AI × Statistics: From Intelligent Models to Making Real-World Differences

Leading experts examine how AI/ML and statistics jointly inform decisions, moving from model development to making a real-world impact.
About this Event

Admission at the door is $20 extra. Please note the link below on registering your vehicle with Rutgers Parking.

AI × Statistics: From Intelligent Models to Making Real-World Difference

Artificial intelligence (AI) and machine learning (ML) are increasingly embedded in data-driven decision making across science, technology, and healthcare. For example, automated table and figure generation in clinical trial reports and continuous monitoring of wearable sensors for early detection of clinical signals. Yet the effectiveness and trustworthiness of these systems depend critically on statistical principles such as study design, uncertainty quantification, validation, and causal reasoning.

The 2026 Joint Annual American Statistical Association (ASA) New Jersey/Princeton-Trenton Chapters Spring Symposium brings together experts from industry, academia, and regulatory organizations to examine how AI/ML and statistics jointly inform decisions, moving from model development to making real-world impact. Presentations will explore methodological advances and real-world applications of AI/ML and statistics across healthcare, clinical development, and biomedical research.

The symposium emphasizes the continuing role of statistical judgment in guiding responsible AI innovation and supporting transparent, interpretable, and reliable decision making in modern applied data environments.

We welcome posters on the topic of patient reported outcomes or other topics in biopharmaceutical statistics. If interested in presenting a poster, please send the title to [email protected] by Thursday, June 18.

For general questions about the symposium, contact the Symposium Organizing Committee Chair, CV Damaraju: [email protected] or Stephanie Pugh (American College of Radiology): [email protected]

For registration questions contact Dirk Moore: [email protected]

Venue (note that there is no option for remote attendance):

Rutgers Medical School Kessler Teaching Labs, Main Auditorium

675 Hoes Lane West, Piscataway, NJ 08854

Advance registration closes on Monday, June 22 at 11:30 AM. Late registration at the door is $20.00 extra.

Travel notes: Parking is free. Please park in Lot C if space is available or in Lot A across the street. Do not park in reserved spots.

We recommend that you set your GPS to "683 Hoes Lane West, Piscataway, NJ". This will take you to the entrance to Lot C. The entrance to Lot A is directly across the street.

You must register your vehicle and license number in advance at this web address:

Failure to do this may result in a traffic citation. (Campus police verify registration by scanning license plates.)

parking registration link:

https://parkingbase.com/c/rutgers/d/3676664?eventId=b36c15b7-5293-4053-a7e1-f6e99aaa1cc1

[Rutgers faculty and staff with parking privileges may not use this link.]

Travel by train: NJ Transit Northeast Corridor to Edison or

New Brunswick. Take a taxi or other ride share to the venue.

Information for Persons with Disabilities

Rutgers University-New Brunswick Student Centers encourages qualified persons with disabilities to participate in its programs and activities. If you anticipate needing any type of accommodation or have questions about the physical access provided at the Student Centers, please contact the Meetings and Events Office in advance of your participation or visit. The Meetings and Events Office may be reached at 848.932.8821 or via email at [email protected].

Speakers:

Program:

8:30 - 9:00 Registration and breakfast

9:00 - 9:05 Opening remarks, Alex Liu, President, ASA NJ Chapter (Bayer)

9:05 - 10:00 Junshui Ma, PhD, Merck, Keynote Speaker

AI Agent with Harness: The Universal Framework to Democratize Statistical Expertise

10:00 - 10:35 Kui Shen, PhD, Bayer

Bridge deep learning and clinical development: from transformers to time-to-event models

10:35 - 10:45 Break / Posters

10:45 - 11:20 Devanarayan Viswanath, PhD, BMS

Digital twin development and applications in clinical trials

11:20 - 12:00 Will Ma, HopeAI

Evidence-Based Clinical Trial Design: When the Power of AI Meets Statistical Rigor

12:00 - 1:00 Lunch / Posters

1:00 - 1:35 Vishal Midya, PhD, Icahn School of Medicine at Mount Sinai

Machine-learning analysis of temporal molecular dynamics stratifies autism likelihood - a multinational study

1:35 - 2:10 Yujie Zhao, Merck

Weighting Strategies in Stratified Binary Designs

2:10 - 2:45 James Zou, Associate PRofessor, Stanford University

AI agents to accelerate biomedical discoveries

2:45 - 3:00 Coffee break, posters

3:00 - 3:30 Panel Discusion

Moderator: Sanhita Sengupta, Vice President of NJ Chapter of ASA (BMS)

3:30 Closing remarks

Dipnil Chakraborty, President, ASA Princeton-Trenton Chapter (BMS)