Computer Science & Artificial Intelligence
Software, algorithms, machine learning, intelligent systems, and human-AI collaboration.
Computing, Communication & EnterpriseBuilding intelligent systems, meaningful stories, and enterprise solutions.
Computing, Communication & Innovation
Disciplinary strength connected to wider systems.
Computing, Communication & Enterprise studies how information is represented, processed, communicated, governed, and transformed into useful systems and institutions. The division connects software, AI, data science, visualization, publishing, design, entrepreneurship, and organizational strategy.
Departments
Fields of study and practice
Departments organize disciplinary identity, curriculum, faculty appointments, and research methods within the division.
Data Science & Research Computing
Data engineering, analysis, visualization, reproducibility, simulation, and computational methods.
Communication, Publishing & Public Scholarship
Writing, editing, design, journals, books, media, public knowledge, and audience engagement.
Enterprise, Innovation & Technology Management
Venture formation, product strategy, operations, e-commerce, finance, and organizational design.
Questions & domains
What the division studies
- Computer science, software systems, artificial intelligence, and machine learning
- Data management, research computing, visualization, and reproducible workflows
- Communication, public scholarship, publishing, media, and knowledge infrastructure
- Enterprise formation, innovation, e-commerce, technology strategy, and operations
- Complex adaptive systems, networks, simulation, and decision environments
Methods
How knowledge is produced
- Programming, software architecture, model development, and systems testing
- Data engineering, statistical computing, visualization, and computational notebooks
- Human-centered design, writing, editing, publishing, and audience research
- Market, organizational, financial, and product analysis
- Simulation, network methods, agent-based modeling, and scenario design
Outputs
What students and faculty create
- Software, data products, dashboards, models, visualizations, and digital tools
- Articles, journals, books, reports, exhibits, and public knowledge platforms
- Business models, product plans, operational systems, and venture prototypes
- Theses, dissertations, capstones, portfolios, and applied computational research
Programs
Academic pathways in Computing, Communication & Enterprise
Degree programs
Computational Intelligence & Data Systems
Combines computer science, AI, data engineering, research computing, visualization, systems thinking, and responsible application.
Four academic yearsOn-campus and hybrid with computing laboratories
View pathway →Communication, Public Scholarship & Digital Media
Connects writing, research, design, publishing, media, public knowledge, audience, and digital systems.
Four academic yearsOn-campus and hybrid with publishing and media studios
View pathway →
Applied AI, Research Computing & Visualization
Advanced computational methods for research, data-intensive inquiry, AI systems, visualization, reproducibility, and decision environments.
Two academic yearsHybrid graduate seminars and computing studios
View pathway →Technology Enterprise & Innovation
Connects technology strategy, venture design, product development, organizational systems, finance, partnerships, and responsible growth.
Two academic yearsHybrid graduate seminars, studios, and applied projects
View pathway →
Computational Systems, Communication & Enterprise
Original research on computational systems and the institutions, communications, markets, and human environments through which they operate.
Four to six academic yearsResidency, hybrid seminars, computational research, and applied environments
View pathway →Certificates
Research Computing & Visualization
Programming, reproducible analysis, data systems, scientific visualization, computational notebooks, and research software practice.
Two to four semestersHybrid with applied laboratory, field, studio, or computing work
View pathway →Complex Adaptive Systems
Emergence, feedback, adaptation, networks, agent interaction, simulation, resilience, and cross-scale systems reasoning.
Two to four semestersHybrid with applied laboratory, field, studio, or computing work
View pathway →Scientific Publishing & Methodological Communication
Research writing, methodological notes, peer review, editorial workflow, reproducibility, public scholarship, and publication production.
Two to four semestersHybrid with applied laboratory, field, studio, or computing work
View pathway →
Applied Artificial Intelligence
Machine learning, language and multimodal models, retrieval, tools, evaluation, governance, and operational AI systems.
Two to four semestersHybrid with applied laboratory, field, studio, or computing work
View pathway →Data Stewardship & Reproducible Research
Data structure, metadata, provenance, validation, versioning, privacy, repositories, and reproducible computational workflows.
Two to four semestersHybrid with applied laboratory, field, studio, or computing work
View pathway →
Research Data Stewardship
A compact credential in reproducible data organization, metadata, documentation, preservation, access control, and responsible research reuse.
One semesterHybrid computing studio
View pathway →Field, laboratory & professional intensives
Research Computing Bootcamp
A concentrated workflow in programming, data management, notebooks, visualization, version control, and reproducible research.
One to six weeksConcentrated field, laboratory, studio, or hybrid format
View pathway →Scientific Publishing Studio
A manuscript-to-publication studio covering structure, evidence, figures, citations, methods, peer review, accessibility, and production.
One to six weeksConcentrated field, laboratory, studio, or hybrid format
View pathway →Courses
Selected courses
CS-110
Computational Thinking & Programming
Introduces programming, algorithms, data, abstraction, testing, and computational problem solving through research and applied examples.
- Credits
- 3.0
- Contact hours
- 45.0
AI-210
Machine Learning Foundations
Introduces supervised and unsupervised learning, model evaluation, features, data quality, bias, and responsible application.
- Credits
- 3.0
- Contact hours
- 45.0
AI-330
Applied AI Systems
Builds AI-enabled applications using models, retrieval, tools, evaluation, guardrails, and human review within a documented system architecture.
- Credits
- 3.0
- Contact hours
- 45.0
DATA-220
Data Management & Reproducible Research
Develops durable data structures, metadata, versioning, cleaning, provenance, documentation, and reproducible analysis workflows.
- Credits
- 3.0
- Contact hours
- 45.0
RC-310
Research Computing & Visualization
Uses computational notebooks, scripting, visualization, statistical workflows, and research software practices to analyze and communicate complex evidence.
- Credits
- 3.0
- Contact hours
- 45.0
CAS-330
Complex Adaptive Systems
Examines emergence, feedback, adaptation, networks, path dependence, scale, and agent interaction across social, biological, environmental, and technological systems.
- Credits
- 3.0
- Contact hours
- 45.0
PUB-320
Scientific Communication & Public Scholarship
Develops clear, accurate, accessible communication across research articles, public writing, visual explanation, presentations, and digital media.
- Credits
- 3.0
- Contact hours
- 45.0
RES-500
Methodological Notes Studio
Produces concise, transparent methodological publications that document workflows, adaptations, validation, failures, and reusable research practice.
- Credits
- 3.0
- Contact hours
- 45.0
Academic leadership & faculty
People and appointments
Academic inquiry
Connect your interests to a program, department, course, or research environment.
Admissions can help identify the most appropriate pathway across the division.