Randal S. Olson

52 papers A 5C 4Misc 3Journal 27Unranked 11

Year	Rank	Type	Title / Venue / Authors
2020	J	`jnl`	How Computational Experiments Can Improve Our Understanding of the Genetic Architecture of Common Human Diseases. Artif. Life Jason H. Moore, Randal S. Olson, Peter Schmitt, Yong Chen, Elisabetta Manduchi
2019	J	`jnl`	Automated discovery of test statistics using genetic programming. Genet. Program. Evolvable Mach. Jason H. Moore, Randal S. Olson, Yong Chen, Moshe Sipper
2019	—	`conf`	Discovering test statistics using genetic programming. GECCO (Companion) Jason H. Moore, Randal S. Olson, Yong Chen, Moshe Sipper
2019	—	`ch.`	TPOT: A Tree-Based Pipeline Optimization Tool for Automating Machine Learning. Automated Machine Learning Randal S. Olson, Jason H. Moore
2019	—	`conf`	Using Machine Learning on Home Health Care Assessments to Predict Fall Risk. MedInfo Yancy Lo, Selah F. Lynch, Ryan J. Urbanowicz, Randal S. Olson, Ashley Z. Ritter, Christina R. Whitehouse, Melissa O'Connor, Susan K. Keim, Margaret V. McDonald, Jason H. Moore, Kathryn H. Bowles
2018	Misc	`conf`	A heuristic method for simulating open-data of arbitrary complexity that can be used to compare and evaluate machine learning methods. PSB Jason H. Moore, Maksim Shestov, Peter Schmitt, Randal S. Olson
2018	J	`jnl`	Benchmarking relief-based feature selection methods for bioinformatics data mining. J. Biomed. Informatics Ryan J. Urbanowicz, Randal S. Olson, Peter Schmitt, Melissa Meeker, Jason H. Moore
2018	Misc	`conf`	Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure. PSB Alena Orlenko, Jason H. Moore, Patryk Orzechowski, Randal S. Olson, Junmei Cairns, Pedro J. Caraballo, Richard M. Weinshilboum, Liewei Wang, Matthew K. Breitenstein
2018	Misc	`conf`	Data-driven advice for applying machine learning to bioinformatics problems. PSB Randal S. Olson, William G. La Cava, Zairah Mustahsan, Akshay Varik, Jason H. Moore
2018	—	`ed.`	Genetic Programming Theory and Practice XV, [GPTP 2017, University of Michigan, Ann Arbor, USA, May 18-20, 2017]. GPTP Wolfgang Banzhaf, Randal S. Olson, William A. Tozier, Rick L. Riolo
2018	C	`conf`	How computational thought experiments can improve our understanding of the genetic architecture of common human diseases. ALIFE Jason H. Moore, Randal S. Olson, Peter Schmitt, Yong Chen, Elisabetta Manduchi
2018	J	`jnl`	Layered TPOT: Speeding up Tree-based Pipeline Optimization. CoRR Pieter Gijsbers, Joaquin Vanschoren, Randal S. Olson
2018	J	`jnl`	Relief-based feature selection: Introduction and review. J. Biomed. Informatics Ryan J. Urbanowicz, Melissa Meeker, William G. La Cava, Randal S. Olson, Jason H. Moore
2017	—	`conf`	A System for Accessible Artificial Intelligence. GPTP Randal S. Olson, Moshe Sipper, William G. La Cava, Sharon Tartarone, Steven Vitale, Weixuan Fu, Patryk Orzechowski, Ryan J. Urbanowicz, John H. Holmes, Jason H. Moore
2017	J	`jnl`	A System for Accessible Artificial Intelligence. CoRR Randal S. Olson, Moshe Sipper, William G. La Cava, Sharon Tartarone, Steven Vitale, Weixuan Fu, John H. Holmes, Jason H. Moore
2017	J	`jnl`	Benchmarking Relief-Based Feature Selection Methods. CoRR Ryan J. Urbanowicz, Randal S. Olson, Peter Schmitt, Melissa Meeker, Jason H. Moore
2017	J	`jnl`	Data-driven Advice for Applying Machine Learning to Bioinformatics Problems. CoRR Randal S. Olson, William G. La Cava, Zairah Mustahsan, Akshay Varik, Jason H. Moore
2017	J	`jnl`	Evolutionary computation: the next major transition of artificial intelligence? BioData Min. Moshe Sipper, Randal S. Olson, Jason H. Moore
2017	J	`jnl`	Grid-based stochastic search for hierarchical gene-gene interactions in population-based genetic studies of common human diseases. BioData Min. Jason H. Moore, Peter C. Andrews, Randal S. Olson, Sarah E. Carlson, Curt Larock, Mario J. Bulhoes, James P. O'Connor, Ellen M. Greytak, Steven Armentrout
2017	—	`conf`	Layered TPOT: Speeding up Tree-based Pipeline Optimization. AutoML@PKDD/ECML Pieter Gijsbers, Joaquin Vanschoren, Randal S. Olson
2017	J	`jnl`	Markov Brains: A Technical Introduction. CoRR Arend Hintze, Jeffrey A. Edlund, Randal S. Olson, David B. Knoester, Jory Schossau, Larissa Albantakis, Ali Tehrani-Saleh, Peter D. Kvam, Leigh Sheneman, Heather Goldsby, Clifford Bohm, Christoph Adami
2017	J	`jnl`	PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison. CoRR Randal S. Olson, William G. La Cava, Patryk Orzechowski, Ryan J. Urbanowicz, Jason H. Moore
2017	J	`jnl`	PMLB: a large benchmark suite for machine learning evaluation and comparison. BioData Min. Randal S. Olson, William G. La Cava, Patryk Orzechowski, Ryan J. Urbanowicz, Jason H. Moore
2017	J	`jnl`	Relief-Based Feature Selection: Introduction and Review. CoRR Ryan J. Urbanowicz, Melissa Meeker, William G. La Cava, Randal S. Olson, Jason H. Moore
2017	A	`conf`	Toward the automated analysis of complex diseases in genome-wide association studies using genetic programming. GECCO Andrew Sohn, Randal S. Olson, Jason H. Moore
2017	J	`jnl`	Toward the automated analysis of complex diseases in genome-wide association studies using genetic programming. CoRR Andrew Sohn, Randal S. Olson, Jason H. Moore
2016	—	`conf`	Automating Biomedical Data Science Through Tree-Based Pipeline Optimization. EvoApplications (1) Randal S. Olson, Ryan J. Urbanowicz, Peter C. Andrews, Nicole A. Lavender, La Creis Kidd, Jason H. Moore
2016	J	`jnl`	Automating biomedical data science through tree-based pipeline optimization. CoRR Randal S. Olson, Ryan J. Urbanowicz, Peter C. Andrews, Nicole A. Lavender, La Creis Kidd, Jason H. Moore
2016	A	`conf`	Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science. GECCO Randal S. Olson, Nathan Bartley, Ryan J. Urbanowicz, Jason H. Moore
2016	J	`jnl`	Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science. CoRR Randal S. Olson, Nathan Bartley, Ryan J. Urbanowicz, Jason H. Moore
2016	A	`conf`	Evolution of Active Categorical Image Classification via Saccadic Eye Movement. PPSN Randal S. Olson, Jason H. Moore, Christoph Adami
2016	J	`jnl`	Evolution of Swarming Behavior Is Shaped by How Predators Attack. Artif. Life Randal S. Olson, David B. Knoester, Christoph Adami
2016	J	`jnl`	Evolution of active categorical image classification via saccadic eye movement. CoRR Randal S. Olson, Jason H. Moore, Christoph Adami
2016	C	`conf`	Exploring the coevolution of predator and prey morphology and behavior. ALIFE Christoph Adami, Jason H. Moore, Fred C. Dyer, Arend Hintze, Randal S. Olson
2016	J	`jnl`	Exploring the coevolution of predator and prey morphology and behavior. CoRR Randal S. Olson, Arend Hintze, Fred C. Dyer, Jason H. Moore, Christoph Adami
2016	C	`conf`	Flies as Ship Captains? Digital Evolution Unravels Selective Pressures to Avoid Collision in Drosophila. ALIFE Randal S. Olson, Christoph Adami, Ali Tehrani-Saleh
2016	—	`conf`	Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool. GPTP Randal S. Olson, Jason H. Moore
2016	J	`jnl`	Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool. CoRR Randal S. Olson, Jason H. Moore
2016	—	`conf`	Orthogonally Evolved AI to Improve Difficulty Adjustment in Video Games. EvoApplications (1) Arend Hintze, Randal S. Olson, Joel Lehman
2016	—	`conf`	Pareto Inspired Multi-objective Rule Fitness for Adaptive Rule-based Machine Learning. GECCO (Companion) Ryan J. Urbanowicz, Randal S. Olson, Jason H. Moore
2016	A	`conf`	Pareto Inspired Multi-objective Rule Fitness for Noise-Adaptive Rule-Based Machine Learning. PPSN Ryan J. Urbanowicz, Randal S. Olson, Jason H. Moore
2016	—	`conf`	TPOT: A Tree-based Pipeline Optimization Tool for Automating Machine Learning. AutoML@ICML Randal S. Olson, Jason H. Moore
2015	—	`conf`	Evolving an optimal group size in groups of prey under predation. ECAL Patrick B. Haley, Randal S. Olson, Fred C. Dyer, Christoph Adami
2015	J	`jnl`	Navigating the massive world of reddit: using backbone networks to map user interests in social media. PeerJ Comput. Sci. Randal S. Olson, Zachary P. Neal
2014	C	`conf`	Exploring Conditions That Select for the Evolution of Cooperative Group Foraging. ALIFE Patrick B. Haley, Randal S. Olson, Fred C. Dyer, Christoph Adami
2014	J	`jnl`	Exploring the evolution of a trade-off between vigilance and foraging in group-living organisms. CoRR Randal S. Olson, Patrick B. Haley, Fred C. Dyer, Christoph Adami
2013	A	`conf`	Critical interplay between density-dependent predation and evolution of the selfish herd. GECCO Randal S. Olson, David B. Knoester, Christoph Adami
2013	J	`jnl`	Evolution of swarming behavior is shaped by how predators attack. CoRR Randal S. Olson, David B. Knoester, Christoph Adami
2013	—	`conf`	Evolved digital ecosystems: Dynamic steady state, not optimal fixed point. ECAL Randal S. Olson, Masoud Mirmomeni, Tim Brom, Eric Bruger, Arend Hintze, David B. Knoester, Christoph Adami
2013	J	`jnl`	Navigating the massive world of reddit: Using backbone networks to map user interests in social media. CoRR Randal S. Olson, Zachary P. Neal
2013	J	`jnl`	Risk aversion as an evolutionary adaptation. CoRR Arend Hintze, Randal S. Olson, Christoph Adami, Ralph Hertwig
2012	J	`jnl`	Predator confusion is sufficient to evolve swarming behavior. CoRR Randal S. Olson, Arend Hintze, Fred C. Dyer, David B. Knoester, Christoph Adami

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.