Understanding Simple Asynchronous Evolutionary Algorithms. - Eric O. Scott; Kenneth A. De Jong (FOGA, 2015)

Learning Genetic Representations for Classes of Real-Valued Optimization Problems. - Eric O. Scott; Jeffrey K. Bassett (GECCO (Companion), 2015)

Evaluation-Time Bias in Asynchronous Evolutionary Algorithms. - Eric O. Scott; Kenneth A. De Jong (GECCO (Companion), 2015)

Evaluation-Time Bias in Quasi-Generational and Steady-State Asynchronous Evolutionary Algorithms. - Eric O. Scott; Kenneth A. De Jong (GECCO, 2016)

An Evolutionary Framework for Replicating Neurophysiological Data with Spiking Neural Networks. - Emily L. Rounds; Eric O. Scott; Andrew S. Alexander; Kenneth A. De Jong; Douglas A. Nitz; Jeffrey L. Krichmar (PPSN, 2016)

Landscape Features for Computationally Expensive Evaluation Functions: Revisiting the Problem of Noise. - Eric O. Scott; Kenneth A. De Jong (PPSN, 2016)

Multitask evolution with cartesian genetic programming. - Eric O. Scott; Kenneth A. De Jong (GECCO (Companion), 2017)

Toward learning neural network encodings for continuous optimization problems. - Eric O. Scott; Kenneth A. De Jong (GECCO (Companion), 2018)

Evolving Simple Models of Diverse Intrinsic Dynamics in Hippocampal Neuron Types. - Siva Venkadesh; Alexander O. Komendantov; Stanislav Listopad; Eric O. Scott; Kenneth A. De Jong; Jeffrey L. Krichmar; Giorgio A. Ascoli (Frontiers Neuroinformatics, 2018)

Automating Knowledge Transfer with Multi-Task Optimization. - Eric O. Scott; Kenneth A. De Jong (CEC, 2019)

ECJ at 20: toward a general metaheuristics toolkit. - Eric O. Scott; Sean Luke (GECCO (Companion), 2019)

Distributed, Automated Calibration of Agent-based Model Parameters and Agent Behaviors. - Matteo D'Auria; Eric O. Scott; Rajdeep Singh Lather; Javier Hilty; Sean Luke (AAMAS, 2020)

Library for evolutionary algorithms in Python (LEAP). - Mark Coletti; Eric O. Scott; Jeffrey K. Bassett (GECCO Companion, 2020)

Assisted Parameter and Behavior Calibration in Agent-Based Models with Distributed Optimization. - Matteo D'Auria; Eric O. Scott; Rajdeep Singh Lather; Javier Hilty; Sean Luke (PAAMS, 2020)

Neuroevolution of a recurrent neural network for spatial and working memory in a simulated robotic environment. - Xinyun Zou; Eric O. Scott; Alexander B. Johnson; Kexin Chen 002; Douglas A. Nitz; Kenneth A. De Jong; Jeffrey L. Krichmar (GECCO Companion, 2021)

Differential Spatial Representations in Hippocampal CA1 and Subiculum Emerge in Evolved Spiking Neural Networks. - Kexin Chen 002; Alexander B. Johnson; Eric O. Scott; Xinyun Zou; Kenneth A. De Jong; Douglas A. Nitz; Jeffrey L. Krichmar (IJCNN, 2021)

Avoiding Excess Computation in Asynchronous Evolutionary Algorithms. - Eric O. Scott; Mark Coletti; Catherine D. Schuman; Bill Kay; Shruti R. Kulkarni; Maryam Parsa; Kenneth A. De Jong (UKCI, 2021)

First Complexity Results for Evolutionary Knowledge Transfer. - Eric O. Scott; Kenneth A. De Jong (FOGA, 2023)

Initialization Matters for Asynchronous Steady-State Evolutionary Algorithms. - Eric O. Scott; Kenneth A. De Jong (GECCO Companion, 2023)

Evolving Deformable Mirror Control to Generate Partially Coherent Light Fields. - Daniel Younis; Thomas M. Antonsen Jr.; Luke A. Johnson; Eric O. Scott; Dmitri Kaganovich; Bahman Hafizi (GECCO Companion, 2023)

Avoiding excess computation in asynchronous evolutionary algorithms. - Eric O. Scott; Mark Coletti; Catherine D. Schuman; Bill Kay; Shruti R. Kulkarni; Maryam Parsa; Chathika Gunaratne; Kenneth A. De Jong (Expert Syst. J. Knowl. Eng., 2023)

Varying Difficulty of Knowledge Reuse in Benchmarks for Evolutionary Knowledge Transfer. - Eric O. Scott; Kenneth A. De Jong (CEC, 2024)

Realistic Tax Planning with Evolutionary Algorithms. - Eric O. Scott; Anmol Srivastava; Abby Pusateri; Andy Taylor; Karen Jones; Hahnemann Ortiz (CEC, 2024)

Leveraging LLMs for Legacy Code Modernization: Evaluation of LLM-Generated Documentation. - Colin Diggs; Michael Doyle; Amit Madan; Eric O. Scott; Emily Escamilla; Jacob Zimmer; Naveed Nekoo; Paul Ursino; Michael Bartholf; Zachary Robin; Anand Patel; Chris Glasz; et al. (LLM4Code@ICSE, 2025)

Impact of Comments on LLM Comprehension of Legacy Code. - Rock Sabetto; Emily Escamilla; Devesh Agarwal; Sujay Kandwal; Justin F. Brunelle; Scott Rosen; Nitin Naik; Samruddhi Thaker; Eric O. Scott; Jacob Zimmer; Amit Madan; Arun Sridharan; et al. (CoRR, 2025)

Can LLMs Replace Humans During Code Chunking? - Christopher Glasz; Emily Escamilla; Eric O. Scott; Anand Patel; Jacob Zimmer; Colin Diggs; Michael Doyle; Scott Rosen; Nitin Naik; Justin F. Brunelle; Samruddhi Thaker; Parthav Poudel; et al. (CoRR, 2025)