AI Bootcamp

  • Increase your competitiveness in grant applications.
  • See how AI can support your research efforts.
  • Learn by doing in hands-on workshops.

Date: Tuesdays and Thursdays
Time: 9 a.m. – Noon
Location: Powerhouse Energy Campus

Offering Two Tracks:

  • Track A: May 26 – June 30 (registration closed)
  • Track B: July 14 – August 18 (registration open)

Bootcamp Highlights

  • Tuesday is faculty-led instruction, while Thursday is guided build time.
  • Each week’s instruction builds on the previous week, culminating in Demo Day presentations.
  • During Bootcamp, participants will build a working AI-integrated prototype.
  • Weekly topics directly cover OVPR proposal goals: applied AI literacy, replicable curriculum, accelerated research, institutional infrastructure, and competitive positioning for external AI funding.

Frequently Asked Questions:

Who should register?

CSU researchers, faculty, graduate students, and ambitious undergraduates.

Do I need previous AI experience?

Some previous experience is helpful but not required.

Will Track A and Track B contain similar information?

Track B will closely follow the same schedule as Track A. Please only register for Track A or Track B (do not register for both).

How do I get to the Powerhouse?

We are just north of Old Town and are accessible via the MAX. We also offer free parking. 

Track A Schedule

Tuesday: Building Foundations

Presenters:

  • Bryan Wilson, Executive Director of the CSU Energy Institute, CSU Presidential Chair in Energy Innovation, Professor of Mechanical Engineering
  • Blake Teipel, Entrepreneur in Residence, CSU Energy Institute
  • Bruce Draper, Professor and Department Chair, Department of Computer Science at CSU

Thursday

  • Set up dev environments
  • Build their first working Q&A tool over a research document of their choosing

Tuesday: Applied AI for Energy

Presenter:

  • Jesse Burkhardt, Associate Professor in the Department of Agricultural and Resource Economics at Colorado State University 

Thursday: Guided Build Time

Tuesday: AI for Design and Optimization

Presenter:

  • Yinshuang Xiao, Assistant Professor of Systems Engineering at CSU

Thursday: Guided Build Time

Tuesday: Applied Deep Learning Methods

Presenter:

  • Tim Hansen, Associate Professor of Electrical and Computer Engineering at CSU

Thursday: Guided Build Time

Tuesday: Ensemble Models and Orchestration Layers

Presenter:

  • TBA

Thursday: Guided Build Time

Tuesday: Demo Day

  • Open to the public, participants will present their project.

Track B Schedule

Tuesday: 

  • Presenter: Bruce Draper, Professor and Department Chair, Department of Computer
  • Topics Covered: Opening + Foundations: AI/ML distinctions, adversarial AI, model evaluation

Thursday

  • Guided Build Time
  • Topics Covered: First API call / RAG pipeline over participant research document

Tuesday: Applied AI for Energy

  • Presenter: Jesse Burkhardt, Associate Professor in the Department of Agricultural and Resource Economics at Colorado State University 
  • Topics Covered: LLM-in action; Manuscript prep; Data analysis and applied lens to Deep Learning for Earth & Energy Data: classification, remote sensing, computer vision

Thursday: 

  • Guided Build Time

Tuesday: AI for Design and Optimization

  • Presenter: Daniel Herber, Assistant Professor of Systems Engineering at CSU
  • Topics Covered: AI for Design & Optimization: surrogate modeling, control co-design, AI-suggested DOE

Thursday:

  • Guided Build Time
  • Topics Covered: Graph construction + GCN/GraphSAGE training on participant research data

Tuesday: Applied Deep Learning Methods

Presenter:

  • Yinshuang Xiao, Assistant Professor of Systems Engineering at CSU
  • Topics Covered: GNNs and Graph Network Modeling: AI for networked engineering systems — infrastructure, transportation, power grids, sociotechnical network

Thursday:

  • Guided Build Time 

Tuesday: Ensemble Models and Orchestration Layers

  • Presenter: Tim Hansen, Associate Professor of Electrical and Computer Engineering at CSU
  • Topics Covered: SLM, Edge & Adaptive Control: fine-tuning, LoRA, quantization, on-device deployment

Thursday:

  • Presenter: Chris Atkinson, Professor, Mechanical and Aerospace Engineering
  • Topics Covered: SLM, Edge & Adaptive Control: fine-tuning, LoRA, quantization, on-device deployment

Tuesday: 

  • Demo Day: Open to the public, participants will present their project.