Dan Garber

Dan Garber is an Associate Professor at the Faculty of Data and Decision Sciences at the Technion - Israel Institute of Technology. He joined the faculty in 2017 after completing his Ph.D. at the Technion (2015) and a year as a Research Assistant Professor at Toyota Technological Institute in Chicago (2016). His research bridges machine learning, continuous optimization, and algorithm design, focusing on developing efficient methods for high-dimensional optimization with applications in data science and machine learning.

• Education:
  • B.Sc. in Computer Engineering (2010), Technion
  • M.Sc. in Computer Science (2012), Technion
  • Ph.D. in Computer Science (2015), Technion

Garber leads the Technion Optimization Lab (TOL), which specializes in foundational research on continuous optimization methodologies and their applications in engineering, medicine, and industry. His work emphasizes theoretical guarantees for scalable algorithms, including those used in large-scale data analysis and sequential decision-making systems.

Funding & Awards:

• Israel Science Foundation grants (2018-2022, 2022-2026, ~$250,000 each)
• ERC Consolidator Grant (2025-2030, ~1.785M Euro)
• Best Student Paper Award at COLT Conference (2022) with Ben Kretzu

Garber supervises graduate students in optimization and machine learning, including M.Sc. and Ph.D. candidates. His laboratory supports research projects and disseminates advancements through workshops, schools, and seminars. Contact: dangar@technion.ac.il | Office: Bloomfield 406