Travis Desell, Ph.D.

Associate Professor
Department of Software Engineering
Rochester Institute of Technology

About Me


I am an Associate Professor specializing in Data Science, housed in the Department of Software Engineering in the B. Thomas Golisano College of Computing and Information Sciences (GCCIS). My research focuses on the application of machine learning to large-scale, real world data sets using high performance and distributed computing, with an emphasis on developing systems for practical scientific use. I'm interested in the intersection of evolutionary algorithms and neural networks, or "neuro-evolution", where evolutionary algorithms are used to automate and optimize the design of neural network architectures. I am actively developing the Evolutionary eXploration of Augmenting Convolutional Toplogies (EXACT) and Evolutionary eXploration of Augmenting Memory Models (EXAMM, formerly known as EXALT) algorithms, which are hosted on GitHub.

I am also active in the area of volunteer computing and citizen science, where I did the initial development of MilkyWay@Home, and more recently the Citizen Science Grid and NSF funded Wildlife@Home which has volunteer citizen scientists annotate hundreds of thousands of hours of video and millions of images to help in the development of computer vision algorithms. Recent work on Wildlife@Home has focused on the development of convolutional neural networks to detect various wildlife species in imagery collected from unmanned aerial systems.

My currently funded research projects include the National General Aviation Flight Information Database (NGAFID), used by general aviation institutions across the country to monitor and predict potential flight safety issues. We are actively developing an interface and methods to detect potential flight issues, trends and mine this massive database of over 800,000 hours of flight data. I am also working on Department of Energy Award #FE0031547, Improving Coal Fired Plant Performance through Integrated Predictive and Condition-Based Monitoring Tools, where we are developing neuro-evolution algorithms to evolve recurrent neural networks to predict coal fired power plant data.

I have also been a main contributor in the development of both the compiler and runtime of SALSA and SALSA Lite, a programming language based on the actor model of computation. SALSA enables easy development of concurrent and transparently distributed applications by following actor semantics.

Contact Information


Email:

tjdvse@rit.edu
Email is the best and most reliable way to contact me.

Office Hours:

GOL (70) - 1559
Monday: 9:00am - 9:50am
Wednesday: 9:00am - 9:50am
Friday : 9:00am - 9:50am
or by appointment.

Address

Department of Software Engineering
GOL 70-1559
Rochester Institute of Technology
134 Lomb Memorial Drive
Rochester, NY 14623

Publications


Data Releases

  1. Wildlife@Home. [Last Update: April 1, 2015]
  2. National General Aviation Flight Information Database (NGAFID). [Last Update: October 20, 2014]


Theses

  1. Travis Desell. Asynchronous Global Optimization for Massive-Scale Computing. PhD Thesis. Rensselaer Polytechnic Institute. December 2009. [pdf]
  2. Travis Desell. Autonomic Grid Computing using Malleability and Migration: An Actor-Oriented Software Framework. Master's Thesis. Rensselaer Polytechnic Institute. May 2007. [pdf]


Books

  1. Sima Noghanian, Abas Sabouni, Travis Desell and Ali Ashtari. Microwave Tomography - Global Optimization, Parallelization and Performance Evaluation. Springer. 2014. [html]


Book Chapters

  1. Nathan Cole, Travis Desell, Daniel Lombranaa Gonzalez, Francisco Fernandez de Vega, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski and Carlos A. Varela. Evolutionary Algorithms on Volunteer Computing Platforms: The MilkyWay@Home Project. In F. Fernandez de Vega, E. Cantu-Paz (Eds.): Parallel and Distributed Computational Intelligence. SCI 269, pages 63-90. Springer-Verlag Berlin Heidelberg. 2010. [pdf]
  2. Kaoutar El Maghraoui, Travis Desell, Boleslaw K. Szymanski, James D. Teresco, and Carlos A. Varela. Towards a Middleware Framework for Dynamically Reconfigurable Scientific Computing. In L. Grandinetti, editor, Grid Computing and New Frontiers of High Performance Processing. Advances in Parallel Computing, Volume 14, pages 275-301. Elsevier. 2005. [pdf]


Journal Articles

  1. AbdElRahman ElSaid, Alexander G. Ororbia and Travis Desell. The Ant Swarm Neuro-Evolution Procedure for Optimizing Recurrent Networks. arXiv: Neural and Evolutionary Computing (cs.NE). September, 2019. [pdf]
  2. Travis Desell, AbdElRahman ElSaid and Alexander G. Ororbia. An Empirical Exploration of Deep Recurrent Connections and Memory Cells Using Neuro-Evolution. arXiv: Neural and Evolutionary Computing (cs.NE). September, 2019. [pdf]
  3. Connor Bowley, Marshall Mattingly, Andrew Barnas, Susan Ellis-Felege and Travis Desell. An Analysis of Altitude, Citizen Science and a Convolutional Neural Network Feedback Loop on Object Detection in Unmanned Aerial Systems. Journal of Computational Science. May, 2019. [pdf]
  4. Alex Ororbia, AbdElRahman ElSaid and Travis Desell. Investigating Recurrent Neural Network Memory Structures using Neuro-Evolution. arXiv: Neural and Evolutionary Computing (cs.NE). February, 2019. [pdf]
  5. Travis Desell. Accelerating the Evolution of Convolutional Neural Networks with Node-Level Mutations and Epigenetic Weight Initialization. arXiv: Neural and Evolutionary Computing (cs.NE). November, 2018. [pdf]
  6. Jake Weiss, Heidi Jo Newberg, Matthew Newby, and Travis Desell. Fitting the Density Substructure of the Stellar Halo with MilkyWay@Home. The Astrophysical Journal Supplement Series, Volume 238, Number 2. September, 2018. [pdf]
  7. AbdElRahman ElSaid, Travis Desell, Fatima El Jamiy, James Higgins and Brandon Wild. Optimizing Long Short-Term Memory Recurrent Neural Networks Using Ant Colony Optimization to Predict Turbine Engine Vibration. Applied Soft Computing. Volume 73, Pages 969-991. December, 2018. [pdf]
  8. Andrei P. Kirilenko, Travis Desell, Hany Kim, and Svetlana Stepchenkova. Crowdsourcing Analysis of Twitter Data on Climate Change: Paid Workers vs. Volunteers. Sustainability. November 3, 2017. [pdf]
  9. AbdElRahman ElSaid, Travis Desell, Fatima El Jamiy, James Higgins and Brandon Wild. Optimizing Long Short-Term Memory Recurrent Neural Networks Using Ant Colony Optimization to Predict Turbine Engine Vibration. arXiv: Neural and Evolutionary Computing (cs.NE). October 10, 2017. [pdf]
  10. Travis Desell. Large Scale Evolution of Convolutional Neural Networks Using Volunteer Computing. arXiv: Neural and Evolutionary Computing (cs.NE). March 15, 2017. [pdf]
  11. Susan N. Ellis-Felege, Travis Desell and Christopher J. Felege. A Bird's Eye View of... Birds: Combining Technology and Citizen Science for Conservation. Wildlife Professional 8: 27-30. Spring 2014. PDF courtsey of The Wildlife Professional. [pdf]
  12. Travis Desell and Carlos Varela. SALSA Lite: A Hash-Based Actor Runtime for Efficient Local Concurrency. Springer Lecture Notes in Computer Science: Concurrent Objects and Beyond. 23 pages. 2013. [pdf]
  13. Matthew Newby, Nathan Cole, Heidi Jo Newberg, Travis Desell, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos Varela, Benjamin Willett, and Brian Yanny. A Spatial Characterization of the Sagittarius Dwarf Galaxy Tidal Tails. The Astronomical Journal. Volume 145, Number 6. May 2013. [pdf]
  14. Travis Desell, Jason LaPorte, Carlos A. Varela, and Gustavo Guevara. Modular Visualization of Distributed Systems. CLEI (Latin-american Center for Informatics Studies) Electronic Journal: Special issue of best papers presented at CLEI'2010. Volume 14, Number 1, Paper 7. April 2011. [pdf]
  15. Kaoutar El Maghraoui, Travis Desell, Boleslaw K. Szymanski, and Carlos A. Varela. Malleable Iterative MPI Applications. Concurrency and Computation: Practice and Experience. Volume 21, Issue 3, pages 393-413. March 2009. [pdf]
  16. Nathan Cole, Heidi Newberg, Malik Magdon-Ismail, Travis Desell, Kristopher Dawsey, Warren Hayashi, Jonathan Purnell, Boleslaw Szymanski, Carlos A. Varela, Benjamin Willett, and James Wisniewski. Maximum Likelihood Fitting of Tidal Streams with Application to the Sagittarius Dwarf Tidal Tails. Astrophysical Journal. Volume 683, pages 750-766. 2008. [pdf]
  17. Travis Desell, Kaoutar El Maghraoui, and Carlos A. Varela. Malleable Applications for Scalable High Performance Computing. Cluster Computing. pages 323-337. June 2007. [pdf]
  18. Kaoutar El Maghraoui, Travis Desell, Boleslaw K. Szymanski, and Carlos A. Varela. The Internet Operating System: Middleware for Adaptive Distributed Computing. The International Journal of High Performance Computing Applications (IJHPCA): Special Issue on Scheduling Techniques for Large-Scale Distributed Platforms. Volume 20, Issue 4, pages 467-480. 2006. [pdf]


Conference and Workshop Proceedings

  1. Alex Ororbia, AbdElRahman ElSaid, and Travis Desell. Investigating Recurrent Neural Network Memory Structures using Neuro-Evolution. The Genetic and Evolutionary Computation Conference (GECCO 2019). Prague, Czech Republic. July 8-12, 2019. [pdf]
  2. AbdElRahman ElSaid, Steven Benson, Shuchita Patwardhan, David Stadem and Travis Desell. Evolving Recurrent Neural Networks for Time Series Data Prediction of Coal Plant Parameters. The 22nd International Conference on the Applications of Evolutionary Computation (EvoStar: EvoApps 2019). Leipzig, Germany. April 24-26, 2019. [pdf]
  3. AbdElRahman ElSaid, Travis Desell and Daniel Krutz. Is Adaptivity a Core Property of Intelligent Systems? It Depends. The 2019 IEEE/ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). Montreal, Canada. May 25-26, 2019. [pdf]
  4. Kelton Karboviak, Sophine Clachar, Travis Desell, Mark Dusenbury, Wyatt Hedrick, James Higgins, John Walberg, and Brandon Wild. Classifying Aircraft Approach Type in the National General Aviation Flight Information Database. The 2018 International Conference on Computational Science (ICCS 2018). Wuxi, China. June 11th-13th, 2018. [pdf]
  5. Connor Bowley, Marshall Mattingly, Andrew Barnas, Susan Ellis-Felege and Travis Desell. Detecting Wildlife in Unmanned Aerial Systems Imagery using Convolutional Neural Networks Trained with an Automated Feedback Loop. The 2018 International Conference on Computational Science (ICCS 2018). Wuxi, China. June 11th-13th 2018. [pdf]
  6. AbdElRahman ElSaid, Fatima El Jamiy, James Higgins, Brandon Wild and Travis Desell . Using Ant Colony Optimization to Optimize Long Short-Term Memory Recurrent Neural Networks. The 2018 Genetic and Evolutionary Computation Conference (GECCO 2018). Kyoto, Japan. July 15th-19th 2018. [pdf]
  7. Travis Desell. Accelerating the Evolution of Convolutional Neural Networks with Node-Level Mutations and Epigenetic Weight Initialization. The 2018 Genetic and Evolutionary Computation Conference (GECCO 2018) - Evolutionary Machine Learning Poster Session. Kyoto, Japan. July 15th-19th 2018. [pdf]
  8. Travis Desell. Developing a Volunteer Computing Project to Evolve Convolutional Neural Networks and Their Hyperparameters. The 13th IEEE International Conference on eScience (eScience 2017). Auckland, New Zealand. October 24-27 2017. [pdf]
  9. Connor Bowley, Marshall Mattingly III, Andrew Barnas, Susan Ellis-Felege and Travis Desell. Toward Using Citizen Scientists to Drive Automated Ecological Object Detection in Aerial Imagery. The 13th IEEE International Conference on eScience (eScience 2017). Auckland, New Zealand. October 24-27 2017. [pdf]
  10. Travis Desell. Large Scale Evolution of Convolutional Neural Networks Using Volunteer Computing. The 2017 Genetic and Evolutionary Computation Conference (GECCO) - Evolutionary Machine Learning Poster Session. Berlin, Germany. July 15th-19th 2017. [pdf]
  11. AbdElRahman ElSaid, Fatima ElJamiy, James Higgins, Brandon Wild, Travis Desell. Optimizing LSTM Recurrent Neural Networks Using Ant Colony Optimization to Predict Aircraft Engine Vibration. The 2017 Genetic and Evolutionary Computation Conference (GECCO) - Late Breaking Abstracts. Berlin, Germany. July 15th-19th 2017. [pdf]
  12. Marshall Mattingly III, Andrew Barnas, Susan Ellis-Felege, Robert Newman, David Iles and Travis Desell. Developing a Citizen Science Web Portal for Manual and Automated Ecological Image Detection. The IEEE 12th International Conference on eScience (eScience 2016). Baltimore, MD, USA. October 23-27, 2016. Best of Conference Award. [pdf]
  13. Connor Bowley, Alicia Andes, Susan Ellis-Felege and Travis Desell. Detecting Wildlife in Uncontrolled Outdoor Video using Convolutional Neural Networks. The IEEE 12th International Conference on eScience (eScience 2016). Baltimore, MD, USA. October 23-27, 2016. [pdf]
  14. AbdElRahman ElSaid, Brandon Wild, James Higgins and Travis Desell. Using LSTM Recurrent Neural Networks to Predict Excess Vibration Events in Aircraft Engines. The IEEE 12th International Conference on eScience (eScience 2016). Baltimore, MD, USA. October 23-27, 2016. [pdf]
  15. David Apostal, Sara Faraji Jalal Apostal, Ronald Marsh and Travis Desell. Towards Modeling a Complex Geological Simulation. The 2016 Spring Simulation Multi-Conference (SpringSim 2016). Pasadena, California, USA. April 3-6, 2016. [pdf]
  16. Travis Desell and Carlos A. Varela. Performance and Scalability Analysis of Actor Message Passing and Migration in SALSA Lite. The 5th International Workshop on Programming based on Actors, Agents, and Decentralized Control (AGERE!), held in conjunction with ACM SIGPLAN conference on Systems, Programming, Languages and Applications: Software for Humanity (SPLASH). Pittsburgh, Pennslyvania, USA. October 26th, 2015. [pdf]
  17. Kyle Goehner, Rebecca Eckroad, Leila Mohsenian, Paul Burr, Nicholas Caswell, Alicia Andes, Susan Ellis-Felege, and Travis Desell. A Comparison of Background Subtraction Algorithms for Detecting Avian Nesting Events in Uncontrolled Outdoor Video. The 11th IEEE International Conference on eScience (eScience 2015). Munich, Germany. August 31 - September 4, 2015. [Data Release and Supplementary Material]. [pdf]
  18. Kris Zarns, Archana Dhasarathy, Sergei Nechaev and Travis Desell. Searching the Human Genome for Snail and Slug With DNA@Home. The 11th IEEE International Conference on eScience (eScience 2015). Munich, Germany. August 31 - September 4, 2015. [pdf]
  19. Thomas O'Neil and Travis Desell. Empirical Support for the High-Density Subset Sum Decision Threshold. In the 14th IEEE Canadian Workshop on Information Theory (CWIT'15). St. John's, Newfoundland, Canada. July 6-9, 2015. (Copyright IEEE 2015). [pdf]
  20. Travis Desell, Kyle Goehner, Alicia Andes, Rebecca Eckroad, and Susan Ellis-Felege. On the Effectiveness of Crowd Sourcing Avian Nesting Video Analysis at Wildlife@Home. In the 15th International Conference on Computational Science. Reykjavík, Iceland. June 1-3, 2015. [pdf]
  21. Travis Desell, Sophine Clachar, James Higgins and Brandon Wild. Evolving Deep Recurrent Neural Networks Using Ant Colony Optimization. In the 15th European Conference on Evolutionary Computation in Combinatorial Optimisation (Evo* 2015: EvoCOP). Copenhagen, Denmark. April 8-10, 2015. [Data Release and Supplementary Material].. [pdf]
  22. Travis Desell, Sophine Clachar, James Higgins and Brandon Wild. Evolving Neural Network Weights for Time-Series Prediction of General Aviation Flight Data. In the 13th International Conference on Parallel Problem Solving from Nature (PPSN 2014). Ljubljana, Slovenia. September 13-17, 2014. [Data Release and Supplementary Material]. [pdf]
  23. David Apostal, Kyle Foerster, Travis Desell and Will Gosnold. Performance Improvements for a Large-Scale Geological Simulation. In the 14th International Conference on Computational Science (ICCS 2014). Cairns, Australia. June 10-12, 2014.
  24. Travis Desell, Robert Bergman, Kyle Goehner, Ronald Marsh, Rebecca VanderClute, and Susan Ellis-Felege. Wildlife@Home: Combining Crowd Sourcing and Volunteer Computing to Analyze Avian Nesting Video. In the 2013 IEEE 9th International Conference on e-Science. Beijing, China. October 23-25, 2013. [pdf]
  25. Travis Desell. Using Actors and the SALSA Programming Language to Introduce Concurrency in Computer Science II. In the Third NSF/TCPP Workshop on Parallel and Distributed Computing Education (EduPar-13), held in conjunction with the 27th IEEE International Parallel & Distributed Processing Symposium. Boston, Massachussets. May 20, 2013. [pdf]
  26. David Apostal, Kyle Foerster, Amrita Chatterjee and Travis Desell. Password Recovery Using MPI and CUDA. In the 19th Annual International Conference on High Performance Computing. Pune, India. December 18-21, 2012. [pdf]
  27. Travis Desell, Malik Magdon-Ismail, Heidi Newberg, Lee Newberg, Boleslaw K. Szymanski, and Carlos A. Varela. A Robust Asynchronous Newton Method for Massive Scale Computing Systems. In the 2011 IEEE International Conference on Computational Intelligence and Software Engineering (CiSE 2011). Wuhan, China. December 9-11, 2011. [pdf]
  28. Travis Desell, Lee A. Newberg, Malik Magdon-Ismail, Boleslaw K. Szymanski and William Thompson. Finding Protein Binding Sites Using Volunteer Computing Grids. In the 2011 2nd International Congress on Computer Applications and Computational Science (CACS 2011). Bali, Indonesia. November 15-17, 2011. [pdf]
  29. Travis Desell, Benjamin A. Willet, Matthew Arsenault, Heidi Newberg, Malik Magdon-Ismail, Boleslaw Szymanski and Carlos A. Varela. Evolving N-Body Simulations to Determine the Origin and Structure of the Milky Way Galaxy's Halo using Volunteer Computing. In the Proceedings of the IPDPS'11 Fifth Workshop on Desktop Grids and Volunteer Computing Systems (PCGrid 2011). Anchorage, Alaska, USA. May 20, 2011. [pdf]
  30. Travis Desell, David P. Anderson, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski and Carlos A. Varela. An Analysis of Massively Distributed Evolutionary Algorithms. In the Proceedings of the 2010 IEEE Congress on Evolutionary Computation (IEEE CEC 2010). pages 1-8. Barcelona, Spain. July 2010. [pdf]
  31. Travis Desell, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos A. Varela, Heidi Newberg and David P. Anderson. Validating Evolutionary Algorithms on Volunteer Computing Grids. In the Proceedings of the 10th IFIP International Conference on Distributed Applications and Interoperable Systems (DAIS 2010). pages 29-41. Amsterdam, Netherlands. June 2010. [pdf]
  32. Travis Desell, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos Varela, Heidi Newberg and Nathan Cole. Robust Asynchronous Optimization for Volunteer Computing Grids. In the Proceedings of the 5th IEEE International Conference on e-Science (eScience2009). pages 263-270. Oxford, UK. December 2009. [pdf]
  33. Nathan Colen, Heidi Newberg, Malik Magdon-Ismail, Travis Desell, Kristopher Dawsey, Warren Hayashi, Xinyang Fred Liu, Jonathan Purnell, Boleslaw Szymanski, Carlos Varela, Benjamin Willett and James Wisniewski. A Study of the Sagittarius Tidal Stream Using Maximum Likelihood. In the Proceedings of the 18th Annual Conference on Astronomical Data Analysis Software and Systems. Quebec City, Quebec, Canada. November 2009.
  34. Travis Desell, Anthony Waters, Malik Magdon-Ismail, Boleslaw Szymanski, Carlos Varela, Matthew Newby, Heidi Newberg, Andreas Przystawik and Dave Anderson. Accelerating the MilkyWay@Home volunteer computing project with GPUs. In the 8th International Conference on Parallel Processing and Applied Mathematics (PPAM 2009). Wroclaw, Poland. September 2009. [pdf]
  35. Nathan Cole, Heidi Newberg, Malik Magdon-Ismail, Travis Desell, Boleslaw Szymanski, Carlos Varela. Tracing the Sagittarius Tidal Stream with Maximum Likelihood. In the Proceedings of the International Conference on Classification and Discovery in Large Astronomical Surveys. pages 216-220. Ringberg Castle, Germany. October 2008.
  36. Travis Desell, Boleslaw Szymanski, and Carlos A. Varela.. An Asynchronous Hybrid Genetic-Simplex Search for Modeling the Milky Way Galaxy using Volunteer Computing. In the Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2008). pages 921-928. Atlanta, Georgia. July 2008. [pdf]
  37. Travis Desell, Boleslaw Szymanski, and Carlos A. Varela. Asynchronous Genetic Search for Scientific Modeling on Large-Scale Heterogeneous Environments. In the Proceedings of the 17th International Heterogeneity in Computing Workshop (HCW/IPDPS'08). IEEE. pages 12. Miami, FL. April 2008. [pdf]
  38. Boleslaw Szymanski, Travis Desell, and Carlos A. Varela. The Effect of Heterogeneity on Asynchronous Panmictic Genetic Search. In the Proceedings of the 7th International Conference on Parallel Processing and Applied Mathematics (PPAM'2007). LNCS. Gdansk, Poland. September 2007. [pdf]
  39. Travis Desell, Nathan Cole, Malik Magdon-Ismail, Heidi Newberg, Boleslaw Szymanski, and Carlos A. Varela. Distributed and Generic Maximum Likelihood Evaluation. In the Proceedings of the 3rd IEEE International Conference on e-Science and Grid Computing (eScience2007). pages 337-344. Bangalore, India. December 2007. Best paper finalist. [pdf]
  40. Kaoutar El Maghraoui, Travis Desell, Boleslaw K. Szymanski, and Carlos A. Varela. Dynamic Malleability in Iterative MPI Applications. In the Proceedings of 7th IEEE International Symposium on Cluster Computing and the Grid (CCGrid 2007). pages 591-598. Rio de Janeiro, Brazil. May 2007. Best paper award nominee. [pdf]
  41. Travis Desell, Kaoutar El Maghraoui, and Carlos A. Varela. Malleable Components for Scalable High Performance Computing. In the Proceedings of the HPDC'15 Workshop on HPC Grid programming Environments and Components (HPC-GECO/CompFrame). IEEE. pages 37-44. Paris, France. June 2006. Best paper award. [pdf]
  42. Travis Desell, Harihar N. Iyer, Abe Stephens, and Carlos A. Varela. OverView: A Framework for Generic Online Visualization of Distributed Systems. In the Proceedings of the European Joint Conferences on Theory and Practice of Software (ETAPS 2004), eclipse Technology eXchange (eTX) Workshop. Barcelona, Spain. March 2004. [pdf]
  43. Travis Desell, Kaoutar El Maghraoui, and Carlos A. Varela. Load Balancing of Autonomous Actors over Dynamic Networks. In the Proceedings of the Hawaii International Conference on System Sciences, HICSS-37 Software Technology Track. pages 1-10. January 2004. [pdf]


Technical Reports

  1. Carlos A. Varela, Gul Agha, Wei-Jen Wang, Travis Desell, Kaoutar El Maghraoui, Jason LaPorte, and Abe Stephens. The SALSA Programming Language: 1.1.2 Release Tutorial. Technical report 07-12. Department of Computer Science, RPI, Troy, NY, USA. February 2007. [pdf]
  2. Kaoutar El Maghraoui, Travis J. Desell, and Carlos A. Varela. Network Sensitive Reconfiguration of Distributed Applications. Technical report 05-03. Department of Computer Science, RPI, Troy, NY USA. 2005. [pdf]
  3. Harihar N. Iyer, Abe Stephens, Travis Desell, and Carlos A. Varela. OverView - Dynamic Visualization of Java-Based Highly Reconfigurable Distributed Systems. Technical report. Worldwide Computing Laboratory, RPI, Troy, NY USA. August 2003. [pdf]


Public Talks

  1. Travis Desell. Investigating Recurrent Neural Network Memory Structures using Neuro-Evolution. The 2019 Genetic and Evolutionary Computation Conference (GECCO 2019).. Prague, Czech Republic. July 15, 2019. [pdf]
  2. Travis Desell. Evolving Recurrent Neural Networks for Time Series Data Prediction of Coal Plant Parameters . The 22nd International Conference on the Applications of Evolutionary Computation (EvoStar: EvoApps 2019). Leipzig, Germany. April 24, 2019. [pdf]
  3. Travis Desell. Investigating Recurrent Neural Network Memory Structures using Neuro-Evolution. RIT CHAI AI Seminar and RIT GCCIS PhD Research Colloquium in Computing and Information Sciences. Rochester Institute of Technology, Rochester, NY. February 9 and February 11, 2019. [pdf]
  4. Travis Desell. Wildlife@Home. South Big Data Hub VITAL Data Series - Video Data Analysis. Online - Hosted by Georgia Tech. October 27, 2015. [pdf]
  5. Travis Desell. Lightning Talk - Digital Agriculture - Unmanned Aircraft Systems, Plant Sciences and Education. The 12th IEEE International Conference on eScience (eScience 2015). Baltimore, Maryland. October 25, 2015. [pdf]
  6. Travis Desell. Using LSTM Recurrent Neural Networks to Predict Excess Vibration Events in Aircraft Engines. The 12th IEEE International Conference on eScience (eScience 2015). Baltimore, Maryland. October 25, 2015. [pdf]
  7. Travis Desell. Developing a Citizen Science Web Portal for Manual and Automated Ecological Image Detection. The 12th IEEE International Conference on eScience (eScience 2015). Baltimore, Maryland. October 25, 2015. [pdf]
  8. Travis Desell. A Comparison of Background Subtraction Algorithms for Detecting Avian Nesting Events in Uncontrolled Outdoor Video. The 11th IEEE International Conference on eScience (eScience 2015). Munich, Germany. September 1, 2015. [pdf]
  9. Travis Desell. On the Effectiveness of Crowd Sourcing Avian Nesting Video Analysis at Wildlife@Home . In the 15th International Conference on Computational Science. Reykjavik, Iceland. June 3, 2015. [pdf]
  10. Travis Desell. Evolving Deep Recurrent Neural Networks Using Ant Colony Optimization. The 15th European Conference on Evolutionary Computation in Combinatorial Optimization. Copenhagen, Denmark. April 9, 2015. [pdf]
  11. Travis Desell. Citizen Science at the University of North Dakota. Biology Department Seminar. Grand Forks, North Dakota. March 6, 2015. [pdf]
  12. Travis Desell. MilkyWay@Home. Arizona State University, Tempe, AZ. November 8, 2013. [html]
  13. Travis Desell. Wildlife@Home: Combining Crowd Sourcing and Volunteer Computing to Analyze Avian Nesting Video. The 9th International Conference on E-Science (e-Science 2013). Beijing, China. October 23, 2013. [html]
  14. Travis Desell. Crowd Sourcing Big Data. Digital Lightning, 'TED' Style Talks hosted by UND's Digital and New Media Working Group. University of North Dakota, Grand Forks, ND. April 22, 2013.
  15. Travis Desell. FOQA in University Flight Operations. Aviation Safety InfoShare. Denver, CO. March 20, 2013.
  16. Travis Desell. DNA@Home: Using Volunteered Computers for Finding Transcription Factor Binding Sites. UND Epigenetics and Epigenomics Symposium. University of North Dakota, Grand Forks, ND. November 15, 2012. [ppt] [keynote]
  17. Travis Desell. Wildlife@Home. The 8th International BOINC Workshop. University of Westminster, London, UK. September 27, 2012. [ppt] [keynote]
  18. Travis Desell. Wildlife@Home. The UND Digital Media Showcase. Fire Hall Theatre, Grand Forks, North Dakota, USA. April 11, 2012. [ppt] [keynote]
  19. Travis Desell. Asynchronous Methods for Scalable and Robust Numerical Optimization. Invited Talk. IBM T.J. Watson Research Center, Yorktown, New York, USA. April 5, 2012. [ppt] [keynote]
  20. Travis Desell. Finding Protein Binding Sites using Volunteer Computing Grids. The 2011 2nd International Congress on Computer Applications and Computational Science (CACS 2011). Bali, Indonesia. November 15-17, 2011. [ppt] [keynote]
  21. Travis Desell. From Analyzing the Tuberculosis Genome to Modeling the Milky Way Galaxy: Using Volunteer Computing for Computational Science. Public Talk. University of North Dakota, Grand Forks, North Dakota, USA. November 2010. [ppt] [keynote]
  22. Travis Desell. MilkyWay@Home and Volunteer Computing at RPI. Invited Talk. RPI Center for Open Source Software (RCOSS), Troy, New York, USA. April 2010. [ppt] [keynote]
  23. Travis Desell. Asynchronous Global Optimization for Massive-Scale Computing. PhD Defense. RPI, Troy, New York, USA. November 2009. [ppt] [keynote]
  24. Travis Desell. Robust Asynchronous Optimization using Volunteer Computing Grids. The 5th Annual Pan-Galactic BOINC Workshop. Barcelona, Spain. October 2009. [ppt] [keynote]
  25. Travis Desell. An Asynchronous Hybrid Genetic-Simplex Search for Modeling the Milky Way Galaxy Using Volunteer Computing. Genetic and Evolutionary Computation Conference (GECCO 2008). Atlanta, Georgia, USA. July 2008.
  26. Travis Desell. Scientific Discovery Through Computationally Intensive Maximum Likelihood Evaluation. NSF Symposium on Cyber-Enabled Discovery and Innovation (NSF-CDI 2007). Troy, New York, USA. September 2007.
  27. Travis Desell. Malleable Components for Scalable High Performance Computing. Workshop on HPC Grid Programming Environments and Components (HPC-GECO/CompFrame). Paris, France. June 2006.
  28. Travis Desell. OverView: A Framework for Generic Online Visualization of Distributed Systems. European Joint Conferences on Theory and Practice of Software (ETAPS 2004), eclipse Technology eXchange (eTX) workshop. Barcelona, Spain. March 2004.


Press

  1. Volunteers Create a 'Web' of Power. June 18, 2012. [UND Discovery]
  2. PCs Around the World Unite To Map the Milky Way. February 10, 2010. [RPI News] [Science Daily]