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Overview of Network


Overview of Network & Complex Systems Courses at IUB. Computer Networks by Minaxi Gupta, ... Overview of Network & Complex Systems Courses at IUB. ... – PowerPoint PPT presentation

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Title: Overview of Network

  • Overview of Network Complex Systems
  • Courses at IUB
  • IUB Faculty
  • Network Complex Systems Talk, September 3rd,

  • CSCI P538 Computer Networks by Minaxi Gupta,
    Computer Science
  • I590, I400 and I-H400 Systems Biology A User's
    Guide by Santiago Schnell, Informatics
  • INFO-I 400/590 Biologically Inspired Computing by
    Luis Rocha, Informatics
  • COGS-Q700 Evolution and Analysis of
    Brain-Body-Environment Systems by Randy Beer,
  • Sustainable Development Systems by Tom Evans,
  • S604 The Semantic Web by John Paolillo, SLIS
  • S660 Social Networks in Sociology by Bernice
    Pescosolido, Sociology
  • L600 Networks Complex Systems talks Katy
    Börner, SLIS

Computer Networks by Minaxi Gupta, Computer
  • Fall 2007 CSCI P538 (3 credits)
  • Computer Networks
  • Time/Venue Tue, Thu 930am-1045am in GL101
  • Textbook Computer Networks A Systems Approach
  • by Peterson and Davie, 4th edition
  • The goal of this course is to learn about
    computer networks. We will do so by
    understanding how
  • computer networks work today and why they are
    designed the way they are. The course will
  • primarily focus on the Internet but will also
    cover other past and present network technologies
  • put things in perspective.
  • The course emphasizes practice. The programming
    projects are derived from
  • real-world operational and security issues facing
    todays Internet.
  • Course load 6-8 assignments, 2 exams, 3-5
    projects to be done in groups of two
  • 20 Students (mostly from CS and Informatics)
  • P538 is jointly offered with P438 this year

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INFO-I 400/590 Biologically Inspired Computing by
Luis Rocha, Informatics
  • What is Life?
  • What is Computation?
  • Imitation of Life
  • Artificial Life and Complex Systems
  • Evolutionary Algorithms
  • Learning
  • Collective Behavior
  • Computer Immune Systems
  • Bio-inspired Artifacts
  • Bio-inspired algorithms in Computational Biology
  • Computing with Natural Means

Web page http//informatics.indiana.edu/rocha/i-bi
c Blog http//life-inspired.blogspot.com/
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The Semantic Web by John Paolillo,
  • SLIS L597 Topics In Library and Information
    Science, 3 credits
  • Thursdays, 545-830 PM, LI 002
  • Format Lecture/discussion lab student
  • This course covers
  • Aims and goals of the Semantic Web
  • Technologies used in implementing the Semantic
  • Markup languages (XML, RDF)
  • Vocabularies (RDF-S, OWL, FOAF, RSS, etc.)
  • Metadata standards (W3C)
  • Query languages (RDQL and related)
  • Platforms for storage and use of SW data (Sesame,
  • Applications of Semantic Web data
  • Weblogs, online communities, social networking
    sites, folksonomies, multimedia, etc.
  • Emergent Semantics of Metadata
  • What is the ultimate outcome of the adoption of
    Semantic Web technologies?
  • Course structure Readings, exercises in using
    and processing Semantic Web data, final project
    and presentation.

  • S660 Social Networks in Sociology by Bernice
    Pescosolido, Sociology

L600 Networks Complex Systems talks Katy
Börner, SLIS
  • SLIS graduate course, 1 credit
  • Time Mon 6-7p in the Wells (Main) Library, Room
  • Grading is based on the attendance of 8 talks
    (sign-up sheets will be provided) and a 4-5 page
    write-up that synergizes/aggregates major points
    made by a subset of the speakers to be submitted
    at the end of the semester.
  • Class Webpage http//vw.indiana.edu/talks-fall07/

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Other Related Courses that might NOT be taught in
Fall 2007
  • Artificial Life as Approach to AI by Larry
    Yaeger, Informatics
  • Agent-Based Modeling and GIS by Hamid Ekbia, SLIS
    (Summer and Fall 08)
  • P448/P548/M448/M548 Mathematical Biology by James
    Glazier, Physics (Spring 08)
  • Social Network Analysis by Stanley Wasserman,
    Sociology Psychology
  • S651 Network Analysis by Stan Wasserman,
    Statistics, Sociology, Psychological and Brain
  • Complex Adaptive Systems by Eliot Smith Robert
    Goldstone, Psychology
  • The Simplicity of Complexity by Alessandro
    Vespignani Alessandro Flammini, Informatics
  • I601 Introduction to Complexity by Alessandro
    Vespignani Alessandro Flammini, Informatics
  • Web Mining by Filippo Menczer, Informatics
  • Fundamentals of Computer Networks by Beth Plale,
    Computer Science
  • Internet Services Protocols by Minaxi Gupta,
    Computer Science
  • I400/I590 (cross-listed in Cognitive Science)
    Seek and Find Search Strategies in Space and
    Time by Peter M. Todd, Informatics Psychological
    and Brain Sciences
  • P582 Biological and Artificial Neural Networks by
    John Beggs, Physics
  • I690 Mathematical Methods for Informatics by
    Santiago Schnell, Informatics
  • COGS-Q580 An Introduction to Dynamical Systems in
    Cognitive Science by Randall Beer, Cognitive
    Science, Computer Science, and Informatics at IU
  • 400/590 Structure of Information Environments by
    Peter Todd, Psychology Informatics
  • S604 Structural Data Mining Modeling by Katy
    Börner, SLIS
  • S637 Information Visualization by Katy Börner,
    SLIS (Spring 08)

(No Transcript)
Seek and Find Search strategies inspace and
time by Peter Todd, Informatics/Cognitive Science
  • Informatics I400/I590 Topics course
    (grad/undergrad), cross-listed in Cognitive
    Science Tu-Th 1-215 pm, Informatics 107 3
  • Format Discussion of papers presentations led
    by students.
  • This course covers
  • Strategies that humans (and other animals) use to
    decide where and how to search and when to stop
    searching, in a variety of domains including
  • foraging for food in the wild
  • foraging for information on the Web
  • shopping for a bargain
  • looking for a parking space
  • seeking a job
  • searching for a mate
  • Emergent patterns that arise when many
    individuals look for things at the same time
  • Co-adaptation of strategies for searching and
    strategies for hiding (or being found)
  • How computational tools can be built using these
    ideas to help people do a better job at finding
    what they seek.
  • Course structure Students read papers for each
    class and come up with discussion questions for
    each one, and research and present a particular
    topic on search and develop a Wiki page on that
    topic. Papers will be distributed in class.
  • Class webpage in OnCourse CL

Biological and Artificial Neural Networks by
John Beggs, Physics
  • P 582 Biological and Artificial Neural Networks,
    3 credits
  • Format Three weekly classes, regular homework,
    and a final project presentation.
  • Meetings Mon, Wed, Fri 125p-215p in Swain
    West 218
  • Text Neural Networks, an introduction, by
    Muller, Reinhardt, and Strickland
  • We will first cover the biological details of
    neurons that are thought to be computationally
    relevant. Next we will explore major artificial
    neural network theories and models, many of which
    draw from statistical physics. Finally, we will
    cover experimental data from living neural
    networks and critically evaluate neural network
    theories that claim to describe biological

The Simplicity of Complexity by Alessandro
Vespignani Alessandro Flammini, Informatics
  • INFO I690 (soon to become I601) 3 credits
  • Introduction to Complex Systems
  • Format Two weekly classes, bi-weekly
    assignments, final project presentation.
  • Time Tue, Thu 930a-1045a in G L101
  • 16 Students ( from Informatics, but also
    Phys, Chem., Bio, CS, Math)
  • ..The course is meant to provide a set of
    interpretative tools, both theoretical and
    computational, that will help to better describe,
    model and understand Complexityas we perceive it
    today, the final aim being able to see the
    "unifying picture" beyond the foggy curtain of
    peculiaritities that individual complex system
    may display..

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