Scholar
Yutong Dai
Google Scholar ID: B-e2IDIAAAAJ
Salesforce; Lehigh University
Citations & Impact
Citations
2,133
H-index
11
i10-index
12
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Selected publications include SCUBA: Salesforce Computer Use Benchmark, CoAct-1: Computer-using Agents with Coding as Actions, GTA1: GUI Test-time Scaling Agent, etc. Participated in research projects such as An Adaptive Half-Space Projection Method for Stochastic Optimization Problems with Group Sparse Regularization, A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization, etc.
Research Experience
- Senior Applied Scientist, Salesforce, Aug 2025 – Present; Applied Scientist, Salesforce, Jan 2024 – Jul 2025; Engineer Intern, Adobe, May 2023 – Aug 2023; Research Intern, Salesforce, May 2022 – Aug 2022; Data Scientist Intern, Bud Analytic Lab of Anheuser-Busch InBev, Jan 2018 – May 2019.
Education
- Ph.D. in Industrial & Systems Engineering, December 2023, Lehigh University, supervised by Professor Daniel P. Robinson; M.S. in Statistics, May 2019, University of Illinois at Urbana-Champaign; B.S. in Statistics (with honors), June 2017, Sichuan University.
Background
- Research interests include building and evaluating computer/browser use agents, training (multimodal) large language models, designing, analyzing, and implementing algorithms for large-scale non-convex non-smooth optimization problems arisen in machine learning and federated learning, and making machine learning and deep learning algorithms secure, private, and robust.
Co-authors