Registration is open until May 21st for workshops, the practical core of AI. From fundamentals to practical applications, it will be set on the city's campus from May 28th to 29th and is led by Hasan.
The workshop is designed for faculty who are beginning to apply Artificial Intelligence (AI) to their research and are beginning to ease their experience covering basic, practical tools and practical implementations. Day 1 will focus on understanding the possibilities of AI and choosing the right tools. Day 2 will provide a hands-on implementation with guided support for applying AI solutions. Participants who complete both sessions are eligible for mini-grants to support further implementation of AI over the summer of 2025.
Day 1
•Morning Session (9am to 11am): Part 1 – Basics
•Noon Session (11:30am – 12:30pm): Part 2 – Applications
Day 2
•Morning Session (9am to 11:30am): Part 3 – Practical Implementation
Part 1: Basics – AI Landscape Survey
Purpose: We introduce the concepts, technology and connections of core AI with engineering.
topic:
• Data type: structured, unstructured, time series
• Modern AI: Machine learning and deep learning
Focus: LLMS and VLM for engineering applications
Social Meaning and Limitations of AI
Part 2: Applications – AI Implementation Decision Framework
Purpose: Equip faculty with a method to apply AI to research questions.
topic:
• Issue Rating: When is AI appropriate for a particular problem?
• Essential skills for faculty and graduate students (e.g. Python, fine-tuning, model evaluation)
•Ethical considerations and the use of AI in engineering
Part 3: Practical Implementation
Purpose: Allows instructors to implement AI solutions with guided support.
Leader: PhD student at Human First Artificial Intelligence Lab (HAL 2.0)
activity:
• Guided implementation of AI solutions with increased complexity (e.g. image classification, text analysis)
•Uses pre-configured tools such as Google Colab for accessibility
• Technology for adapting and fine-tuning pre-trained models for engineering applications
•Evaluation and optimization of AI models' performance
Participants completing parts 1-3 can submit mini-grant applications for use in the summer of 2025 to promote access to computing resources, preparation of datasets for consultation from graduates, and enhance the use of AI tools, especially in research. The COE covers reasonable costs and expects a brief report on the outcome by the end of summer.
Details: https://go.unl.edu/kit3
