The revolutionary impact and emerging challenges of generative AI in STEM research and education

18 Jan 2024, 09:00 → 19 Jan 2024, 17:00 America/New_York

Harvard Science Center/MIT 10-250 (Harvard (Thur)/MIT (Fri))

Kevin Burdge (MIT), Logan McCarty (Harvard), Lina Necib (MIT), Christoph Paus (MIT), Phiala Shanahan (MIT), Christopher Stubbs (Harvard), Mark Vogelsberger (MIT), Mike Williams (MIT)

Join us for an insightful two-day symposium where we delve into the transformative role of generative artificial intelligence (AI) in the realms of academic research and education. This event, co-hosted by two of the world's leading academic institutions - MIT and Harvard, offers a platform for scholars, educators, and AI experts to examine the profound effects and the complex challenges brought forth by generative AI technologies.

Key Highlights:

• Innovative Applications: Discover how generative AI is revolutionizing traditional methodologies in academic research, fostering novel approaches, and enabling groundbreaking discoveries.

• Educational Transformation: Explore the significant ways in which AI tools are reshaping the educational landscape, from personalized learning experiences to automated content generation.

• Ethical and Societal Implications: Engage in critical discussions on the ethical considerations and societal impacts of integrating AI into academia. What are the potential benefits and risks? How can we navigate the moral complexities?

• Future Prospects and Challenges: Look ahead to the future of generative AI in academia. What challenges do we anticipate, and how can the academic community prepare for them?

• Interactive Panels and Workshops: Participate in dynamic panel discussions with leading AI and academic figures, and attend workshops designed to provide hands-on experience with the latest AI tools and technologies.

This symposium is not only an opportunity to learn about the cutting-edge advancements in AI but also a chance to actively contribute to shaping the future role of AI in academia. Whether you're an academic, a researcher, an educator, or simply an AI enthusiast, this event promises to be a thought-provoking exploration of one of the most significant technological developments of our time.

Join us in sparking a dialogue that bridges technology and academia, and in envisioning a future where AI and education evolve hand in hand.

(This is event description was written entirely by chatGPT)

Thursday, 18 January ¶

1 Introduction and Welcome¶

Speakers: Kevin Burdge (MIT), Dr Logan McCarty (Harvard University)

2 Keynote: Generative AI in Education: Experiences and lessons learned¶

Speaker: Prof. Kavita Bala (Cornell)

3 Undermind: Introducing Deep Scientific Search on ArXiv¶

Speaker: Joshua Ramette (MIT)

4 Leveraging Generative AI for Efficient Literature Review and Synthesis¶

Speaker: Dr Ethan Kyzivat (Harvard)

10:30 Coffee break

5 Toward Physics of Intelligence: Can Generative AI Imagine?¶

Speaker: Dr Hidenori Tanaka (Harvard)

6 Enhancing Academic Research with Locally-Run LLMs: Retrieval-Augmented Generation using Sparse Mixture of Experts¶

Speaker: Dr Nikhil Mukund (MIT)

7 Panel Discussion¶

Speakers: Prof. Kavita Bala (Cornell), Joshua Rammette (MIT), Dr Ethan Kyzivat (Harvard), Dr Hidenori Tanaka (Harvard), Dr Nikhil Mukund (MIT)

12:00 Lunch

8 What should today's undergraduates know about Generative AI?¶

Speaker: Dr Logan McCarty (Harvard University)

9 Afternoon keynote: Automated Question Modification to Challenge AI Models¶

Speaker: Prof. Soroush Vosoughi (Dartmouth)

10 AI and the Future of STEM Education¶

Speaker: Jack Maier (MIT)

14:30 Afternoon coffee break

11 Comparing AI-Supported Instruction vs. Active Learning in Introductory Physics¶

Speakers: Dr Greg Kestin (Harvard), Dr Kelly Miller (Harvard)

12 AI & Mathematics: Exploring AI as a Culturally Relevant Intervention for Attaining Numeracy in Low-Income, K-12 Pedagogical Contexts¶

Speaker: Damion Mannings (Harvard)

13 AI-Enhanced Pedagogy in CS50: From Personalized Tutoring to Holistic Support¶

Speaker: Rongxin Liu

14 Day 1 panel and open discussion¶

Speakers: Prof. Kavita Bala (Cornell), Damion Mannings (Harvard), Dr Greg Kestin (Harvard), Rongxin Liu, Jack Maier (MIT), Dr Kelly Miller (Harvard), Prof. Soroush Vosoughi (Dartmouth)

Friday, 19 January ¶

15 Introduction and welcome for day 2¶

Speaker: Kevin Burdge (MIT)

16 Keynote: Generative AI: What's it good for, and what's it good at?¶

Speaker: Prof. Christopher Stubbs (Harvard)

17 A2rchi: An open-source, end-to-end AI framework for research and education¶

Speaker: Julius Heitkoetter (MIT)

A2rchi_education_and_research_revised.pptx

18 GenPhys and Beyond: Unveiling the Synergy of Physics and Diffusion Models in Generative Processes.¶

Speaker: Ziming Liu (MIT)

19 Supernova Science in the AI Era: Pioneering Real-Time Analysis with Large Language Models¶

Speaker: Dr Alexander Gagliano (MIT)

10:30 Coffee break

20 Revolutionizing Personalized Learning: Introducing Squirrel Ai's Large Adaptive Model (LAM)¶

Speaker: Joleen Liang (Squirrel Ai Learning & Technology)

21 Facial Recognition, Black Women, and Cops: An Urgent Need for an Ethical Framework to Prevent Algorithmic Bias¶

Speaker: Damion Mannings (Harvard)

22 Morning panel+discussion¶

Speakers: Prof. Christopher Stubbs (Harvard), Dr Alexander Gagliano (MIT), Damion Mannings (Harvard), Julius Heitkoetter (MIT), Kevin Burdge (MIT), Ziming Liu (MIT)

12:00 Lunch

23 Afternoon keynote¶

Speaker: Prof. Christopher Capozzola (MIT)

24 Shaping the Future of High-Energy Physics: The Role of Foundation Models in Higgs Boson Identification and Anomaly Detection¶

Speaker: Prof. Philip Harris (MIT)

25 Heterogeneity research can be critical for bridging the gap between AI innovations and biomedicine¶

Speaker: Dr Zhanshan Ma (Harvard)

14:30 Afternoon coffee break

26 The AI Patient Actor: Technology-Supported Clinical Skill Development in Medical Training¶

Speaker: Prof. Thomas Thesen (Dartmouth)

27 LLMs in astrophysics graduate student research¶

Speaker: Emma Chickles (MIT)

28 Integrating generative AI as a tool in large enrollment physics courses¶

Speaker: Dr Mohamed Abdelhafez (MIT)

29 End of workshop panel+discussion¶

Speakers: Prof. Christopher Stubbs (Harvard), Prof. Christopher Capozzola (MIT), Emma Chickles (MIT), Thomas Thesen (Dartmouth), Mohamed Abdelhafez (MIT), Zhanshan (Sam) Ma, Prof. Philip Harris (Massachusetts Institute of Technology)

30 Closing remarks¶

Speaker: Kevin Burdge (MIT)