Overview of Network & Complex Systems Courses at IUB IUB Faculty Network & Complex Systems Talk, August 29, 2005

Overview of Network & Complex Systems Courses at IUB. Overview  P582 Biological and Artificial Neural Networks by John Beggs, PhysicsJohn Beggs  Artificial Life as Approach to AI by Larry Yaeger, Informatics Artificial Life as Approach to AILarry Yaeger  INFO-I 400/590 Biologically Inspired Computing by Luis Rocha, Informatics INFO-I 400/590 Biologically Inspired Computing  The Simplicity of Complexity by Alessandro Vespignani & Alessandro Flammini, Informatics The Simplicity of ComplexityAlessandro VespignaniAlessandro Flammini  TEL603: Communication Networks by J. Alison Bryant, Telecommunications TEL603: Communication NetworksJ. Alison Bryant  400/590 Structure of Information Environments by Peter Todd, Psychology & Informatics  CS B538 Computer Networks by Minaxi Gupta, Computer Science CS B538 Computer NetworksMinaxi Gupta  L597 Structural Data Mining & Modeling by Katy Börner, SLIS L597 Structural Data Mining & ModelingKaty Börner  L600 Networks & Complex Systems talks Katy Börner, SLISNetworks & Complex Systems Katy Börner

Overview of Network & Complex Systems Courses at IUB. 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 1:25p-2:15p 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 phenomena.

Overview of Network & Complex Systems Courses at IUB. Artificial Life as approach to AI Artificial Life as approach to AI by Larry Yaeger, InformaticsLarry Yaeger Informatics I400/I590 Topics course (grad/undergrad), 3 credits Format: Weekly lecture and discussion. One class project, one presentation, three or four exams (can drop one). This course covers  Bottom-up design informed by top-down analysis  Definitions and quantifications of life and intelligence  Genetic algorithms  Neural networks  The evolution of learning  Intelligence as an emergent property  Computational ecologies / artificial worlds  Information theory and complexity measures Students do weekly readings, provide a presentation on one reading, prepare a project, and participate in class & online discussion. All reading materials are online, except the required text: Valentino Braitenberg’s Vehicles: Experiments in Synthetic Psychology Class Webpage: Class list:

Overview of Network & Complex Systems Courses at IUB. 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 Blog

Overview of Network & Complex Systems Courses at IUB. Communication Networks by J. Alison Bryant, TelecommunicationsJ. Alison Bryant TEL graduate course, 3 credits Format: Lecture/discussion with 2-3 in-class labs throughout the semester. 2-3 assignments and a course paper. This seminar is intended to:  focus on network formulations of selected communication, organizational, social-psychological, and sociological theories  review theoretical, conceptual, and analytic issues associated with network perspectives on communication  emphasize the influences and consequences of communication patterns, processes, and content Text: Monge, P.R., & Contractor, N.S. (2003). Theories of Communication Networks. New York: Oxford. This course will be taught Fall 2005 as TEL 603.

Overview of Network & Complex Systems Courses at IUB. Structure of Information Environments by Peter Todd, Informatics/Cog.Sci. Informatics I400/I590 Topics course (grad/undergrad), cross-listed in Cognitive Science; Tu-Th 1-2:15 pm, Business 209; 3 credits Format: Discussion of papers; presentations led by students. This course covers:  How information is structured in environments that people encounter: cues, distributions, sequential patterns, etc.  Ways of describing information patterns  How decision mechanisms take advantage of information structure  How people create information structure intentionally and unintentionally  Structure in social, cultural, and institutional environments  How to create information structure to aid human decision making Course structure: Students read papers for each class and come up with discussion questions for each one, present one or two papers during the term and lead the discussion around everyone’s questions, and critically evaluate one paper in writing. Papers will be distributed in class. Class webpage in OnCourse CL

Overview of Network & Complex Systems Courses at IUB. The Simplicity of ComplexityThe Simplicity of Complexity by Alessandro Vespignani & Alessandro Flammini, InformaticsAlessandro VespignaniAlessandro Flammini INFO 400/590 Topics in Informatics, 3 credits Format: Two weekly classes and two bring-home assignments and a final project presentation. Time: Mon, Wed 1:00p-2:15p in SY Students : 10 undergrads (all Info) 6 grads ( 1I+1CS+4PHY) “…..The course is meant to provide a set of interpretative tools, both theoretical and computational, that will help to better describe, model and understand Complexity as 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…..

FRACTALS CHAOS EMERGENT BEHAVIOR NETWORKS MODELING & SIMULATION COMPLEX SYSTEMS STRANGE ATTRACTORS SCALE INVARIANCE ORDER FROM DISORDER COMPUTATION RECURSIVITY COMPLEX ARCHITECTURE

Overview of Network & Complex Systems Courses at IUB. Communication Networks by J. Alison Bryant, TelecommunicationsJ. Alison Bryant TEL graduate course, 3 credits Format: Lecture/discussion with 2-3 in-class labs throughout the semester. 2-3 assignments and a course paper. This seminar is intended to:  review theoretical, conceptual, and analytic issues associated with network perspectives on social interaction and communication  focus on network formulations of selected communication, organizational, social- psychological, and sociological theories  approach social science from multi-level, multi-theoretical network perspective  discuss how to use network theory as a starting point for network research Text: Monge, P.R., & Contractor, N.S. (2003). Theories of Communication Networks. New York: Oxford. Tuesdays, 9:30am-12:00pm RTV 169 This course begins tomorrow.

Overview of Network & Complex Systems Courses at IUB. CSCI B538: Computer Networks Minaxi Gupta, Computer Science Dept Minaxi Gupta CS graduate course (3 credits) Time/Venue: Tue/Thur 8:00-9:15am, LH 102 Prerequisites: a undergraduate networking/OS course, programming experience Textbook: Computer Networks: A Systems Approach (Peterson and Davie, IIIrd ed) Goals: To understand the design principles of the Internet. The course will follow a bottom-up approach, covering prominent link, network, and transport layer technologies, and the applications that shape the Internet. New this year: Internet-wide measurements as class projects, using Planet-lab infrastructure! Grading:  Midterm: 15%  Final: 15%  Written assignments: 15%  Projects: 45% (15% for each of the three projects)  Class participation/summaries: 10% Class Website:

Overview of Network & Complex Systems Courses at IUB. L597 Structural Data Mining & Modeling by Katy Börner, SLISStructural Data Mining & ModelingKaty Börner SLIS graduate course, 3 credits Time: Tue 1p-3:45p, LI036 Format: Lectures and 4-5 labs. Four class projects and two class presentations. This course  Introduces students to major methods, theories, and applications of structural data mining and modeling.  Covers elementary graph theory and matrix algebra, data collection, structural data mining, data modeling, and applications. Upon taking this course students will be able to analyze and describe real networks (power grids, WWW, social networks, etc.) as well as relevant phenomena such as disease propagation, search, organizational performance, social power, and the diffusion of innovations. Class Webpage:

Overview of Network & Complex Systems Courses at IUB. L600 Networks & Complex Systems talks Katy Börner, SLISNetworks & Complex Systems Katy Börner SLIS graduate course, 1 credit Time: Mon 6-7p in the Informatics 901 E. 10th St., Room 107Informatics 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: