Vector Prediction Approach to Handle Dynamical Optimization Problems. - Bojin Zheng; Yuanxiang Li 001; Ting Hu 001 (SEAL, 2006)

A Novel Multi-objective Evolutionary Algorithm. - Bojin Zheng; Ting Hu 001 (International Conference on Computational Science (4), 2007)

Measuring rate of evolution in genetic programming using amino acid to synonymous substitution ratio ka/ks. - Ting Hu 001; Wolfgang Banzhaf (GECCO, 2008)

Nonsynonymous to Synonymous Substitution Ratio ka/ks: Measurement for Rate of Evolution in Evolutionary Computation. - Ting Hu 001; Wolfgang Banzhaf (PPSN, 2008)

The Role of Population Size in Rate of Evolution in Genetic Programming. - Ting Hu 001; Wolfgang Banzhaf (EuroGP, 2009)

Neutrality and variability: two sides of evolvability in linear genetic programming. - Ting Hu 001; Wolfgang Banzhaf (GECCO, 2009)

An evolutionary approach to planning IEEE 802.16 networks. - Ting Hu 001; Yuanzhu Peter Chen; Wolfgang Banzhaf; Robert Benkoczi (GECCO, 2009)

WiMAX Network Planning Using Adaptive-Population-Size Genetic Algorithm. - Ting Hu 001; Yuanzhu Peter Chen; Wolfgang Banzhaf (EvoApplications (2), 2010)

Variable population size and evolution acceleration: a case study with a parallel evolutionary algorithm. - Ting Hu 001; Simon Harding; Wolfgang Banzhaf (Genet. Program. Evolvable Mach., 2010)

Robustness, Evolvability, and Accessibility in Linear Genetic Programming. - Ting Hu 001; Joshua L. Payne; Wolfgang Banzhaf; Jason H. Moore (EuroGP, 2011)

Characterizing Genetic Interactions in Human Disease Association Studies Using Statistical Epistasis Networks. - Ting Hu 001; Nicholas A. Sinnott-Armstrong; Jeff Kiralis; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (BMC Bioinform., 2011)

Lévy-Flight Genetic Programming: Towards a New Mutation Paradigm. - Christian Darabos; Mario Giacobini; Ting Hu 001; Jason H. Moore (EvoBIO, 2012)

Evolutionary dynamics on multiple scales: a quantitative analysis of the interplay between genotype, phenotype, and fitness in linear genetic programming. - Ting Hu 001; Joshua L. Payne; Wolfgang Banzhaf; Jason H. Moore (Genet. Program. Evolvable Mach., 2012)

Bipartite Networks Show the Genotype-to-Phenotype Relationship in Biological Systems Models: A Study of the Robustness, Evolvability, and Accessibility in Linear Cellular Automata. - Christian Darabos; Britney E. Graham; Ting Hu 001; Jason H. Moore (ECAL, 2013)

Bladder cancer specific pathway interaction networks. - Qinxin Pan; Ting Hu 001; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (ECAL, 2013)

Robustness and Evolvability of Recombination in Linear Genetic Programming. - Ting Hu 001; Wolfgang Banzhaf; Jason H. Moore (EuroGP, 2013)

Supervising Random Forest Using Attribute Interaction Networks. - Qinxin Pan; Ting Hu 001; James D. Malley; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (EvoBIO, 2013)

Bipartite networks to study the genotype-to-phenotype relationship in cellular automata models. - Christian Darabos; Britney E. Graham; Ting Hu 001; Jason H. Moore (GECCO (Companion), 2013)

Statistical Epistasis Networks Reduce the Computational Complexity of Searching Three-Locus Genetic Models. - Ting Hu 001; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (Pacific Symposium on Biocomputing, 2013)

Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis. - Ryan L. Collins; Ting Hu 001; Christian Wejse; Giorgio Sirugo; Scott M. Williams; Jason H. Moore (BioData Min., 2013)

Research and applications: An information-gain approach to detecting three-way epistatic interactions in genetic association studies. - Ting Hu 001; Yuanzhu Peter Chen; Jeff Kiralis; Ryan L. Collins; Christian Wejse; Giorgio Sirugo; Scott M. Williams; Jason H. Moore (J. Am. Medical Informatics Assoc., 2013)

Population Exploration on Genotype Networks in Genetic Programming. - Ting Hu 001; Wolfgang Banzhaf; Jason H. Moore (PPSN, 2014)

The Effects of Recombination on Phenotypic Exploration and Robustness in Evolution. - Ting Hu 001; Wolfgang Banzhaf; Jason H. Moore (Artif. Life, 2014)

Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility. - Ting Hu 001; Qinxin Pan; Angeline S. Andrew; Jillian M. Langer; Michael D. Cole; Craig R. Tomlinson; Margaret R. Karagas; Jason H. Moore (BioData Min., 2014)

Computational genetics analysis of grey matter density in Alzheimer's disease. - Amanda L. Zieselman; Jonathan M. Fisher; Ting Hu 001; Peter C. Andrews; Casey S. Greene; Li Shen 001; Andrew J. Saykin; Jason H. Moore (BioData Min., 2014)

Genome-Wide Genetic Interaction Analysis of Glaucoma Using Expert Knowledge Derived from Human Phenotype Networks. - Ting Hu 001; Christian Darabos; Maria E. Cricco; Emily Kong; Jason H. Moore (Pacific Symposium on Biocomputing, 2015)

Characterizing gene-gene interactions in a statistical epistasis network of twelve candidate genes for obesity. - Rishika De; Ting Hu 001; Jason H. Moore; Diane Gilbert-Diamond (BioData Min., 2015)

Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networks. - Ting Hu 001; Angeline S. Andrew; Margaret R. Karagas; Jason H. Moore (BioData Min., 2015)

Evolutionary algorithmic deployment of radio beacons for indoor positioning. - Sipan Ye; Yuanzhu Peter Chen; Ting Hu 001 (CEC, 2016)

Quantitative Analysis of Evolvability using Vertex Centralities in Phenotype Network. - Ting Hu 001; Wolfgang Banzhaf (GECCO, 2016)

Neutrality, Robustness, and Evolvability in Genetic Programming. - Ting Hu 001; Wolfgang Banzhaf (GPTP, 2016)

Metabolomics Differential Correlation Network Analysis of Osteoarthritis. - Ting Hu 001; Weidong Zhang; Zhaozhi Fan; Guang Sun; Sergei Likhodi; Edward Randell; Guangju Zhai (PSB, 2016)

Toward Understanding Hidden Patterns in Human Mobility Using Wi-Fi. - Ali Farrokhtala; Yuanzhu Chen 001; Ting Hu 001; Sipan Ye (CCECE, 2018)

Observing Friendship Patterns Through Smart Phone Radios. - Sipan Ye; Yuanzhu Chen 001; Ting Hu 001; Jooyoung Son; Qing Li 005; Ali Farrokhtala (CCECE, 2018)

Analyzing Feature Importance for Metabolomics Using Genetic Programming. - Ting Hu 001; Karoliina Oksanen; Weidong Zhang; Edward Randell; Andrew Furey; Guangju Zhai (EuroGP, 2018)

Feature Selection for Detecting Gene-Gene Interactions in Genome-Wide Association Studies. - Faramarz Dorani; Ting Hu 001 (EvoApplications, 2018)

Measuring evolvability and accessibility using the hyperlink-induced topic search algorithm. - Kyle L. Nickerson; Yuanzhu Chen 001; Feng Wang; Ting Hu 001 (GECCO, 2018)

Soft Computing for Analysis of Biomedical Data. - Federico Divina; Miguel García-Torres; Ting Hu 001; Christian E. Schaerer (Comput. Math. Methods Medicine, 2018)

An evolutionary learning and network approach to identifying key metabolites for osteoarthritis. - Ting Hu 001; Karoliina Oksanen; Weidong Zhang; Edward Randell; Andrew Furey; Guang Sun; Guangju Zhai (PLoS Comput. Biol., 2018)

Complex Network Analysis of a Genetic Programming Phenotype Network. - Ting Hu 001; Marco Tomassini; Wolfgang Banzhaf (EuroGP, 2019)

Fault Detection and Classification for Induction Motors Using Genetic Programming. - Yu Zhang; Ting Hu 001; Xiaodong Liang; Mohammad Zawad Ali; Md. Nasmus Sakib Khan Shabbir (EuroGP, 2019)

The Time Element of Temporal Networks. - Ali Farrokhtala; Yuanzhu Chen 001; Ting Hu 001 (GLOBECOM, 2019)

Classification of Autism Genes Using Network Science and Linear Genetic Programming. - Yu Zhang; Yuanzhu Chen 001; Ting Hu 001 (EuroGP, 2020)

Practical Strategy of Acquaintance Immunization without Contact Tracing. - Zhihao Dong; Yuanzhu Chen 001; Terrence S. Tricco; Cheng Li 005; Ting Hu 001 (ISPA/BDCloud/SocialCom/SustainCom, 2020)

Special issue on highlights of genetic programming 2019 events. - Ting Hu 001; Miguel Nicolau; Lukás Sekanina (Genet. Program. Evolvable Mach., 2020)

A network perspective on genotype-phenotype mapping in genetic programming. - Ting Hu 001; Marco Tomassini; Wolfgang Banzhaf (Genet. Program. Evolvable Mach., 2020)

Feature Selection for Polygenic Risk Scores using Genetic Algorithm and Network Science. - Zhendong Sha; Ting Hu 001; Yuanzhu Chen 001 (CEC, 2021)

Principled quality diversity for ensemble classifiers using MAP-Elites. - Kyle L. Nickerson; Ting Hu 001 (GECCO Companion, 2021)

An evolutionary approach to interpretable learning. - Jake Robertson; Ting Hu 001 (GECCO Companion, 2021)

A Bio-Inspired Framework for Machine Bias Interpretation. - Jake Robertson; Catherine Stinson; Ting Hu 001 (AIES, 2022)

geneDRAGNN: Gene Disease Prioritization using Graph Neural Networks. - Awni Altabaa; David Huang; Ciaran Byles-Ho; Hani Khatib; Fabian Sosa; Ting Hu 001 (CIBCB, 2022)

Creating Diverse Ensembles for Classification with Genetic Programming and Neuro-MAP-Elites. - Kyle L. Nickerson; Antonina Kolokolova; Ting Hu 001 (EuroGP, 2022)

Permutation-Invariant Representation of Neural Networks with Neuron Embeddings. - Ryan Zhou; Christian Muise; Ting Hu 001 (EuroGP, 2022)

Genetic heterogeneity analysis using genetic algorithm and network science. - Zhendong Sha; Yuanzhu Peter Chen; Ting Hu 001 (GECCO Companion, 2022)

Regulatory genotype-to-phenotype mappings improve evolvability in genetic programming. - Jinting Zhang; Ting Hu 001 (GECCO Companion, 2022)

Banksformer: A Deep Generative Model for Synthetic Transaction Sequences. - Kyle L. Nickerson; Terrence S. Tricco; Antonina Kolokolova; Farzaneh Shoeleh; Charles Robertson; John Hawkin; Ting Hu 001 (ECML/PKDD (6), 2022)

Editorial Introduction. - Leonardo Trujillo; Ting Hu 001; Nuno Lourenço 002; Mengjie Zhang 001 (Genet. Program. Evolvable Mach., 2022)

Phenotype Search Trajectory Networks for Linear Genetic Programming. - Ting Hu 001; Gabriela Ochoa; Wolfgang Banzhaf (EuroGP, 2023)

Evolving Better Initializations For Neural Networks With Pruning. - Ryan Zhou; Ting Hu 001 (GECCO Companion, 2023)

How the Combinatorics of Neutral Spaces Leads Genetic Programming to Discover Simple Solutions. - Wolfgang Banzhaf; Ting Hu 001; Gabriela Ochoa (GPTP, 2023)

Evolutionary approaches to explainable machine learning. - Ryan Zhou; Ting Hu 001 (CoRR, 2023)

How complex is the microarray dataset? A novel data complexity metric for biological high-dimensional microarray data. - Zhendong Sha; Li Zhu; Zijun Jiang; Yuanzhu Peter Chen; Ting Hu 001 (CoRR, 2023)

Linear Genetic Programming. - Wolfgang Banzhaf; Ting Hu 001 (GECCO Companion, 2024)

ATOMIC: an Interpretable Clustering Method Based on Data Topology. - Matthew Vandergrift; Ting Hu 001 (GECCO Companion, 2024)

Distinct network patterns emerge from Cartesian and XOR epistasis models: a comparative network science analysis. - Zhendong Sha; Philip J. Freda; Priyanka Bhandary; Attri Ghosh; Nicholas Matsumoto; Jason H. Moore; Ting Hu 001 (BioData Min., 2024)

Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems. - Ryan Zhou; Jaume Bacardit; Alexander E. I. Brownlee; Stefano Cagnoni; Martin Fyvie; Giovanni Iacca; John A. W. McCall; Niki van Stein; David Walker 003; Ting Hu 001 (CoRR, 2024)

Ego-Aware Graph Neural Network. - Zhihao Dong; Yuanzhu Chen 001; Terrence S. Tricco; Cheng Li 005; Ting Hu 001 (IEEE Trans. Netw. Sci. Eng., 2024)

How Neutrality Shapes Evolution: Simplicity Bias and Search. - Ting Hu 001; Wolfgang Banzhaf; Gabriela Ochoa (GECCO, 2025)

Editorial introduction for the special issue on highlights of genetic programming 2023 events. - Gisele L. Pappa; Mario Giacobini; Ting Hu 001; Domagoj Jakobovic (Genet. Program. Evolvable Mach., 2025)