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Data Science AI Events

AI Training Day: March 5th, 2024


The Data Science Institute invites you to join us for our first AI Training Day on Custom Models on March 5th, 2024 at the VU Student Life Center. This day-long, hybrid event combines comprehensive insights into the development of new AI models with a focus on the practicalities of custom model training. Tailored for the Vanderbilt community and invited guests, the training day aims to equip researchers, educators, and practitioners with the knowledge needed to navigate the rapidly evolving AI landscape. By exploring modern training methods and architectural designs, this event seeks to enhance your understanding and skills in AI, ensuring you’re up-to-date on the rapidly evolving AI landscape.

Date: Tuesday, March 5th, 2024, 9:00 – 5:00 Central Time

Location: VU Student Life Center, (310 25th Ave S)

 

To secure your spot at AI training day:

REGISTER HERE

 

The event will cover essential topics such as:

  • AI Foundations: Gain a solid understanding of AI models, including generative AI models like ChatGPT and diffusion models.
  • AI Services: Explore the range of AI services and how they can be integrated into your work.
  • Building, Training, and Running Custom AI Models: Dive deep into the practical aspects of AI model development, from conception to deployment.

Special emphasis will be placed on:

  • Train the Trainer: Aimed at trainers, educators, and researchers, this session focuses on equipping you with the knowledge to effectively communicate AI concepts.
  • Running Models and Training Overview: Detailed walkthroughs on running AI models and a comprehensive overview of model training.
  • Training Your Model: An intensive, hands-on workshop on the end-to-end process of AI model training.

The event will follow this schedule:

  • 8:30 am: Breakfast
  • 9:00 am – 12:00 pm: Morning sessions including AI Foundations and AI Services
  • 12:00 pm: Lunch and AI Showcase Winners Presentations
  • 1:00 pm – 5:00 pm: Afternoon sessions focused on building, training, and running custom AI models

Morning Session: Train the Trainer

The morning kicks off with a series of engaging sessions with a focus on AI’s core principles and applications:

  • 9:00 AM – AI Foundations: This session provides a comprehensive overview of fundamental AI concepts, essential for anyone looking to deepen their understanding of how AI models, including generative models like ChatGPT, function and can be applied across various domains.
  • 10:30 AM – Coffee Break: A brief interlude to refresh and network with fellow AI enthusiasts.
  • 10:35 AM – AI Services: Explore the spectrum of AI services available today. This segment focuses on how these services can be utilized to enhance research, development, and innovation in your projects or organizations.
  • 12:00 PM – Lunch and AI Showcase Winners Presentations: Enjoy lunch while listening to presentations from winners of the AI Showcase. This is a perfect opportunity to see real-world applications of AI and the innovative solutions emerging in the field.

Afternoon Session: Building, Training, and Running Custom AI Models

The afternoon is dedicated to more specialized topics, with a focus on the practical aspects of AI model development:

  • 1:00 PM – Running Models: An in-depth look at the logistics and strategies for efficiently running AI models. This session covers everything from choosing the right platforms to optimizing model performance.
  • 1:30 PM – Model Training Overview: A crucial session for those looking to understand the nuances of AI model training. It will cover the when, why, and how of training models, including considerations for domain-specific training and task optimization.
  • 2:00 PM – Training Your Model: This extensive workshop offers hands-on experience in AI model training. Participants will learn about setting up training loops, selecting compute resources, and navigating through the training process for successful model development.
  • 5:00 PM – End of Training Day: The day concludes, leaving participants with new insights, skills, and connections in the AI field.

Registration

To secure your spot at AI training day:

REGISTER HERE

We look forward to an engaging and informative session that promises to elevate your AI skills and knowledge.

 

2023

AI Revolutions Symposium, March 27/28

The Data Science Institute’s AI Revolutions Symposium will be a two-day event, beginning with the virtual workshops on March 27th. These virtual workshops include:

  • Understanding AI Models, 10:00 to 11:00 a.m.
  • Making ChatGPT Work for Your Research, 1:00 to 2:30 p.m.
  • ChatGPT Prompt Engineering Clinic, 2:30 to 3:30 p.m.

The in-person sessions on March 28th, including featured speakers, will last all day. The event will be held at the Wyatt Rotunda on Peabody’s campus. Speakers include:

  • Yaa Kumah-Crystal, MD, MPH, MS
    Assistant Professor, Biomedical Informatics
    Assistant Professor, Pediatric Endocrinology
  • John Yang, PhD
    Assistant Professor, Chemistry
  • Gregor Neuert, PhD
    Associate Professor, Molecular Physiology and Biophysics
    Associate Professor, Biomedical Engineering
    Associate Professor, Pharmacology
  • Hassane S. Mchaourab, PhD
    Louise B. McGavock Chair, Molecular Physiology and Biophysics
    Professor, Physics
    Professor, Chemistry
    Professor, Structural Biology
  • Alex Christensen, MA, PhD
    Assistant Professor, Psychology and Human Development
    Department of Psychology and Human Development
  • Michael Bess, PhD
    Chancellor’s Professor of History
    Professor, Communication of Science and Technology Professor,  European Studies
  • Ole Molvig, PhD
    Assistant Professor, History
    Assistant Professor, Communications of Science and Technology
    Assistant Professor, Physics;
    Founder, emergent technology lab at the Wond’ry
    Curator, Garland Historical Scientific Instruments Collection
  • Frank Tong, PhD
    Centennial Professor, Psychology
    Professor, Ophthalmology and Visual Sciences
  • Doug Schmidt, PhD
    Associate Provost, Research Development and Technologies
    Cornelius Vanderbilt Professor, Engineering
    Professor, Computer Science
    Professor, Electrical and Computer Engineering
    Co-Director, Data Science Institute
  • Jules White, PhD
    Associate Dean, Strategic Learning Programs
    Associate Professor, Computer Science
  • Jesse Spencer-Smith, PhD
    Chief Data Scientist, Data Science Institute
    Interim Director, Data Science Institute
    Professor of Practice, Computer Science

A happy hour will follow.

Registration

To register, please use this form.

2020

Due to COVID-19, we unfortunately had to cancel our 2020 symposium. We look forward to welcoming you back to our next event in 2021.

2019

If you attended our 2019 symposium, thanks! If you were unable to make it, we are sorry to have missed you. Below are the recordings to all of the sessions.

Program Agenda

8:30am – 9:45am: Registration

8:30am: Graduate Student Poster Session & Breakfast

9:45am: Welcome & Opening Remarks
Video Recording

10:00am: Short Talks
Video Recording

11:00am: Faculty Lightning Talks
Video Recording

12:00pm – 1:00pm: Lunch
12:15pm – 12:20pm:
Graduate Student Poster Award
Video Recording

12:20pm – 1:00pm: Panel Discussion
Video Recording

1:00pm: Key Note Talk

“Terra Cognita: The Silicon Age of Earth Exploration”
Dr. Ian Howat, Ph.D.
Professor, The Ohio State University
Video Recording

2:00pm: Coffee Break

2:30pm: Short Talks
Video Recording

3:30pm: Live Deep Learning Demo
Video Recording

2018

8:00-9:45am – Student Poster Session & Breakfast  (lobby outside Flynn auditorium)

  • 9:45-10:00am – Welcome Remarks – Andreas Berlind, Associate Professor of Physics and Astronomy – Video Recording
  • 10:00-11:00am – Short Talks – (chair: Douglas Schmidt) – Video Recording
    • Analyzing Thousands of Genomes to Map Human Evolution and Disease
      Tony Capra, Assistant Professor of Biological Science
    • Data Analytics and Decision Support for Public Safety
      Yevgeniy Vorobeychik, Assistant Professor of Computer Science
    • Using Big Data for Population Health Services and Policy Research
      Stacie Dusetzina, Associate Professor of Health Policy
    • Affluence and Congruence: Unequal Representation Around the World
      Noam Lupu, Associate Professor of Political Science
    • Power of Simulation (Even if You Have ‘Big’ Data)
      Leena Choi, Associate Professor of Biostatistics & Sara van Driest, Assistant Professor of Pediatrics
  • 11:00-12:00am – Lighting Talk Session – (chair: Yu Shyr)
    • Research IT Working Group Progress Report
      Douglas Schmidt, Cornelius Vanderbilt Professor of Engineering – Video Recording
    • 15 2-minute talksVideo Recording
  • 12:00-1:00pm – Panel Discussion & LunchVideo Recording
    • Panel Discussion: Ethics of Data
      Moderator: Jonathan Gilligan, Associate Professor of Earth and Environmental Science
      Panelists: Sarah Igo, Associate Professor of History, Chris Slobogin, Milton R. Underwood Chair in Law, Eugene Vorobeychik, Assistant Professor of Computer Science
  • 1:00-2:00pm – Short Talks (chair: Kelly Holley-Bockelmann) – Video Recording
    • AI for Law and Law for AI – A Typology of Themes
      J. B. Ruhl, David Daniels Allen Distinguished Chair of Law
    • Statistical Thinking for Data Science
      Chris Fonnesbeck, Assistant Professor of Biostatistics
    • Genetic Discovery at Scale through Phenome Phishing
      Nancy Cox, Mary Phillips Edmonds Gray Professor of Genetics
    • Using Spatial Analysis to Understand Access to Higher Education
      William Doyle, Associate Professor of Public Policy and Higher Education
    • Data Science at HCA
      Jesse Spencer-Smith, Director of Data Science at HCA Healthcare
  • 2:00-2:30pm – Coffee Break
  • 2:30-3:30pm – Keynote Talk: Digital Echoes: Understanding Patterns of Mass Violence with Data and Statistics
    Patrick Ball, Director of Research, Human Rights Data Analysis Group – Video Recording
  • 3:30-4:00pm – Student Poster AwardsVideo Recording
    • Winner: Andrew Summers
    • Runners-up: Victor Calderon, Linda Zhang

Data Science Colloquia

Spring 2021

Watch Here

Fall 2020

October 21

Watch Recording Here

 

 

 

 

 

 

 

Spring 2020

January 31
Learn More

February 14
Learn More

February 28
Learn More

March 13
Learn More

March 20
Learn More

April 3
Learn More

April 10
Learn More

Fall 2019

2018

Alberto Cairo, U. Miami | Visual Trumpery

September 20, 2018

Cameron McBride, Rubicon Project | Data Science: the What, Why, and How of my Transition from Science to Tech

May 4, 2018

Daniel Tamayo, CITA | Planetary Science in a Data Rich Era

April 13, 2018

Brian Johnson, DonorBureau | Building Your Applied Data Science Toolkit

March 16, 2018

 

2017

Danielle Beringer, Nissan | Big Data & Analytics – Driving Change at Nissan

December 1, 2017

Jesse Spencer-Smith, HCA | Data Science in Practice: Essential Skills and Training for an Evolving Field

October 5, 2017