Boaz Lerner

Senior Lecturer

Dept. of Industrial Engineering & Management Ben-Gurion University Beer-Sheva 84105 Israel

+972 8 6479 375 (Office) +972 8 6472 958 (Fax) +972 544 399 763 (Mobile) boaz@bgu.ac.il

Boaz Lerner is a Senior Lecturer at the Department of Industrial Engineering & Management of Ben-Gurion University, Israel. His main areas of research lie in machine learning, statistical pattern recognition and data mining approaches to data analysis with applications to 'real-world' problems. Current research focuses on:

• Development and application of machine learning and data mining models to data, text, signal and image detection, segmentation, classification and understanding
• Structure learning for Bayesian networks and Bayesian network classifiers
• Applications of machine learning and data mining to industrial problems

Brief Biography

Publications

Presentations

Professional Activities

Pattern Analysis & Machine Learning Lab (ECE)

Teaching

• Machine Learning & Data Mining
• Introduction to Probability
• Selected Topics in Machine Learning
• Applied AI
• Learning Probabilistic Graphical Models
• Introduction to Digital Image Processing
• Introduction to Electrical Engineering
• Multimedia Signal Processing

Students of my Machine Learning & Data Mining Lab

• Nuaman Asbeh
• Hanna Belyavin
• Eyal Ben-Zion
• Idit Bernstein
• Michal Caspi
• Asaf Cohen
• Dan Halbersberg (with A. Even)
• Noam Nelke

Past students

• Iddo Salton (2004)
  Classification of imbalanced data using neural networks
• Yaniv Gurwicz (2004)
  Classification using Bayesian multinets
• Ra'anan Yehezkel (2004)
  Bayesian network structure learning using recursive autonomy identification
• Roy Malka (2005)
  Bayesian network classifiers
• Boaz Vigdor (2005)
  Pattern recognition using a probability-driven fuzzy ARTMAP classifier
• Lior Konis (2006)
  Radar target classification using dynamic Bayesian networks
• Lev Koushnir (2007)
  A unified methodology for image analysis and classification of dot and non-dot-like fluorescence in situ hybridization signals
• David Bechor (2007)
  Studying and comparing initial starting points of the K-means clustering algorithm
• Yair Meidan (2008)
  Identifying and quantifying factors affecting waiting time and its prediction in manufacturing fabs using machine learning (with G. Rabinowitz)

· Tal Alumot (2009)
On sensitivity to parameters of methods of Bayesian network structure learning, parameter estimation and combination of learning methods

· Roy Kelner (2010)

Learning Bayesian network classifiers by risk minimization

· Tali Alterman (2011)

Machine learning for explanation and prediction of accident severity: Learning strategies in imbalanced problems

· Noam Cohen (2011)

On the impact of missing data on machine learning algorithms and sensitivity reduction to missing data by dynamic allocation of neighbors (with A. Even)

· Naama Simchon (2011)

Selective constraint-based structure learning for Bayesian networks

· Elad Ben Akoune (2011)

A robust value difference metric for feature-oriented imputation (with A. Even)

· Rafi Bojmel (2011)

Automatic threshold selection for Bayesian network structure learning algorithms

· Maydan Wienreb (2011)

Analysis and Prediction of FAB's Work in Process Using Machine Learning: Trading Between Accuracy and Information in Classification Problem (with G. Rabinwitz)

This page is maintained by Boaz Lerner (boaz@bgu.ac.il)

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