behavioral
and Organizational Research
 Dr. Jay Nunamaker, U. of Arizona  Systems
and Technical Research
 Dr. Andy Whinston, U. of Texas at Austin,
Purdue U.  Economics and Modeling
Research
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Top Five UA MIS Programs
MIT: economics, social, IT consulting
CMU: economics, MS/OR, social
UT Austin: economics, MS/OR
Arizona: system, technical
Minnesota: behavioral, organizational
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Andersen Consulting 1999 Market Analysis
UA-MIS is highly ranked versus competitors and
has the broadest scope - Andersen Consulting Report
MBA Program: 180 Students
BS Program: 1100 Majors
Broad
UofA
Broad
NYU
UofA
Michigan
MIT
Texas
Scope
Scope
Michigan
Texas
ASU
Minnesota
MIT
ASU
Minnesota
Carnegie Mellon
Carnegie Mellon
U Penn
Narrow
Narrow
Ranking
High
NYU
Broad
UofA
MIT
ASU
Berkeley
UofA
Scope
Scope
Michigan
Carnegie Mellon
Illinois
NYU
Texas
Minnesota
Stanford
Irvine
Carnegie Mellon
Narrow
High
Ranking
Low
PhD Program: 35 Students
MS Program: 90 Students
Broad
Ranking
High
Low
Low
Narrow
High
Ranking
Low
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Major (Pure) MIS Journals
 MISQ: Behavioral/Organizational
 Information Systems Research:
Behavioral,/Organizational, Economics, some
Systems
 Management Science: MS, Modeling, some
Systems
 J of MIS: Behavioral/Organizational, Economics,
some Systems
 Decision Support Systems: mostly Systems
 Others: Decision Sciences, Information Systems,
etc.
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Other Major MIS Related (Technical)
Journals
 ACM: CACM (IT), ACM Trans. On Information
Systems (IR)
 IEEE: Computer (IT), TKDE (database), SMC
(cybernetics), TITB (biomedicine), Technology
Management, Intelligent Systems (AI)
 ASIS: JASIST
 Other technical journals: IJHCS, IPM, JBI, etc.
 Others: Many in Economics, Management,
Management Science, Accounting, Finance,
Marketing, etc.
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Major MIS Conference: ICIS
 Managed by AIS
 1000-1400 participants from US, Europe, and Asia
 High quality papers, job search
 20 tracks, major submissions in behavioral,
organizational, economics tracks
 ICIS 2008, Paris
 ICIS 2009, Phoenix, Arizona; Conference Chairs:
Nunamaker and Currie; Program Chairs: Chen and
Slaughter
 New tracks: Web 2.0, Web Mining, Service
Computing, Biomedical, etc.
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MIS: Good
 IT the fabric of all organizations
 MIS has evolved from EDP (book keeping) to the
backbone of all business operations
 MIS has matured as a discipline in breadth and
depth
 MIS has become a department in most major
business schools
 Major journals and conference well regarded
 Ph.D. students academic placement stable; BS/MS
students IT company placement good
 US faculty salary higher than peer groups (CS,
Economics, Management, etc.)
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MIS: Bad and Ugly
 MIS is not a major part of IT revolution; computer science
is (GDSS/TAM vs. PC/Unix/Internet)
 MIS has not gained respect in scientific academic world
(little federal funding or contribution)
 MIS has not gained respect in businesses or business
schools (little contribution or relevance to business; TAM
vs. CAPM; IS dept removed from major b-schools)
 MIS discipline is narrow and in-breeding (MISQ and ISR too
behavior and economics centric; few MIS faculty are
known outside of MIS)
 MIS curriculum is soft and out of date (few companies
need behavioral or economics BS/MS graduates; too much
theory too little substance; need to get back to core of
M.I.S.)
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MIS: Future and Opportunities
 MIS curriculum needs to be relevant to
management (business subject courses,
organizations), information (DBMS, data mining,
knowledge management, Web contents), systems
(supply-chain, ERP, Internet, Web 2.0 apps)
 MIS scholars need to go beyond MIS and compete
in the broader academic world (CS, Economics,
Management, etc.)
 MIS research needs to be relevant and useful to
businesses
 MIS vs. CS  Stick to our strengths:
management, information, and systems!!!
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MIS Future: Recommendations
 Curriculum: Some business and behavioral
courses; Need many hands-on database, web
computing, business systems (CRM, ERP)
courses; Need hand-on development projects and
interns
 Research: What are the emerging topics (Web 2.0,
forums/blogs, etc.)? NSF proposals and funding
(innovative and fundable); Identify unique
approach (systems vs. algorithms)
 Impact: Work with other subject experts (business,
biomedicine, security, etc.); Identify and solve new
problems; Is it news-worthy (NYT, USA Today,
Newsweek)?
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University of Arizona
Management Information
Systems
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Vision for UA-MIS
To establish leadership in information
technology education, research and
outreach that accentuate innovation,
hands-on experience and strategic values
of information management, intelligence
and technology.
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Historical Overview
 BS, MS and Ph.D. programs were first offered in
1974.
 The department was established in 1977. 30th year
celebration in 2004
 15 faculty members, 45 Ph.D., 60 MS, 80 MBA, 600
BS students
 Unique values of our program
 Successful innovations and technology transfer
 Hands-on learning about synergies among development,
application and management
 Applied and relevant
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MIS Recognition
 US News & World Report: ranked among top 5
programs for more than 15 consecutive years
 External Peer Review (1998): “a jewel”
 Decision Line rankings (1998, 1999):
Dept. research productivity: #1 by far
Dr. Nunamaker: #2
Comm. of AIS (2005):
Institution publication productivity: #4
Dr. Nunamaker #6; Dr. Chen #8
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Faculty
15 faculty members
Total Research Funding: $80+ million
Pioneers and leaders in
Collaboration technology and science
Knowledge management and artificial
intelligence
Large scale data management and mining
Economics and technology management issues
Featured in Fortune, Business Week, Forbes,
Sciences and New York Times articles
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UA-MIS Board of Advisors
Provide guidance and support
Established in summer 1998
Inkind, scholarship, infrastructure and fund
donations exceeding $10 million
Members include:
AOL, Ameristar Casinos, Andersen Consulting,
Arthur Andersen, Cap Gemini, Cargill, Commerce
One, Compaq, EMC2, Farmers Insurance, HP,
Harvard Group, Honeywell, IBM, IFS, Intel,
Oracle, PWC, Raytheon, RCM Technologies,
SoftQuad, Ultralife Batteries
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Partnership Outcomes
Mark and Susan Hoffman E-Commerce Lab
Harvard Group and Honeywell Scholarships
E-business Executive education program
Specialized co-op program
Student and faculty projects
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Major UA/MIS Research Centers
 Center for the Management of Information (CMI):
Collaborative computing and deception detection
research
 Artificial Intelligence Lab: Knowledge management
and web computing research
 Hoffman E-Commerce Lab: E-Commerce and
Internet computing research, education, outreach
 Advanced Database Research Group: Data
modeling and management research
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UA/MIS Research Focuses:
Technical/system: artificial intelligence, web
computing, GDSS, databases
Management sciences/OR: workflow, supplychain, project management
Information economics: auctioning, modeling
Social/behavioral/cognitive: social impacts,
computer-mediated communication, humancomputer interactions (HCI)
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AI Lab Background
 Founded in 1989
 Excellence in Digital Library, Web Intelligence and
Mining, Biomedical Informatics, and Security and
Intelligence Informatics
 Funding, $25M: federal (NSF, NIH, NIJ, DARPA, CIA,
DHS, etc.) and industries (SAP, HP, IBM, etc.)
 30+ researchers: 6 full-time researchers/staff, 12
Ph.D. students, 12 MS/BS students (and 10+
affiliated faculty)
 Research infrastructure: NT/UNIX/Linux
workstations, servers, supercomputers (SGI);
Java/C/C++, DBMS (Oracle/MS SQL), web protocols24
AI Lab Research Methodologies
 Databases, knowledge bases, ontologies
(Database)
 Data mining and statistical analysis (Algorithm)
 Text mining and natural language processing
(Linguistics)
 Web mining, search engines, and recommender
systems (Web)
 Information systems design and humancomputer interactions (HCI)
 Visualization and human factors (Visualization)
 System evaluation (Evaluation)
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AI Lab Projects: Web Intelligence and
Mining
 Digital library, intelligent searching, multi-lingual
support, post-retrieval analysis, knowledge map
visualization
 Scientific portals: NanoPort (for Nano Technology),
DGPort (for digital government)
 Intelligence portals: (English/Chinese) business
intelligence and medical intelligence,
Spanish/Arabic
 CMC visualization by Glyphs, MDS/SOM
visualization for financial management and Internet
survey, financial data/text mining, GetSmart elearning concept map, recommender systems
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AI Lab Projects: Biomedical Informatics
 Biomedical data and text mining, gene pathway
analysis, medical ontologies, GeneArray analysis,
biosurveillance
 HelpfulMed and MedTextus; Arizona Pathway
Visualizer; BioPortal for disease informatics
 Gene pathway text mining, computational
linguistics, GeneArray data mining, clustering,
Medical knowledge visualization, pathway modeling
and display
 Infectious disease and bioagent information
sharing, analysis, and visualization, hotspot
analysis, spatio-temporal visualization
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Medical Informatics:
The computational,
algorithmic, database
and informationcentric approach to
the study of medical
and health care
problems.
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AI Lab Projects: Intelligence and Security
Informatics
 Public safety and intelligence information sharing
and analysis, social network analysis, data/text
mining
 COPLINK, BorderSafe, Dark Web
 Criminal and terrorism social network analysis
(SNA): centrality, block-modeling, clustering
 Criminal and terrorism data/text mining: criminal
element association mining and clustering (time,
place, objects); deception detection
 Terrorism link, content, authorship, sentiment
analysis
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Intelligence and Security
Informatics (ISI):
Development of
advanced information
technologies, systems,
algorithms, and
databases for national
security related
applications, through an
integrated technological,
organizational, and
policy-based approach.
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Research Opportunities
 Ph.D. Program: excellent GPA (top 5 in class),
strong GRE/GMAT (top 5%), strong research record,
strong faculty personal recommendation ($18,000
annual financial support, 5 years)  become
professor ($100,000 + 2/9)
 MS Program: good GPA and GRE/GMAT (top 10%),
good recommendation (good chance for financial
support after first semester, $14,000 per year, 2
years)  become IT professional ($60,000)
 Need good to excellent English communication
skills (speaking and writing)
 Joint faculty research, sabbatical exchange, visitor
program
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ICIS 2009 program participation and
involvement opportunities!!!
Faculty visit and collaboration
opportunities!!!
Recruiting new Ph.D. and MS
Students!!!
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For more information
Eller College: http://eller.arizona.edu
AI Lab: http://ai.arizona.edu
Hsinchun Chen:
[email protected]
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