CV - Biography

Academic Appointments

  • 4/2018 - Present, Senior Lecturer (with tenure), Department of Management, Bar-Ilan University
  • 9/2019 - 12/2019, Visiting Associate Professor, MSIS Department, Rutgers Business School of Newark and New Brunswick
  • 10/2013 - 3/2018, Lecturer, Department of Management, Bar-Ilan University

Education

  • 2010 PhD, Operations Research, RUTCOR, Rutgers University, New Brunswick, NJ
  • 2004 MSc, Decisions and Operations Research, School of Management, Tel Aviv University
  • 1998 BSc, with High Distinction (Magna Cum Laude), Computer Science, University of Toronto
  • 1996 BBA (Honours Degree), Schulich School of Business, York University

Postroctoral Fellowships / Positions

  • 2013 Carnegie Mellon University
  • 2011-2012 Argonne National Laboratory
  • 2009-2011 Technion - Israel Institute of Technology


Bio

Noam Goldberg completed a PhD in operations research at Rutgers University (RUTCOR) in 2009. His graduate studies followed an early non-academic system/software engineering career in telecommunications. In his PhD thesis he applied and developed new OR and mathematical programming techniques for machine learning. His PhD research on sparse data classification models using decision rules was awarded a first prize in a contest of the INFORMS NJ chapter in 2009. He held several postdoctoral positions during 2009-2013 at the Technion-Israel Institute of Technology, Argonne National Laboratory and Carnegie Mellon University. He joined Bar-Ilan University in 2013 where he was a tenure-track lecturer in 2013-2018, and a tenured senior lecturer since 2018. In fall 2019 he was a visiting associate professor at the Rutgers Business School in New Brunswick. He is an active member of the data science institute at Bar-Ilan and several professional associations including ORSIS, EURO and MOS. He has more than 20 peer reviewed publications including top journals in optimization and conference proceedings in computer science. In his current work he continues to be motivated by high-impact societal applications of OR, data driven optimization models, game models and solution techniques.