Unshackling evolution: evolving soft robots with multiple materials and a powerful generative encoding. - Nick Cheney; Robert MacCurdy; Jeff Clune; Hod Lipson (GECCO, 2013)

Hands-free Evolution of 3D-printable Objects via Eye Tracking - Nick Cheney; Jeff Clune; Jason Yosinski; Hod Lipson (CoRR, 2013)

Evolved Electrophysiological Soft Robots. - Nicholas Cheney; Jeff Clune; Hod Lipson (ALIFE, 2014)

Automated vibrational design and natural frequency tuning of multi-material structures. - Nicholas Cheney; Ethan Ritz; Hod Lipson (GECCO, 2014)

Evolving Soft Robots in Tight Spaces. - Nick Cheney; Josh C. Bongard; Hod Lipson (GECCO, 2015)

Material properties affect evolutions ability to exploit morphological computation in growing soft-bodied creatures. - Josh C. Bongard; Cecilia Laschi; Hod Lipson; Nick Cheney; Francesco Corucci (ALIFE, 2016)

On the Difficulty of Co-Optimizing Morphology and Control in Evolved Virtual Creatures. - Hod Lipson; Vytas SunSpiral; Josh C. Bongard; Nicholas Cheney (ALIFE, 2016)

How the Strictness of the Minimal Criterion Impacts Open-Ended Evolution. - Kenneth O. Stanley; Nick Cheney; Lisa B. Soros (ALIFE, 2016)

Topological evolution for embodied cellular automata. - Nick Cheney; Hod Lipson (Theor. Comput. Sci., 2016)

A minimal developmental model can increase evolvability in soft robots. - Sam Kriegman; Nick Cheney; Francesco Corucci; Josh C. Bongard (GECCO, 2017)

Simulating the evolution of soft and rigid-body robots. - Sam Kriegman; Collin Cappelle; Francesco Corucci; Anton Bernatskiy; Nick Cheney; Josh C. Bongard (GECCO (Companion), 2017)

Scalable Co-Optimization of Morphology and Control in Embodied Machines. - Nick Cheney; Josh C. Bongard; Vytas SunSpiral; Hod Lipson (CoRR, 2017)

On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations. - Nicholas Cheney; Martin Schrimpf; Gabriel Kreiman (CoRR, 2017)

Evolving soft locomotion in aquatic and terrestrial environments: effects of material properties and environmental transitions. - Francesco Corucci; Nick Cheney; Francesco Giorgio-Serchi; Josh C. Bongard; Cecilia Laschi (CoRR, 2017)

How morphological development can guide evolution. - Sam Kriegman; Nick Cheney; Josh C. Bongard (CoRR, 2017)

Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants. - Francesco Corucci; Nick Cheney; Sam Kriegman; Josh C. Bongard; Cecilia Laschi (Frontiers Robotics AI, 2017)

Interoceptive robustness through environment-mediated morphological development. - Sam Kriegman; Nick Cheney; Francesco Corucci; Josh C. Bongard (GECCO, 2018)

EVO-SCHIRP: Evolved Secure Swarm Communications. - Shaya Wolf; Rafer Cooley; Mike Borowczak; Nicholas Cheney (ISC2, 2018)

Using Digital Field Experiments To Elicit Risk Mitigation Behavioral Strategies For Disease Management Across Agricultural Production Systems. - Eric M. Clark; Scott C. Merrill; Luke Trinity; Gabriela Bucini; Nicholas Cheney; Ollin Langle-Chimal; Trisha Shrum; Christopher Koliba; Asim Zia; Julia M. Smith (CoRR, 2019)

Embodiment dictates learnability in neural controllers. - Joshua P. Powers; Ryan Grindle; Sam Kriegman; Lapo Frati; Nick Cheney; Josh C. Bongard (CoRR, 2019)

Estimating Biomechanical Time-Series with Wearable Sensors: A Systematic Review of Machine Learning Techniques. - Reed D. Gurchiek; Nick Cheney; Ryan S. McGinnis (Sensors, 2019)

Learning to Continually Learn. - Shawn Beaulieu; Lapo Frati; Thomas Miconi; Joel Lehman; Kenneth O. Stanley; Jeff Clune; Nick Cheney (ECAI, 2020)

Morphology dictates learnability in neural controllers. - Joshua P. Powers; Ryan Grindle; Sam Kriegman; Lapo Frati; Nick Cheney; Josh C. Bongard (ALIFE, 2020)

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities. - Joel Lehman; Jeff Clune; Dusan Misevic; Christoph Adami; Lee Altenberg; Julie Beaulieu; Peter J. Bentley; Samuel Bernard; Guillaume Beslon; David M. Bryson; Nick Cheney; Patryk Chrabaszcz; et al. (Artif. Life, 2020)

Interpretable bias mitigation for textual data: Reducing gender bias in patient notes while maintaining classification performance. - Joshua R. Minot; Nicholas Cheney; Marc Maier; Danne C. Elbers; Christopher M. Danforth; Peter Sheridan Dodds (CoRR, 2021)

Continual learning under domain transfer with sparse synaptic bursting. - Shawn L. Beaulieu; Jeff Clune; Nick Cheney (CoRR, 2021)

Wearables and Deep Learning Classify Fall Risk From Gait in Multiple Sclerosis. - Brett M. Meyer; Lindsey J. Tulipani; Reed D. Gurchiek; Dakota A. Allen; Lukas Adamowicz; Dale Larie; Andrew J. Solomon; Nick Cheney; Ryan S. McGinnis (IEEE J. Biomed. Health Informatics, 2021)

UVM KID Study: Identifying Multimodal Features and Optimizing Wearable Instrumentation to Detect Child Anxiety. - Bryn C. Loftness; Julia Halvorson-Phelan; Aisling O'Leary; Nick Cheney; Ellen W. McGinnis; Ryan S. McGinnis (EMBC, 2022)

Editorial: Evolving Robotic Morphologies. - David Howard 001; Kyrre Glette; Nick Cheney (Frontiers Robotics AI, 2022)

Interpretable Bias Mitigation for Textual Data: Reducing Genderization in Patient Notes While Maintaining Classification Performance. - Joshua R. Minot; Nicholas Cheney; Marc Maier; Danne C. Elbers; Christopher M. Danforth; Peter Sheridan Dodds (ACM Trans. Comput. Heal., 2022)

Biological underpinnings for lifelong learning machines. - Dhireesha Kudithipudi; Mario Aguilar-Simon; Jonathan Babb; Maxim Bazhenov; Douglas Blackiston; Josh C. Bongard; Andrew P. Brna; Suraj Chakravarthi Raja; Nick Cheney; Jeff Clune; Anurag Reddy Daram; Stefano Fusi; et al. (Nat. Mach. Intell., 2022)

How Much Data Is Enough? A Reliable Methodology to Examine Long-Term Wearable Data Acquisition in Gait and Postural Sway. - Brett M. Meyer; Paolo DePetrillo; Jaime Franco; Nicole Donahue; Samantha R. Fox; Aisling O'Leary; Bryn C. Loftness; Reed D. Gurchiek; Maura Buckley; Andrew J. Solomon; Sau Kuen Ng; Nick Cheney; et al. (Sensors, 2022)

Preterm Preeclampsia Risk Modelling: Examining Hemodynamic, Biochemical, and Biophysical Markers Prior to Pregnancy. - Bryn C. Loftness; Ira Bernstein; Carole A. McBride; Nick Cheney; Ellen W. McGinnis; Ryan S. McGinnis (EMBC, 2023)

Toward Digital Phenotypes of Early Childhood Mental Health via Unsupervised and Supervised Machine Learning. - Bryn C. Loftness; Donna M. Rizzo; Julia Halvorson-Phelan; Aisling O'Leary; Shania Prytherch; Carter Bradshaw; Anna Jane Brown; Nick Cheney; Ellen W. McGinnis; Ryan S. McGinnis (EMBC, 2023)

Neighbor-Hop Mutation for Genetic Algorithm in Influence Maximization. - Aviral Chawla; Nick Cheney (GECCO Companion, 2023)

Many-objective Optimization via Voting for Elites. - Jackson Dean; Nick Cheney (GECCO Companion, 2023)

OmnImage: Evolving 1k Image Cliques for Few-Shot Learning. - Lapo Frati; Neil Traft; Nick Cheney (GECCO, 2023)

Modular Controllers Facilitate the Co-Optimization of Morphology and Control in Soft Robots. - Alican Mertan; Nick Cheney (GECCO, 2023)

Coping with seasons: evolutionary dynamics of gene networks in a changing environment. - Csenge Petak; Lapo Frati; Melissa Helen Pespeni; Nick Cheney (GECCO Companion, 2023)

Evolving Robust Facility Placements. - Will Thompson; Alex Freidrichsen; Christopher M. Danforth; Peter Sheridan Dodds; Nicholas Cheney (GECCO Companion, 2023)

Temporal Evolution of Risk Behavior in a Disease Spread Simulation. - Ollin D. Langle-Chimal; Scott C. Merrill; Eric M. Clark; Gabriela Bucini; Tung-Lin Liu; Trisha R. Shrum; Christopher Koliba; Asim Zia; Julia M. Smith; Nicholas Cheney (CoRR, 2023)

The Resume Paradox: Greater Language Differences, Smaller Pay Gaps. - Joshua R. Minot; Marc Maier; Bradford Demarest; Nicholas Cheney; Christopher M. Danforth; Peter Sheridan Dodds; Morgan R. Frank (CoRR, 2023)

Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning. - Lapo Frati; Neil Traft; Jeff Clune; Nick Cheney (ECAI, 2024)

Investigating Premature Convergence in Co-optimization of Morphology and Control in Evolved Virtual Soft Robots. - Alican Mertan; Nick Cheney (EuroGP, 2024)

Towards Multi-Morphology Controllers with Diversity and Knowledge Distillation. - Alican Mertan; Nick Cheney (GECCO, 2024)

No-brainer: Morphological Computation Driven Adaptive Behavior in Soft Robots. - Alican Mertan; Nick Cheney (SAB, 2024)

The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health. - Bryn C. Loftness; Julia Halvorson-Phelan; Aisling O'Leary; Carter Bradshaw; Shania Prytherch; Isabel Berman; John B. Torous; William E. Copeland; Nick Cheney; Ryan S. McGinnis; Ellen W. McGinnis (IEEE J. Biomed. Health Informatics, 2024)

Controller Distillation Reduces Fragile Brain-Body Co-Adaptation and Enables Migrations in MAP-Elites. - Alican Mertan; Nick Cheney (GECCO, 2025)

How Weight Resampling and Optimizers Shape the Dynamics of Continual Learning and Forgetting in Neural Networks. - Lapo Frati; Neil Traft; Jeff Clune; Nick Cheney (CoRR, 2025)