Biography

Yutong Dai earned his Ph.D. degree from the Department of Industrial and Systems Engineering at Lehigh University, under the supervision of Professor Daniel P. Robinson. He also works closely with Professor Lichao Sun.

His research interests include

  1. designing, analyzing and implementing algorithms for large scale non-convex non-smooth optimization problems arisen in machine learning and federated learning, and
  2. making machine learning and deep learning algorithms secure, private, and robust.

Interests

  • Nonsmooth Optimization with Structured Sparsity
  • Federated Learning
  • Optimization in Machine Learning
  • Multimodal Large Language Model

Education

  • Ph.D. in Industrial & Systems Engineering, December, 2023

    Lehigh University

  • M.S. in Statistics, May, 2019

    University of Illinois at Urbana-Champaign

  • B.S. in Statistics (with honors), June, 2017

    Sichuan University

Experience

 
 
 
 
 

Applied Research Scientist

Salesforce

Jan 2024 – Present Palo Alto, CA
LLM & MLLM
 
 
 
 
 

Machine Learning Engineer Intern

Adobe

May 2023 – Aug 2023 San Jose, CA
Benchmarked personalized ranking algorithms based on implicit feedback data from Adobe’s products; Developed a multi-objective optimization framework to improve the current ranking algorithms to accommodate the diverse needs of business partners.
 
 
 
 
 

Research Intern

Salesforce

May 2022 – Aug 2022 Palo Alto, CA
Conduct research on federated learning focusing on data heterogeneity with class imbalance. The work was accepted by AAAI'23.
 
 
 
 
 

Data Scientist Intern

Bud Analytic Lab of Anheuser-Busch InBev

Jan 2018 – May 2019 Urbana, IL
Leverage the power of the machine learning algorithms and domain knowledge to support global agronomist teams manage Barley in a data-driven way.

Projects

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Real Estate Market Data Analysis

Develope data products to help Airbnb hosts to determine listing prices.

Show and Tell: A Neural Image Caption Generator

Feed in an image, AI will generate the caption for you!

Variational Gaussian Mixtures

Clustering under the variation inference framework.

Services

  1. Reviewer:
  • Conferences: KDD(2), AISTATS(2)
  • Journals: Journal of Scientific Computing (6), Optimization Letters (3), Mathematical Programming Series A (2)
  1. Conference Sessions Organizer:
  1. Teaching:

Contact

  • 200 West Packer Avenue, Bethlehem, PA 18015