Load Balancing of Autonomous Actors over Dynamic Networks. - Travis J. Desell; Kaoutar El Maghraoui; Carlos A. Varela (HICSS, 2004)

Towards a middleware framework for dynamically reconfigurable scietific computing. - Kaoutar El Maghraoui; Travis J. Desell; Boleslaw K. Szymanski; James D. Teresco; Carlos A. Varela (High Performance Computing Workshop, 2004)

OverView: A Framework for Generic Online Visualization of Distributed Systems. - Travis J. Desell; Harihar Narasimha-Iyer; Carlos A. Varela; Abe Stephens (eTX, 2004)

Approaches to Architecture-Aware Parallel Scientific Computation. - James D. Teresco; Joseph E. Flaherty; Scott B. Baden; Jamal Faik; Sébastien Lacour; Manish Parashar; Valerie E. Taylor; Carlos A. Varela; Xingfu Wu; Rick Stevens; Nicholas T. Karonis; Ian T. Foster; et al. (Parallel Processing for Scientific Computing, 2006)

The Internet Operating System: Middleware for Adaptive Distributed Computing. - Kaoutar El Maghraoui; Travis J. Desell; Boleslaw K. Szymanski; Carlos A. Varela (Int. J. High Perform. Comput. Appl., 2006)

Dynamic Malleability in Iterative MPI Applications. - Kaoutar El Maghraoui; Travis J. Desell; Boleslaw K. Szymanski; Carlos A. Varela (CCGRID, 2007)

Distributed and Generic Maximum Likelihood Evaluation. - Travis J. Desell; Nathan Cole; Malik Magdon-Ismail; Heidi Jo Newberg; Boleslaw K. Szymanski; Carlos A. Varela (eScience, 2007)

The Effects of Heterogeneity on Asynchronous Panmictic Genetic Search. - Boleslaw K. Szymanski; Travis J. Desell; Carlos A. Varela (PPAM, 2007)

Malleable applications for scalable high performance computing. - Travis J. Desell; Kaoutar El Maghraoui; Carlos A. Varela (Clust. Comput., 2007)

An asynchronous hybrid genetic-simplex search for modeling the Milky Way galaxy using volunteer computing. - Travis J. Desell; Boleslaw K. Szymanski; Carlos A. Varela (GECCO, 2008)

Asynchronous genetic search for scientific modeling on large-scale heterogeneous environments. - Travis J. Desell; Boleslaw K. Szymanski; Carlos A. Varela (IPDPS, 2008)

Robust Asynchronous Optimization for Volunteer Computing Grids. - Travis J. Desell; Malik Magdon-Ismail; Boleslaw K. Szymanski; Carlos A. Varela; Heidi Jo Newberg; Nathan Cole (eScience, 2009)

Accelerating the MilkyWay@Home Volunteer Computing Project with GPUs. - Travis J. Desell; Anthony Waters; Malik Magdon-Ismail; Boleslaw K. Szymanski; Carlos A. Varela; Matthew Newby; Heidi Jo Newberg; Andreas Przystawik; David P. Anderson (PPAM (1), 2009)

Malleable iterative MPI applications. - Kaoutar El Maghraoui; Travis J. Desell; Boleslaw K. Szymanski; Carlos A. Varela (Concurr. Comput. Pract. Exp., 2009)

Asynchronous global optimization for massive-scale computing. - Travis Desell (2009)

An analysis of massively distributed evolutionary algorithms. - Travis J. Desell; David P. Anderson; Malik Magdon-Ismail; Heidi Jo Newberg; Boleslaw K. Szymanski; Carlos A. Varela (IEEE Congress on Evolutionary Computation, 2010)

Validating Evolutionary Algorithms on Volunteer Computing Grids. - Travis J. Desell; Malik Magdon-Ismail; Boleslaw K. Szymanski; Carlos A. Varela; Heidi Jo Newberg; David P. Anderson (DAIS, 2010)

Evolutionary Algorithms on Volunteer Computing Platforms: The MilkyWay@Home Project. - Nathan Cole; Travis J. Desell; Daniel Lombraña Gonzalez; Francisco Fernández de Vega; Malik Magdon-Ismail; Heidi Jo Newberg; Boleslaw K. Szymanski; Carlos A. Varela (Parallel and Distributed Computational Intelligence, 2010)

Evolving N-Body Simulations to Determine the Origin and Structure of the Milky Way Galaxy's Halo Using Volunteer Computing. - Travis J. Desell; Malik Magdon-Ismail; Boleslaw K. Szymanski; Carlos A. Varela; Benjamin A. Willett; Matthew Arsenault; Heidi Jo Newberg (IPDPS Workshops, 2011)

Modular Visualization of Distributed Systems. - Gustavo Guevara; Travis J. Desell; Jason LaPorte; Carlos A. Varela (CLEI Electron. J., 2011)

Password recovery using MPI and CUDA. - David Apostal; Kyle Foerster; Amrita Chatterjee; Travis J. Desell (HiPC, 2012)

Wildlife@Home: Combining Crowd Sourcing and Volunteer Computing to Analyze Avian Nesting Video. - Travis Desell; Robert Bergman; Kyle Goehner; Ronald Marsh; Rebecca VanderClute; Susan Ellis-Felege (e-Science, 2013)

Using Actors and the SALSA Programming Language to Introduce Concurrency in Computer Science II. - Travis J. Desell (IPDPS Workshops, 2013)

SALSA Lite: A Hash-Based Actor Runtime for Efficient Local Concurrency. - Travis J. Desell; Carlos A. Varela (Concurrent Objects and Beyond, 2014)

Performance Improvements for a Large-scale Geological Simulation. - David Apostal; Kyle Foerster; Travis J. Desell; William Gosnold (ICCS, 2014)

Evolving Neural Network Weights for Time-Series Prediction of General Aviation Flight Data. - Travis Desell; Sophine Clachar; James Higgins; Brandon Wild (PPSN, 2014)

Empirical support for the high-density subset sum decision threshold. - Thomas O'Neil; Travis Desell (CWIT, 2015)

A Comparison of Background Subtraction Algorithms for Detecting Avian Nesting Events in Uncontrolled Outdoor Video. - Kyle Goehner; Travis Desell; Rebecca Eckroad; Leila Mohsenian; Paul Burr; Nicolas Caswell; Alicia Andes; Susan Ellis-Felege (e-Science, 2015)

Searching the Human Genome for Snail and Slug with DNA@Home. - Kristopher Zarns; Travis Desell; Sergei Nechaev; Archana Dhasarathy (e-Science, 2015)

Evolving Deep Recurrent Neural Networks Using Ant Colony Optimization. - Travis Desell; Sophine Clachar; James Higgins; Brandon Wild (EvoCOP, 2015)

On the Effectiveness of Crowd Sourcing Avian Nesting Video Analysis at Wildlife@Home. - Travis Desell; Kyle Goehner; Alicia Andes; Rebecca Eckroad; Susan Ellis-Felege (ICCS, 2015)

Detecting wildlife in uncontrolled outdoor video using convolutional neural networks. - Connor Bowley; Alicia Andes; Susan Ellis-Felege; Travis Desell (eScience, 2016)

Using LSTM recurrent neural networks to predict excess vibration events in aircraft engines. - AbdElRahman ElSaid; Brandon Wild; James Higgins; Travis Desell (eScience, 2016)

Developing a citizen science web portal for manual and automated ecological image detection. - Marshall Mattingly; Andrew Barnas; Susan Ellis-Felege; Robert Newman; David Iles; Travis J. Desell (eScience, 2016)

Towards modeling a complex geological simulation. - David Apostal; Sara Faraji Jalal Apostal; Ronald Marsh; Travis Desell (SpringSim (HPS), 2016)

Toward Using Citizen Scientists to Drive Automated Ecological Object Detection in Aerial Imagery. - Connor Bowley; Marshall Mattingly; Andrew Barnas; Susan Ellis-Felege; Travis Desell (eScience, 2017)

Developing a Volunteer Computing Project to Evolve Convolutional Neural Networks and Their Hyperparameters. - Travis Desell (eScience, 2017)

Large scale evolution of convolutional neural networks using volunteer computing. - Travis Desell (GECCO (Companion), 2017)

Optimizing LSTM RNNs using ACO to predict turbine engine vibration. - AbdElRahman ElSaid; Brandon Wild; Fatima El Jamiy; James Higgins; Travis Desell (GECCO (Companion), 2017)

A Robust Asynchronous Newton Method for Massive Scale Computing Systems. - Travis Desell; Malik Magdon-Ismail; Heidi Jo Newberg; Lee A. Newberg; Boleslaw K. Szymanski; Carlos A. Varela (CoRR, 2017)

Accelerating the evolution of convolutional neural networks with node-level mutations and epigenetic weight initialization. - Travis Desell (GECCO (Companion), 2018)

Using ant colony optimization to optimize long short-term memory recurrent neural networks. - AbdElRahman ElSaid; Fatima El Jamiy; James Higgins; Brandon Wild; Travis Desell (GECCO, 2018)

Detecting Wildlife in Unmanned Aerial Systems Imagery Using Convolutional Neural Networks Trained with an Automated Feedback Loop. - Connor Bowley; Marshall Mattingly; Andrew Barnas; Susan Ellis-Felege; Travis Desell (ICCS (1), 2018)

Classifying Aircraft Approach Type in the National General Aviation Flight Information Database. - Kelton Karboviak; Sophine Clachar; Travis Desell; Mark Dusenbury; Wyatt Hedrick; James Higgins; John Walberg; Brandon Wild (ICCS (1), 2018)

Optimizing long short-term memory recurrent neural networks using ant colony optimization to predict turbine engine vibration. - AbdElRahman ElSaid; Fatima El Jamiy; James Higgins; Brandon Wild; Travis Desell (Appl. Soft Comput., 2018)

Evolving Recurrent Neural Networks for Time Series Data Prediction of Coal Plant Parameters. - AbdElRahman ElSaid; Steven A. Benson; Shuchita Patwardhan; David Stadem; Travis Desell (EvoApplications, 2019)

Investigating recurrent neural network memory structures using neuro-evolution. - Alexander Ororbia; AbdElRahman ElSaid; Travis Desell (GECCO, 2019)

Is adaptivity a core property of intelligent systems?: it depends. - AbdElRahman ElSaid; Travis Desell; Daniel E. Krutz (SEAMS@ICSE, 2019)

Improving the Decision-Making Process of Self-Adaptive Systems by Accounting for Tactic Volatility. - Jeffrey Palmerino; Qi Yu 001; Travis Desell; Daniel E. Krutz (ASE, 2019)

Investigating Recurrent Neural Network Memory Structures using Neuro-Evolution. - Alexander Ororbia; Ahmed Ahmed Elsaid; Travis Desell (CoRR, 2019)

An Empirical Exploration of Deep Recurrent Connections and Memory Cells Using Neuro-Evolution. - Travis J. Desell; AbdElRahman ElSaid; Alexander Ororbia (CoRR, 2019)

The Ant Swarm Neuro-Evolution Procedure for Optimizing Recurrent Networks. - AbdElRahman ElSaid; Alexander G. Ororbia II; Travis J. Desell (CoRR, 2019)

An analysis of altitude, citizen science and a convolutional neural network feedback loop on object detection in Unmanned Aerial Systems. - Connor Bowley; Marshall Mattingly; Andrew Barnas; Susan Ellis-Felege; Travis Desell (J. Comput. Sci., 2019)

MaintNet: A Collaborative Open-Source Library for Predictive Maintenance Language Resources. - Farhad Akhbardeh; Travis Desell; Marcos Zampieri (COLING (Demonstrations), 2020)

An Empirical Exploration of Deep Recurrent Connections Using Neuro-Evolution. - Travis Desell; AbdElRahman ElSaid; Alexander G. Ororbia II (EvoApplications, 2020)

Neuro-Evolutionary Transfer Learning Through Structural Adaptation. - AbdElRahman ElSaid; Joshua Karnas; Zimeng Lyu; Daniel E. Krutz; Alexander G. Ororbia II; Travis Desell (EvoApplications, 2020)

Ant-based Neural Topology Search (ANTS) for Optimizing Recurrent Networks. - AbdElRahman ElSaid; Alexander G. Ororbia II; Travis J. Desell (EvoApplications, 2020)

Improving neuroevolutionary transfer learning of deep recurrent neural networks through network-aware adaptation. - AbdElRahman ElSaid; Joshua Karns; Zimeng Lyu; Daniel E. Krutz; Alexander Ororbia; Travis Desell (GECCO, 2020)

NLP Tools for Predictive Maintenance Records in MaintNet. - Farhad Akhbardeh; Travis Desell; Marcos Zampieri (AACL/IJCNLP (System Demonstrations), 2020)

Long term predictions of coal fired power plant data using evolved recurrent neural networks. - Travis J. Desell; AbdElRahman ElSaid; Zimeng Lyu; David Stadem; Shuchita Patwardhan; Steven A. Benson (Autom., 2020)

Improving Neuroevolution Using Island Extinction and Repopulation. - Zimeng Lyu; Joshua Karns; AbdElRahman ElSaid; Travis Desell (CoRR, 2020)

Neuroevolutionary Transfer Learning of Deep Recurrent Neural Networks through Network-Aware Adaptation. - AbdElRahman ElSaid; Joshua Karns; Alexander G. Ororbia II; Daniel E. Krutz; Zimeng Lyu; Travis Desell (CoRR, 2020)

An Experimental Study of Weight Initialization and Weight Inheritance Effects on Neuroevolution. - Zimeng Lyu; AbdElRahman ElSaid; Joshua Karns; Mohamed Wiem Mkaouer; Travis Desell (CoRR, 2020)

Investigating Deep Recurrent Connections and Recurrent Memory Cells Using Neuro-Evolution. - Travis Desell; AbdElRahman ElSaid; Alexander G. Ororbia II (Deep Neural Evolution, 2020)

Handling Extreme Class Imbalance in Technical Logbook Datasets. - Farhad Akhbardeh; Cecilia Ovesdotter Alm; Marcos Zampieri; Travis Desell (ACL/IJCNLP (1), 2021)

Continuous Ant-Based Neural Topology Search. - AbdElRahman ElSaid; Joshua Karns; Zimeng Lyu; Alexander G. Ororbia II; Travis Desell (EvoApplications, 2021)

An Experimental Study of Weight Initialization and Lamarckian Inheritance on Neuroevolution. - Zimeng Lyu; AbdElRahman ElSaid; Joshua Karns; Mohamed Wiem Mkaouer; Travis Desell (EvoApplications, 2021)

Improving Distributed Neuroevolution Using Island Extinction and Repopulation. - Zimeng Lyu; Joshua Karns; AbdElRahman ElSaid; Mohamed Wiem Mkaouer; Travis Desell (EvoApplications, 2021)

Improving the scalability of distributed neuroevolution using modular congruence class generated innovation numbers. - Joshua Karns; Travis Desell (GECCO Companion, 2021)

Neuroevolution of recurrent neural networks for time series forecasting of coal-fired power plant operating parameters. - Zimeng Lyu; Shuchita Patwardhan; David Stadem; James Langfeld; Steven A. Benson; Seth Thoelke; Travis Desell (GECCO Companion, 2021)

Reducing Catastrophic Forgetting in Self Organizing Maps with Internally-Induced Generative Replay. - Hitesh Vaidya; Travis Desell; Alexander Ororbia (CoRR, 2021)

Reducing Catastrophic Forgetting in Self Organizing Maps with Internally-Induced Generative Replay (Student Abstract). - Hitesh Vaidya; Travis Desell; Alexander G. Ororbia II (AAAI, 2022)

Predictive Maintenance for General Aviation Using Convolutional Transformers. - Hong Yang; Aidan P. LaBella; Travis Desell (AAAI, 2022)

Self-adaptation of Neuroevolution Algorithms Using Reinforcement Learning. - Michael Kogan; Joshua Karns; Travis Desell (EvoApplications, 2022)

Addressing tactic volatility in self-adaptive systems using evolved recurrent neural networks and uncertainty reduction tactics. - Aizaz Ul Haq; Niranjana Deshpande; AbdElRahman ElSaid; Travis Desell; Daniel E. Krutz (GECCO, 2022)

ONE-NAS: an online neuroevolution based neural architecture search for time series forecasting. - Zimeng Lyu; Travis Desell (GECCO Companion, 2022)

Transfer Learning Methods for Domain Adaptation in Technical Logbook Datasets. - Farhad Akhbardeh; Marcos Zampieri; Cecilia Ovesdotter Alm; Travis Desell (LREC, 2022)

Optimized flight safety event detection in the national general aviation flight information database. - Aidan P. LaBella; Joshua A. Karns; Farhad Akhbardeh; Travis Desell; Andrew J. Walton; Zechariah Morgan; Brandon Wild; Mark Dusenbury (SAC, 2022)

Robust Augmentation for Multivariate Time Series Classification. - Hong Yang; Travis Desell (CoRR, 2022)

A Large-Scale Annotated Multivariate Time Series Aviation Maintenance Dataset from the NGAFID. - Hong Yang; Travis Desell (CoRR, 2022)

Search-based detection of code changes introducing performance regression. - Deema Alshoaibi; Mohamed Wiem Mkaouer; Ali Ouni 001; Abdulmutalib Wahaishi; Travis Desell; Makram Soui (Swarm Evol. Comput., 2022)

Local Stochastic Differentiable Architecture Search for Memetic Neuroevolution Algorithms. - Joshua Karns; Travis Desell (GECCO Companion, 2023)

Co-evolving Recurrent Neural Networks and their Hyperparameters with Simplex Hyperparameter Optimization. - Amit Dilip Kini; Swaraj Sambhaji Yadav; Aditya Shankar Thakur; Akshar Bajrang Awari; Zimeng Lyu; Travis Desell (GECCO Companion, 2023)

Efficient Neuroevolution Using Island Repopulation and Simplex Hyperparameter Optimization. - Aditya Shankar Thakur; Akshar Bajrang Awari; Zimeng Lyu; Travis Desell (SSCI, 2023)

Predicted Embedding Power Regression for Large-Scale Out-of-Distribution Detection. - Hong Yang; William Gebhardt; Alexander G. Ororbia II; Travis Desell (CoRR, 2023)

Backpropagation-Free 4D Continuous Ant-Based Neural Topology Search. - AbdElRahman ElSaid; Karl Ricanek; Zeming Lyu; Alexander Ororbia; Travis Desell (CoRR, 2023)

Online evolutionary neural architecture search for multivariate non-stationary time series forecasting. - Zimeng Lyu; Alexander Ororbia; Travis Desell (Appl. Soft Comput., 2023)

Backpropagation-free 4D continuous ant-based neural topology search. - AbdElRahman ElSaid; Karl Ricanek; Zimeng Lyu; Alexander Ororbia; Travis Desell (Appl. Soft Comput., 2023)

Enabling An Informed Contextual Multi-Armed Bandit Framework For Stock Trading With Neuroevolution. - Devroop Kar; Zimeng Lyu; Alexander G. Ororbia II; Travis Desell; Daniel E. Krutz (GECCO Companion, 2024)

Minimizing the EXA-GP Graph-Based Genetic Programming Algorithm for Interpretable Time Series Forecasting. - Jared Murphy; Travis Desell (GECCO Companion, 2024)

EXA-GP: Unifying Graph-Based Genetic Programming and Neuroevolution for Explainable Time Series Forecasting. - Jared Murphy; Devroop Kar; Joshua Karns; Travis Desell (GECCO Companion, 2024)

Minimally Supervised Topological Projections of Self-Organizing Maps for Phase of Flight Identification. - Zimeng Lyu; Pujan Thapa; Travis Desell (IJCNN, 2024)

Minimally Supervised Learning using Topological Projections in Self-Organizing Maps. - Zimeng Lyu; Alexander Ororbia; Rui Li; Travis Desell (CoRR, 2024)

Neuro-mimetic Task-free Unsupervised Online Learning with Continual Self-Organizing Maps. - Hitesh Vaidya; Travis Desell; Ankur Arjun Mali; Alexander Ororbia (CoRR, 2024)

Neuroevolution Neural Architecture Search for Evolving RNNs in Stock Return Prediction and Portfolio Trading. - Zimeng Lyu; Amulya Saxena; Rohaan Nadeem; Hao Zhang; Travis Desell (CoRR, 2024)

Evolving RNNs for Stock Forecasting: A Low Parameter Efficient Alternative to Transformers. - Zimeng Lyu; Devroop Kar; Matthew Simoni; Rohaan Nadeem; Avinash Bhojanapalli; Hao Zhang; Travis Desell (EvoApplications (2), 2025)

Evaluation Time Bias in Asynchronous Evolutionary Algorithms: A Replication Study and a Novel Mitigation Strategy. - Joshua Karns; Travis Desell (GECCO, 2025)

Visualizing the Dynamics of Neuroevolution with Genetic Distance Projections. - Evan Patterson; Joshua Karns; Zimeng Lyu; Travis Desell (GECCO, 2025)

Can We Ignore Labels in Out of Distribution Detection? - Hong Yang; Qi Yu 001; Travis Desell (ICLR, 2025)

Directly Learning Stock Trading Strategies Through Profit Guided Loss Functions. - Devroop Kar; Zimeng Lyu; Sheeraja Rajakrishnan; Hao Zhang; Alexander Ororbia; Travis Desell; Daniel E. Krutz (CoRR, 2025)