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Chad Mourning

Chad Mourning
Assistant Professor
Stocker Center 337

Research interests: Computer graphics and data visualization, virtual and augmented reality, simulation and modeling, machine learning for meteorology, cybersecurity

Journal Article, Academic Journal (2)

  • Nykl, S., Mourning, C., Chelberg, D. (2014). Interactive mesostructures with volumetric collisions. 7. IEEE transactions on visualization and computer graphics; 20: 970--982.
  • Young, B., Weckman, G., Rangwala, M., Whiting, H., Paschold, H., Snow, A., Mourning, C. (2011). An investigation of TREPAN utilising a continuous oracle model. 4. International Journal of Data Analysis Techniques and Strategies; 3: 325--352.

Patent (2)

  • Mourning, C. REDUCTION OF SENSOR CAPTURED DATA STREAMED TO AN OPERATOR. 9 ,756 ,280.
  • Mourning, C. Wake turbulence analyzer for real-time visualization, detection, and avoidance. 9,709,698.

Conference Proceeding (28)

  • Mourning, C., Lounsbury, B. A Turing Test for Beatmap Generation. Proceedings of the 2024 IEEE Conference on Games.
  • Dhakal, R., Mourning, C. (2024). Synthetic Cloud Height Prediction Using Stereo Matching And Deep Learning. Proceedings of the 2024 IEEE International Geoscience and Remote Sensing Symposium.
  • Phelps, B., Mourning, C. (2024). Electromagnetic Goggles for NAVAID Antenna Pattern Visualization. Proceedings of the 2024 International Flight Inspection Symposium.
  • Phelps, B., Mourning, C. (2024). A Parallel Approach to Arbitrarily-High Antenna Pattern Visualizations. Proceedings of the 2024 AIAA Regional Student Conferences.
  • Salyer, O., Mourning, C. (2024). Extracting Information from NOTAMs Using Named-Entity Recognition. Proceedings of the 2024 AIAA Regional Student Conferences.
  • Phelps, B., Klinger-Neviska, Z., Mourning, C., Braasch, M. (2024). Quantum in Aviation Security: ADS-B Protection with QKD. 2024 Integrated Communications, Navigation and Surveillance Conference (ICNS).
  • Mourning, C. (2024). Advice for the First Time Hardware CTF Organizer. Proceedings of the 55th ACM Technical Symposium on Computer Science Education; 2.
  • Mourning, C., Wright, D., Murray, J. (2024). Towards a Low Cost Distributed AWOS: Machine Learning for Cost Effective Visibility Estimation. AIAA.
  • Phelps, B., Mourning, C. (2024). Utilizing Parallelism and Multithreading for Iterative Refinement of Antenna Pattern Visualization. AIAA.
  • Wright, D., Mourning, C., Murray, J., Albin, T., Young, C., Krimins, E. (2023). Weather Visibility Sensor Network: Platform Characterization. IEEE.
  • Mourning, C., Chenji, H., Hallman-Thrasher, A., Kaya, S., Abukamail, N., Juedes, D., Karanth , A. (2023). Reflections of Cybersecurity Workshop for K-12 Teachers. ACM SIGCSE.
  • Mourning, C., Juedes, D., Hallman-Thrasher, A., Chenji, H., Kaya, S., Karanth , A. (2022). Reflections of Cybersecurity Workshop for K-12 Teachers and High School Students. New York, NY, USA: Association for Computing Machinery; 1127. https://doi.org/10.1145/3478432.3499094.
  • Mourning, C., Odunaiya, S. (2022). Visualization of the Effects of Multipath on NAVAID Antenna Patterns. 10. https://ifissa.co.za/.
  • Lipec, D., Mourning, C. (2022). A 3D Visualization of Errors in GNSS Constellations. NASA/Ohio Space Grant Consortium; 166.
  • Klinger, Z., Mourning, C. (2022). Lindenmayer System Renderer and Parser. NASA/Ohio Space Grant Consortium; 156-158.
  • Mourning, C., Odunaiya, S. (2021). Dynamic Antenna Pattern Visualization for Aviation Safety Incorporating Multipath and Situational Awareness. Springer.
  • Uijt De Haag, Maarten, ., Engelmann, J., Mourning, C. (2019). Performance Evaluation of Predictive Altering of Energy Methods using Flight Simulator Data. 0983.
  • Engelmann, J., Mourning, C., de Haag, M. (2018). Feasibility of Machine Learning Methods for Predictive Alerting of the Energy State for Aircraft. 1--10.
  • Engelmann, J., Mourning, C., de Haag, M. (2017). Comparison of aircraft state prediction methods under sensor uncertainty. 1--10.
  • Mourning, C., Chelberg, D., Vigo, R., Zeigler, D. (2016). Disocclusion mitigation for point cloud imposters. 191--192.
  • Mourning, C., Nykl, S., Chelberg, D. (2014). Disocclusion mitigation for image based point cloud imposters. 861--871.
  • Nykl, S., Mourning, C., Chelberg, D. (2013). Interactive mesostructures. 37--44.
  • Nykl, S., Mourning, C., Nykl, E., Chelberg, D., Skidmore, T. (2012). Jpals visualization tool. 3--10.
  • Nykl, S., Mourning, C., Ghandi, N., Chelberg, D. (2011). A flight tested wake turbulence aware altimeter. 219--228.
  • Mourning, C., Nykl, S., Chelberg, D. (2011). An analysis of impostor based level of detail approximations for LIDAR data. 637--646.
  • Mourning, C., Nykl, S., Xu, H., Chelberg, D., Liu, J. (2010). GPU acceleration of robust point matching. 417--426.
  • Mourning, C., Nykl, S., Chelberg, D., Franklin, T., Liu, C. (2009). An overview of first generation steamie learning objects. 3748--3757.
  • Nykl, S., Mourning, C., Leitch, M., Chelberg, D., Franklin, T., Liu, C. (2008). An overview of the STEAMiE educational game engine. F3B--21.

Abstract (3)

  • Lipec, D., Mourning, C. (2023). A Three-Dimensional Virtual Depiction of the Errors of the Major Global Navigation Satellite System Constellations. 2022-2023 SCHOLAR / FELLOW STUDENT JOURNAL.
  • Mourning, C. (2022). A Three-Dimensional Virtual Depiction of the Errors of the Major Global Navigation Satellite System Constellations. Ohio Space Grant Consortium Student Journal.
  • Klinger, Z., Mourning, C. (2022). Using an Evolutionary Algorithm with L-Systems as the Genome to Generate Possible Martian Tree Structures. Ohio Space Grant Consortium Student Journal.

Other (3)

  • Mourning, C. (2016). Mitigation of disocclusion artifacts.
  • Mourning, C. (2015). Disocclusion Mitigation for Point Cloud Image-Based Level-of-Detail Imposters. Ohio University.
  • Mourning, C. (2008). A highly parallelized approach to silhouette edge detection for shadow volumes in three dimensional triangular meshes. Ohio University.