List of Past PhD Students and Post-Doc(s)

List of Past PhD Students and Post-Doc(s):

Name Dissertation's Title Position with

Nicholas G. Hall Solutions for the Multicovering Problem Ohio State University

Thomas A. Feo I. A lagrangean relaxation method for testing the infeasibility of certain VLSI routing problems. II. Efficient reduction of planar networks for solving certain combinatorial problems. University of Texas, Austin

Mallek Khellaf On graph partitioning problems British Telecom

David B. Shmoys Approximation algorithms for problems in sequencing, scheduling, and communication network design Cornell University

Olivier P. Goldschmidt Deterministic and probabilistic aspects of the k-cut problem OPNET Technologies

Sung-Pil Hong About strongly polynomial algorithms of some special classes of convex quadratic programming Seoul National University, Korea

Dan Landy Batch scheduling for manufacturing i2 Technology, California and perpetual commute

Anna Chen Efficient algorithms for the ultimate pit limit problem

Anu Pathria Algorithms and complexity for cuts and selection problems on graphs Correlation Ventures, San Diego

Eli Olinick Algorithms for telecommunication networks Southern Methodist University, Texas

Bala Chandran Implementations of the pseudoflow algorithm for maximum flow, bipartite matching, flows in unit capacity networks, and parametric maximum flow Analytics Operations Engineering, Inc. Boston
Erick Moreno-Centeno Use and analysis of new optimization techniques for decision theory and data mining Texas A&M
Ephrat Bitton Geometric Models for Collaborative Search and Filtering Data scientist, Lyft
Barak Fishbain Post-doc on :DOmestic NUClear Threats Security (DONUTS) Faculty at Technion, Civil Engineering
Yan Yang Machine Learning Techniques in Nuclear Material Detection, Drug Ranking and Video Tracking Amazon, Boston, Ma
Philipp Baumann Post-doc on: DARPA Security Routing University of Bern, Bern, Switzerland
Cheng Lu Efficient Algorithms for Markov Random Fields, Isotonic Regression, Graph Fused Lasso, and Image Segmentation Google, Ca
Quico Spaen Applications and Advances in Similarity-based Machine Learning Amazon, Palo Alto, Ca

Back to Hochbaum main page

Name	Dissertation's Title	Position with
Nicholas G. Hall	Solutions for the Multicovering Problem	Ohio State University
Thomas A. Feo	I. A lagrangean relaxation method for testing the infeasibility of certain VLSI routing problems. II. Efficient reduction of planar networks for solving certain combinatorial problems.	University of Texas, Austin
Mallek Khellaf	On graph partitioning problems	British Telecom
David B. Shmoys	Approximation algorithms for problems in sequencing, scheduling, and communication network design	Cornell University
Olivier P. Goldschmidt	Deterministic and probabilistic aspects of the k-cut problem	OPNET Technologies
Sung-Pil Hong	About strongly polynomial algorithms of some special classes of convex quadratic programming	Seoul National University, Korea
Dan Landy	Batch scheduling for manufacturing	i2 Technology, California and perpetual commute
Anna Chen	Efficient algorithms for the ultimate pit limit problem
Anu Pathria	Algorithms and complexity for cuts and selection problems on graphs	Correlation Ventures, San Diego
Eli Olinick	Algorithms for telecommunication networks	Southern Methodist University, Texas
Bala Chandran	Implementations of the pseudoflow algorithm for maximum flow, bipartite matching, flows in unit capacity networks, and parametric maximum flow	Analytics Operations Engineering, Inc. Boston
Erick Moreno-Centeno	Use and analysis of new optimization techniques for decision theory and data mining	Texas A&M
Ephrat Bitton	Geometric Models for Collaborative Search and Filtering	Data scientist, Lyft
Barak Fishbain	Post-doc on :DOmestic NUClear Threats Security (DONUTS)	Faculty at Technion, Civil Engineering
Yan Yang	Machine Learning Techniques in Nuclear Material Detection, Drug Ranking and Video Tracking	Amazon, Boston, Ma
Philipp Baumann	Post-doc on: DARPA Security Routing	University of Bern, Bern, Switzerland
Cheng Lu	Efficient Algorithms for Markov Random Fields, Isotonic Regression, Graph Fused Lasso, and Image Segmentation	Google, Ca
Quico Spaen	Applications and Advances in Similarity-based Machine Learning	Amazon, Palo Alto, Ca