Research
IEOR researchers investigate the latest mathematical tools, approaches, and methodologies to make new theoretical discoveries and innovations that touch nearly every industry, making them more efficient and profitable in areas such as supply chain, logistics, manufacturing, data science, energy systems, robotics, and management.
Selected Publications
A comparative study of the leading machine learning techniques and two new optimization algorithms
Philip Baumann, Dorit S. Hochbaum and Yan T. Yang. A comparative study of the leading machine learning techniques and two new optimization algorithms. European Journal of Operational Research, Volume 272, Issue 3, 1 February 2019, Pages 1041-1057. Online version
Learning Ambidextrous Robot Grasping Policies
Learning Ambidextrous Robot Grasping Policies. Jeffrey Mahler, Matthew Matl, Vishal Satish, Mike Danielczuk, Bill DeRose, Stephen McKinley, Ken Goldberg. Science Robotics Journal. V4(26). Jan 2019. [.pdf].
Simplex QP-based Methods for Minimizing a Conic Quadratic Function over Polyhedra
A. Atamturk and A. Gomez. Simplex QP-based Methods for Minimizing a Conic Quadratic Function over Polyhedra. Mathematical Programming Computation 11, 311-340, 2019. https://doi.org/10.1007/s12532-018-0152-7
Optimal Black Start Allocation for Power System Restoration
Georgios Patsakis, Deepak Rajan, Ignacio Aravena, Jennifer Rios and Shmuel Oren, “Optimal Black Start Allocation for Power System Restoration”, IEEE PES Transactions, Vol. 33, No. 6, (2018) pp 6766-6776
Robots and the Return to Collaborative Intelligence (Commentary)
Robots and the Return to Collaborative Intelligence (Commentary). Ken Goldberg. Nature Machine Intelligence Journal. volume 1, pages 2–4. January 2019. [.pdf]