Submit an abstract
Submissions open: February 19, 2024
Early bird submissions close: March 15, 2024
Late bird submissions close: April 1, 2024
Acceptance notifications starting: Monday, March 18, 2024
Conference: Friday April 12, 2024 - Saturday April 13, 2024
Presenters are expected to register for the conference. Accepted student presenters will receive a discount code to register for FREE in their abstract acceptance notification.
Registration & Fees
- $60 non-member two-day ticket
- $40 ASA member two-day ticket
- $25 student, AP Stats Teacher and 2YC instructor two-day ticket
- Free student presenter ticket (submit an abstract before you register)
TWO-DAY TICKETS: Include Friday and Saturday with breakfast and lunch
Registration on Eventbrite
Location & Directions
From the NYS Thruway
Take Exit 46. Immediately after exiting, get on I-390 North and refer to directions below.
From I-390 (Northbound)
Take Exit 13 (Hylan Drive). Turn left onto Hylan Dr. and continue north to Jefferson Road (Route 252), and turn left at the light. Proceed west a short distance to the main campus. Turn left onto campus, just past the Radisson Inn, via Lowenthal Road (the first entrance onto campus from this direction).
After entering campus
Parking will be in Lot S, on the back side of campus. As you enter RIT’s main entrance off of Jefferson Road, take the 2nd exit into a smaller traffic circle and then take a right onto Ezra and Betsy Memorial Drive. Take that road around to the back side of campus and take a left onto Ralph Tyler Drive. Lot S will be on the right.
Friday after 5pm and Saturday parking in Lot S is free. On Friday before 5pm, you may stop at the visitor welcome center in the 2nd small traffic circle to get a visitor pass.
Max Lowenthal Hall (LOW) to the right of Lot S highlighted in the photo.
An interactive map can be found here: https://maps.rit.edu/
4:00 - 5:00pm
T1A: Introduction to Causal Inference
Teresa Gibson, PhD, Professor of Practice, School of Mathematics & Statistics, Rochester Institute of Technology
Level: Basic to intermediate
T1B: Websites/Webservers & Web Graphics for Beginners
Gregory Babbitt, PhD, Associate Professor, Gosnell School of Life Sciences, Rochester Institute of Technology
Level: Basic
T1C: A Gentle Introduction to Diffusion Models in Machine Learning (Part 1)
Zi-Jia Gong, Graduate Student, School of Mathematics & Statistics, Rochester Institute of Technology
Level: Basic to Intermediate
5:00 - 6:00pm
T2A: Community Detection in Complex Networks
Nishant Malik, PhD, Assistant Professor, School of Mathematics & Statistics, Rochester Institute of Technology
Level: Basic
T2B: Introduction to Basic Bioinformatics Concepts & Databases for Beginners
Gregory Babbitt, PhD, Associate Professor, Gosnell School of Life Sciences, Rochester Institute of Technology
Level: Basic
T2C: A Gentle Introduction to Diffusion Models in Machine Learning (Part 2)
Zi-Jia Gong, Graduate Student, School of Mathematics & Statistics, Rochester Institute of Technology
Level: Basic to Intermediate
T2D: Demystifying Tiny GPT: Hands-On Training with PyTorch (Part 1) Canceled
Bardh Rushiti, Co-founder @ AI Kosovo, Computer Vision & AI Engineer @ Calvary Robotics
Level: Intermediate
6:00 - 7:00pm
T3A: AntiCopyPaster: An Open-Source Ecosystem for Just-in-time Code Duplicates Extraction
Mohamed Wiem Mkaouer, PhD, Assistant Professor, Software Engineering, Rochester Institute of Technology
Level:
T3B: An Introduction to the Conformal Prediction Approach to Uncertainty Quantification
Ernest Fokoue, PhD, Professor, School of Mathematics & Statistics, Rochester Institute of Technology
Level: Intermediate
T3C: Introduction to Research Computing at RIT
Benjamin Meyers, PhD, Research Computing, Rochester Institute of Technology
Level: Intermediate
T3D: Demystifying Tiny GPT: Hands-On Training with PyTorch (Part 2) Canceled
Bardh Rushiti, Co-founder @ AI Kosovo, Computer Vision & AI Engineer @ Calvary Robotics
Level: Intermediate
I1: Federated Learning with Data Quality and Security Evaluated OR How to Make Distributed Machine Learning Work in Real-Life? - Organizer: Sergei Chuprov, RIT
I2: An exploration of AI assisted research in Criminal Justice - Organizers: John McCluskey and Irshad Altheimer, RIT
I3: Subsampling and Network Analysis - Organizer: Marianthi Markatou, PhD, University at Buffalo
I4: Accelerating Science with High-Performance Computing - Organizer: Benjamin Meyers, PhD, RIT
I5: Network Analysis - Organizer: Marianthi Markatou, PhD, University at Buffalo
The UPSTAT Conference series team is forever grateful to all the generous sponsors who have support the conference over the years. It would be impossible to properly run a high quality conference without the support of our sponsors.