Welcome to my site.

Contact:

Etcheverry Hall

University of California

Berkeley, CA 94720

TEL: (510) 642-4998

hochbaum at ieor.berkeley.edu

News:

UC Berkeley, with Georgia Tech, USC and other universities, was awarded $20M for the NSF National AI Institute for Advances in Optimization, 2021-2026. I serve as co-PI on this award.

The paper "The Max-Cut Decision Tree: Improving on the Accuracy and Running Time of Decision Trees" by Jon Bodine and myself won the Best Student Paper Award at the 12th International Conference on Knowledge Discovery and Information Retrieval (KDIR 2020) that took place November 2020. Jon is an undergrad at the IEOR department, and is likely among the very few undergraduates to ever win such an award. For more details, see IEOR News .

As for older news:

I was awarded, summer 2018, an NSF grant titled "A Graph Theoretic Approach for Spatial Dependence in Quality Control and Prediction" by the Operations Engineering (OE) CMMI division.

The neuron segmentation algorithm HNCcorr is one of the leading algorithms in the Neurofinder . benchmark for cell identification in calcium imaging movies. The algorithm is HNC (Hochbaum Normalized Cut), aka NC', with similarities based on distances in correlation space. This is joint work with Quico Spaen and Roberto Asin.

I try to be an optimizer in whatever I do, and my research interests reflect that. Some problem applications I am interested in include:

  • Data mining and pattern recognition with flow techniques
  • Image segmentation and detecting hidden features in medical images
  • Detecting security threats - domestic nuclear threat security (detection) The DoNuTS project
  • Information technology issues in supply chain management
  • Manufacturing of VLSI circuit
  • Testing and designing circuits
  • Scheduling problems
  • Planning of mining operations
  • Locations of facilities
  • Distribution and logistics
  • And, baking cakes optimally

Please consult the list of publications or technical reports for specific titles.

I also have substantial interest in algorithms that solve problems as efficiently as possible and exploring complexity issues. These include approximation algorithms, strongly polynomial algorithms, practical integer programming algorithms for discrete optimization problems, problems on graphs, and nonlinear problems.

Topics in nonlinear complexity and combinatorial optimization: IEOR 290G, Spring 2017 -

in Lecture notes Spring 2017.

Network Flows and Graph Algorithms: IEOR 266, Updated Fall 2020 -

in Lecture notes Fall 2020.

Integer Programming and Combinatorial Optimization: IEOR 269 -

in Lecture notes Spring 2010.