Rutgers AI/High Performance Computing Workshop

Rutgers AI/HPC Workshop: AI-Driven Research at Rutgers

REGISTRATION IS REQUIRED. SPACE IS LIMITED!

Register to attend: https://shprutgers.jotform.com/262576127488166

Agenda

Part I: The Vision & The Platform

Setting the stage for the new era of scientific discovery.

09:00 AM – 09:30 AM | Welcome & Opening Remarks

• Objectives for the day: From consumption to creation.
• The “AI Scientist” concept: Moving beyond chatbots to research agents.

09:30 AM – 10:15 AM | Session 1: AI’s Enhanced Role in Science and Research

• Shift from “AI as a Tool” to “AI as a Partner.”
• Case studies: Accelerating literature reviews, hypothesis generation, and experimental design.
• Discussion: How Generative AI is reshaping the scientific method itself.

10:15 AM – 11:00 AM | Session 2: Google Cloud for Science & Gemini’s Science Vision

• Introduction to the Gemini model family

Part II: Demonstrations & Application

Seeing the tools in action before taking the wheel.

11:15 AM – 12:00 PM | Session 3: Demo – Demonstration for HPC Applications

• Live Demo: Evolutionary algorithms optimizing High-Performance Computing (HPC) code.
• Showcase: Automating code discovery and performance tuning.
• Q&A: Integrating Alpha-based tools into existing TAMU workflows.

12:00 PM – 01:00 PM | Networking Lunch (provided)

Part III: Hands-On Labs (The “Builder” Phase)

Interactive sessions where attendees build real AI workflows.

01:00 PM – 02:30 PM | Session 4: Computer Systems Design with Google AI

• Objective: Co-design an AI accelerator chip using AI agents.
• Activity: The “Architect vs. Critic” Loop.
• Build an adversarial agent system to propose and critique memory hierarchies.
• Run JAX-based trace simulations (MoE workloads) driven by Vertex AI Vizier.
• Analyze the Pareto Frontier of the results using Gemini.
• Outcome: A data-backed specification for a 2026-era AI processor.

02:30 PM – 02:45 PM | Afternoon Break

02:45 PM – 04:15 PM | Session 5: Lab – Bioinformatics with Google AI Tools

• Objective: Accelerate genomic analysis or protein folding tasks.
• Activity: Using Gemini to parse complex biological datasets, generate analysis scripts (Python/R), and visualize protein structures (AlphaFold integration or similar).
• Outcome: A working prototype for a bio-data pipeline.

Part IV: Conclusion

04:15 PM – 04:30 PM | Closing & Next Steps

• Recap of tools used (Vertex AI, Vizier, Gemini).
• Final Q&A.