Ph.D. in Informatics - Complex Networks and Systems Track

Explore the science behind complex systems

If you’re curious about how systems work and how individual parts interact to shape the behavior of the whole, the Complex Networks and Systems (CNS) track could be a great fit. This track explores patterns and dynamics in everything from social networks and the human brain to financial markets and power grids.

You’ll apply your knowledge across disciplines like computer science, biology, physics, and the social sciences, tackling real-world problems such as predicting the spread of misinformation or uncovering drug interaction risks through social media data.

What you'll learn

The Complex Networks and Systems (CNS) track gives you the chance to study how parts of a system interact to shape overall behavior, whether in the brain, the internet, ecosystems, or social networks. With a strong interdisciplinary focus, the track connects ideas from computer science, physics, biology, math, and the social sciences. You'll work alongside faculty at Center for Complex Networks and Systems Research (CNetS) and Center for Social and Biomedical Complexity CSBC on real-world problems, like modeling disease spread or analyzing what makes online content go viral.

You'll learn from 11 core faculty members who advise across areas like complex networks, cognitive science, social media analytics, artificial intelligence, and more. Students in the CNS track come from diverse backgrounds but share a drive to build strong theoretical, computational, and technical skills. From the start, you'll be involved in research projects ranging from web mining to modeling biochemical systems. Graduates go on to top universities, research labs, and leading tech companies around the world.

  • A focused core of informatics coursework
  • Research and events training in complex networks and systems
  • Seminars such as colloquiums or talks organized by CNetS and the CSBC
  • A strong faculty-supervised research component

Track faculty

Jacob G. Foster
Track Director

Jacob G. Foster

 

Jisun An

Jisun An

Data Science with applications to journalism, politics, health, and computational social science.

Randall Beer

Randall Beer

Cognitive science, computational and theoretical biology. Understanding how coordinated behavior arises from the dynamical interaction of an animal’s nervous system; its body and its environment. Evolution and analysis of dynamical “nervous systems” for model agents neuro-mechanical modeling of animals, biologically-inspired robotics, and dynamical systems approaches to behavior and cognition.

Johan Bollen

Johan Bollen

Computational social science, social media analytics informetrics, and digital libraries, meme diffusion, markets and sentiment, metrics from usage data, science of science.

Alessandro Flammini

Alessandro Flammini

Computational social science, complex networks, online social media.

Santo Fortunato

Santo Fortunato

Statistical physics of social dynamics, Community structure in complex networks, Science of Science.

Haewoon Kwak

Haewoon Kwak

Social computing, computational social science, media bias, online harms, fairness and bio-sociotechnical systems, game analytics, esports.

Filippo Menczer

Filippo Menczer

Web science, social media, social networks, social computing, Web search and data mining, distributed and intelligent Web applications, and modeling of complex information networks.

Stasa Milojevic

Stasa Milojevic

Dynamics of science as a social and an intellectual (cognitive), science, technology, and societySTSTS), science of science, information science, network science, economics, sociology, philosophy, history.

Filippo Radicchi

Filippo Radicchi

Complex Networks and Systems, Data Science, Science of Science, Sport Analytics.

Alexander J. Stewart

Alexander J. Stewart

 

Madhurima Vardhan

Madhurima Vardhan

Specializing in computational health, Madhurima Vardhan leverages Generative Artificial Intelligence, High Performance Computing, and Physics-based modeling to advance personalized disease diagnosis and treatment. Her research is focussed on developing trustworthy and scalable AI models designed to aid clinical decision-making and non-invasive diagnosis. Her work emphasizes the creation of smart medicine technology using Large Language Models for the identification of novel disease biomarkers through clinical data mining, computational fluid dynamics, and the development of empathetic, AI-driven models that integrate behavioral science with patient physiology to enhance long-term patient wellness. 

Track guide

Required courses

A student must successfully complete ninety (90) credit hours of graduate-level course work. The specific track requirements are listed below.

  • I501: Introduction to Informatics (3 cr.)
  • I502: Human-Centered Research Methods in Informatics Health Informatics Core Requirements (3 cr.)

  • INFO I601 Introduction to Complex Systems (3 cr.)
  • INFO I606 Network Science (3 cr.)

  • INFO I609 Seminar I in Informatics: Complex Systems (3 cr.)
  • INFO I709 Seminar II in Informatics: Complex Systems (3 cr.)

NOTE: A student must take I609 and/or I709.

  • INFO I790 Informatics Research Rotation (3 cr.)

NOTE: A student must complete two rotations of I790. A third rotation will not count for course credit.

NOTE: These courses must be appropriate for a Ph.D. in Informatics.

NOTE: A student must complete an internal or external minor approved by the University Graduate School and the School. If a student selects an individualized minor, prior to taking courses, the University Graduate School must approve the proposed minor course list. There is no typical minor; however, students in the Complex Systems & Networks track often pursue a minor in Biology, Computer Science, or Statistics.

Thesis Reading and Research (minimum of 21 cr. and a maximum of 30 cr.)

  • INFO I890 Thesis Readings and Research

  • INFO I585 Biologically-inspired Computing
  • INFO I590 Topics in Informatics
  • CSCI B657 Computer Vision
  • COGS Q580 Introduction to Dynamical Systems in Cognitive Science

Qualifying exam

Written and oral examinations decided by program committee based on bibliography from I609, I709 and specific research interests of candidate. Typical written exam: three papers or one-week take home exam.

Typical minors

Cognitive Science, Statistics, Biophysics.

Sample dissertation titles

Abi-Haidar, AlaaAn Adaptive Document Classifier Inspired by T-cell Cross-regulation of the Immune System
Mourao, MarcioReconstructing the Mechanisms and the Dynamical Behavior Complex Biochemical Pathways
Conover, MichaelDigital Democracy: The Structure and Dynamics of Political Communication in a Large Scale Social Media Stream
Frey, SethComplex Collective Dynamics in Human Higher-Level Reasoning: A Study Over Multiple Methods
Kaur , JasleenEmergence of Innovation and Impact in Science
Kolchinsky, ArtemyMeasuring Scales: Integration and Modularity in Complex Systems
Mao , HuinaModeling Economic and Financial Behavior from Large-scale Datasets
Shuai, XinModeling Scholarly Communications Across Heterogeneous Corpra
Simas, TiagoStochastic Models And Transitivity In Complex Networks
Wang, ZhipingBiomedical Literature Mining For Pharmacokinetics Numerical Parameter Collection
Weng, LilianInformation Diffusion on Online Social Networks
Barron, Alexander T.J.Collective Creation of Identity and Institutions through the Lens of Language Innovation
Notarmuzi, DanieleInformation Diffusion in Online Social Media
Varol, OnurAnalyzing Social Big Data To Study Online Discourse And Its Manipulation
Yang, Kai-ChengSocial Media Bots: Detection, Characterization, and Human Perception, 2023

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