professor •​ author • ​top researcher • 200+ publications • 7 books • 30 grads • awards • ​evolutionary algorithms, machine learning, deep learning
"A little perspective. That's it. I'd like some fresh, clear, well-seasoned perspective. Can you suggest a good wine to go with that?" 
​— Anton Ego, Ratatouille 🐭
BIO 📜​
​Moshe Sipper is a professor of computer science at Ben-Gurion University of the Negev, Israel. He received the BA degree from the Technion — Israel Institute of Technology, and the MSc and PhD degrees from Tel Aviv University, all in computer science. During 1995–2001 he was a senior researcher at the EPFL (Switzerland), and during 2016-2020 he was a visiting professor at the University of Pennsylvania (USA).

​His current research focuses on evolutionary computation, machine learning, artificial intelligence​, and deep learning. At some point or other he also did research in: artificial life, artificial self-replication, bio-inspired computing, cellular automata, cellular computing, embryonic electronics, evolvable hardware, fuzzy logic, games, robotics, and software engineering.

Dr. Sipper has authored over 200 scientific publications, including three books: Evolved to Win, Machine Nature: The Coming Age of Bio-Inspired Computing, and Evolution of Parallel Cellular Machines: The Cellular Programming Approach. He has supervised close to 30 graduate students, and taught numerous basic and advanced courses in computer science, both undergraduate and graduate.

He is an associate editor of the journal Genetic Programming and Evolvable Machines, and was an associate editor of the journals: IEEE Transactions on Evolutionary Computation, IEEE Transactions on Computational Intelligence and AI in Games, and Memetic Computing. He organized and chaired several conferences and has served on the program committees of over 130. He has also served as a reviewer for nearly 40 journals and funding agencies.

Dr. Sipper won the 2015 IEEE CIS Outstanding TCIAIG Paper Award, the 2008 BGU Toronto Prize for Academic Excellence in Research, the 1999 EPFL Latsis Prize, and 6 HUMIE Awards (Human-Competitive Results Produced by Genetic and Evolutionary Computation). He has been cited as a top scientist, appears in the top 2% in the Mendeley list, and was one of 5 Scientists At The Forefront Of Computing And AI.
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He is the author of four fiction books: Fredric: A Collection of Flash Fiction, Daniel Max and the King in the Tower, Xor: The Shape of Darkness, and The Peaceful Affair. He is also a cartoonist and has been known to sing.
 SPOTLIGHT​ 🔦​
♢​ EC-KitY: Evolutionary Computation Tool Kit in Python
♢ Artificial General Intelligence: Pressure Cooker or Crucible?
♢ High Per Parameter: A Large-Scale Study of Hyperparameter Tuning for Machine Learning Algorithms
♢ Attackar: Attack of the Evolutionary Adversary
♢ Combining Deep Learning with Good Old-Fashioned Machine Learning
♢ AddGBoost: A Gradient Boosting-Style Algorithm Based on Strong Learners
♢ Evolution of Activation Functions for Deep Learning-Based Image Classification
♢ From Requirements to Source Code: Evolution of Behavioral Programs
♢ Binary and Multinomial Classification through Evolutionary Symbolic Regression
♢ Neural Networks with À La Carte Selection of Activation Functions
♢ Symbolic-Regression Boosting
♢ Conservation Machine Learning: A Case Study of Random Forests
♢ Conservation Machine Learning
♢ New Pathways in Coevolutionary Computation
♢ Automatically Balancing Model Accuracy and Complexity using Solution and Fitness Evolution (SAFE)​
♢ Solution and Fitness Evolution (SAFE): Coevolving Solutions and Their Objective Functions
♢ Solution and Fitness Evolution (SAFE): A Study of Multiobjective Problems
♢ OMNIREP: Originating Meaning by Coevolving Encodings and Representations
♢ Coevolving Artistic Images Using OMNIREP
♢ Newsweek: The aliens have landed—but they're not smart enough to take over
♢ Gamorithm
♢ Genetic programming theory and practice: A fifteen-year trajectory
♢ To know the objective is not (necessarily) to know the objective function
♢ Automated discovery of test statistics using genetic programming
♢ Investigating the parameter space of evolutionary algorithms
♢ EBIC: an evolutionary-based parallel biclustering algorithm for pattern discovery
♢ Evolutionary computation: the next major transition of artificial intelligence?
♢ Artificial intelligence: more human with human
♢ A system for accessible artificial intelligence
♢ ​Fredric: A Collection of Flash Fiction
♢ Machine Nature excerpts: ◦ Biologic or “By Ole Logic” ◦ Who's the Boss? ◦ The Scigineer ​◦​ A Life of Its Own
CONTACT 📭​
​Department of Computer Science, Ben-Gurion University, Beer-Sheva 8410501, Israel • Alon Building, 37/121 • (972)-8-6477880 (internal: 77880) • sipper@bgu.ac.il • GitHub • Twitter • Linkedin • YouTube • ORCID​
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