We will showcase all the accepted papers from: https://openreview.net/group?id=NeurIPS.cc/2025/Education_Program#tab-your-consoles

From Data to CO₂: The Hidden Climate Cost of Artificial Intelligence https://openreview.net/forum?id=Z2laB12Hix

How AI Vaccines Work: Fine‑Tuning, Prompt Injection Defense, and Red‑Teaming to Keep AI Safe https://openreview.net/forum?id=8yeuKSEbMY

Ethical Algorithms for the Modern Clinician https://openreview.net/forum?id=FIQeorc5z5

AHA Moments in AI: Classroom Conversation Starters for High School Students https://openreview.net/forum?id=glBHwBwGAD

A Brief Lesson on Transformers https://openreview.net/forum?id=jxzvYQ1G7S

Interpreting Large Language Models (LLMs) with Geometry https://openreview.net/forum?id=X8ON3ZDBP1

Oregon State University Artificial Intelligence Literacy Videos https://openreview.net/forum?id=86do3uR6vU

You Didn't Train a Model: Common Patterns in Mislabeling AI Development Efforts https://openreview.net/forum?id=F3xEv3mMy3

From Basics to Artificial Intelligence: Designing Significant Early-Stage AI Courses https://openreview.net/forum?id=aBS7SwLqSP

AI & Human Co-Creativity: LLM Hallucinations are Features, Prompts are Experiments, AI is not a being https://openreview.net/forum?id=2UtRJKCHF9

How do AI models process multimodal inputs? https://openreview.net/forum?id=eXkCtjqZG0

IoT-MCP: Design and Control IoT Systems via LLMs https://openreview.net/forum?id=hB1hzziKjK

Beat the Machine — Can You Triage Better than AI? (AI in Healthcare: Triage Through 7 Cases and When It Fails) https://openreview.net/forum?id=u97ugwplrU

Tangled Up in Bluebook: Preparing Lawyers to Catch AI Hallucinations Before They Hit the Record https://openreview.net/forum?id=TGbnXXeyDW

When AI Spills Its Secrets: Detecting System Prompt Leaks in Large Language Models https://openreview.net/forum?id=KdQ3pjbSjt

Benchmarks 101 https://openreview.net/forum?id=TSkYNaS4RA

How are Physiological Time Series Data used for Health Research with AI? https://openreview.net/forum?id=Xc6lUT1xug

Understanding How Neural Networks See ​ (and Read)​ https://openreview.net/forum?id=vHlXiUBvGV

GPT is Coming to Class: A Song https://openreview.net/forum?id=NFtoVPrxXs

XAI: Explaining How AI Makes Decisions https://openreview.net/forum?id=IuS6xI7nfh

Next Token Predication in Decoder Only Models https://openreview.net/forum?id=kKWIgTxchb

Safe AI: Prompt Injection, Data Exfiltration, and Defense-in-Depth https://openreview.net/forum?id=4oxLAmsSRp

AI Safety Fundamentals in Business, Medicine, and Social Media https://openreview.net/forum?id=3x7hrwl0Zl

The AI Scientist - Physics Informed Neural Networks (PINNs) https://openreview.net/forum?id=LVvnfalppC

How to Train a Model: A hands-on, interactive guide to understanding how calculus is used to train AI models. https://openreview.net/forum?id=t99LtZ3Pua

Understanding the Evolution of AI through the Lens of Authorship Verification https://openreview.net/forum?id=Eu5JMON9Gs

Deep Learning for Drug Discovery: A Case Study in Kinase Inhibitors for Anti-Cancer Therapies https://openreview.net/forum?id=spyuQeeO3r

An Interactive Demo of Multiplicity in ML https://openreview.net/forum?id=eYvWzw1xxZ

Understanding Bias and Ethics in AI - Video Submission https://openreview.net/forum?id=t9xBVVtXli

Inside Recommender Systems: How They Work and Why They Matter https://openreview.net/forum?id=5RSottXkP4

The Beginners Mind Guide to ML https://openreview.net/forum?id=F70qsvZ72R

Inside AI Assistant https://openreview.net/forum?id=giLW3MBnQo

MCP Explorer: Interactive Learning Experience https://openreview.net/forum?id=51lXdqM5pC

AI-Powered Agritourism Toolkit: Revolutionizing Agritourism with AI and Machine Learning https://openreview.net/forum?id=TJf48rYenp

Teaching High School Students LLM Literacy Through a Technical, Socio-Ethical, and Career Development Lens: Syllabus, Projects, and Activities https://openreview.net/forum?id=uxO3CwCT6c

Interdisciplinary Lesson Platform with AI Code Generation https://openreview.net/forum?id=SmPpOUeTEl

Reimagining AI Education: Local, Tangible, and Personally Meaningful https://openreview.net/forum?id=nZfkHVORpX

Machine Learning and AI: An Interactive Introduction https://openreview.net/forum?id=LCVFw9EfDN

Exploring Uncertainty with Gaussian Processes: An Interactive Tutorial https://openreview.net/forum?id=rYq0TsMQry

Understanding Artificial Intelligence: An In-Depth Guide for Non-Expert Readers https://openreview.net/forum?id=m1FPLQnmYN

Hallucinations and Phantoms: Correcting AI Attempts at Chemistry https://openreview.net/forum?id=7pYJoGkH9R

¿Qué es la IA Generativa?/What is Generative AI? https://openreview.net/forum?id=ldWrdWzWqA

Application of Multi-Agent Systems for Essay Scoring https://openreview.net/forum?id=Y9c3ETKw50

How does a LLM work? Explained through Illustrations https://openreview.net/forum?id=1oHAYCVQrJ

Create Your Own AI Assistant https://openreview.net/forum?id=0wlCVjcUo6

The Art of Picking the Next Token https://openreview.net/forum?id=oH3KMKmCSQ

Understanding AI Agents: Explainer Video & Interactive Demo https://openreview.net/forum?id=bIyDDYazTh

Your First AI (Travel) Agent in 15 Minutes! https://openreview.net/forum?id=uYxS366Ssw

LLMs In Your Workflow https://openreview.net/forum?id=Ur0CYUsDjP

The Invisible Fingerprints: Protecting Your Digital Images https://openreview.net/forum?id=IxTOrojAgz

DeBiasMe AI Literacy Workbook: Building Critical Thinking Through Bias Detection, Mapping, and Mitigation https://openreview.net/forum?id=6aHaK9c8Z3

AI Literacy – Responsible AI in Education https://openreview.net/forum?id=vUdib5izNV

Good Ideas Start With You: Creating AI Videos With the "Me" Factor https://openreview.net/forum?id=ecGGWn2acL

AI Camp - Years R-3 Workbook https://openreview.net/forum?id=PBDKRFf60T

Cut Through the Noise: How to Write an Effective Elevator Pitch

Whether you are explaining your work to collaborators, pitching a project for funding, talking with journalists or interviewing for a top industry job, clarity will help you cut through the noise. This hands-on, interactive session will equip you with practical tools to translate your research into a short, effective, and accessible overview. You will leave with an elevator pitch ready to be adapted for any audience. This workshop will give you: 1. Theoretical foundations on how to make complex messages memorable and persuasive. 2. Exercises to find your core message and focus on what matters most. 3. Storytelling techniques to strip jargon, frame your data, and turn technical details into engaging narratives. 4. Individualized advice on public speaking to make the most out of every opportunity.

Application of Multi-Agent Systems for Essay Scoring by Ali Keramati and Mark Warschauer

Understanding How Neural Networks See by Michael Guerzhoy

MCP Explorer: Interactive Learning Experience by Jiayu He, Sherry Ruan and James Landay

The Invisible Fingerprints: Protecting Your Digital Images by Prachee Sharma

How to Train a Model: A hands-on, interactive guide to understanding how calculus is used to train AI models by Jacob Buckhouse

IoT-MCP: Design and Control IoT Systems via LLMs by Tingjun Chen and Yiran Chen

Serena Booth studies how people write specifications for AI systems and how people assess whether AI systems are successful in learning from their specifications. Serena's work is often conducted in the context of reinforcement learning, and her work is sometimes physically embodied, too, i.e. as robots.

Serena received her PhD at MIT CSAIL in 2023. She is a graduate of Harvard College (2016) and former Associate Product Manager at Google. Her research has been supported by the National Science Foundation, the Canadian Institute for Advanced Research, the Survival and Flourishing Fund, and the UK AI Security Institute. She has been recognized as a CIFAR Global Scholar (2025), Human-Robot Interaction Pioneer (2023), and as a Rising Star in Electrical Engineering and Computer Science (2022).

Eunice Jun is an Assistant Professor in CS, where she co-directs the Computation & Discovery Lab. Her research focuses on methods and tools that (i) enhance scientific reasoning and discourse and (ii) make programming more accessible. Recent projects include domain-specific languages for experimental design and statistics, new environments for programming with LLMs more effectively for data science and general-purpose programming, and data visualization techniques for Bayesian inference.

Understanding Bias and Ethics in AI by Anand Rao

Benchmarks 101 by David Huu Pham, Heila Precel, Eleanor Tursman, B Cavello, Francisco Jure, Nicholas Vincent

AI-Powered Agritourism Toolkit: Revolutionizing Agritourism with AI and Machine Learning by Xue A. Dong

Interpreting Large Language Models (LLMs) with Geometry by Lauren Alvarez and Michael Freenor

AI & Human Co-Creativity: LLM Hallucinations are Features, Prompts are Experiments, AI is not a being by Joseph Dumit