Bio
Dr. Chad A. Mello is currently serving as Assistant Professor in Computer & Cyber Sciences at the United States Air Force Academy. He is helping to establish modern standards to enhance higher education for applied computer science, both within and outside the military. He created and currently directs CS 472 Autonomous Systems Integration, an advanced applied machine learning course that blends autonomous systems with machine learning, where cadets learn how to merge ML with autonomous drones and ground vehicles to create applied solutions to real-world problems.
Education
2020 Ph.D. in Engineering with a concentration in Computer Science, University of Colorado, Colorado Springs, Colorado
- Dissertation: Towards the Amelioration of Classification Models for Evoked Potentials in Brain‑Computer Interface
2014 M.S. in Computer Science, University of Colorado, Colorado Springs, Colorado
- Thesis: Machine Learning and Training System for Epileptiform Oscillations in Electroencephalograms
2009 B.S. in Computer Science, College of Santa Fe, Albuquerque, New Mexico
Publications
Advancing Geosynchronous Satellite Classification Utilizing Spectral Data via Fine-Tuned Pretrained Deep Learning Models. In AMOS Conference, Mello, C., Camacho, L., Eberhardt, D, Mendoza, M., September 2024.
The Just-In-Time Adaptive Artificial Augmentation Capstone Project, Las Vegas, USA – 19th Int. Conf. on Frontiers in Education: CS & CE, C. Mello, T. Weingart, July 24-27, 2023
A Hasty Grid S&R Prototype Using Autonomous UTM and AI-Based Mission Coordination, Virtual Workshop – 16th Int. Workshop on Wireless Sensing and Actuating Robotic Networks (WISARN 2023), IEEE INFOCOM 2023, L. Watkins, D. Hamilton, C. Mello, T. Young, S. Zanlongo, B. Kobzik-Juul, and R. Sleight, May 20, 2023
The Multipurpose Autonomous Agent Project: Experiential Learning for Engineering Assistive AI, Prague, Czech Republic – 15th Int. Conf. on Computer Supported Education (CSED), C. Mello, T. Weingart, J. Maher *Best Paper Award*, April 21-23, 2023
CAST: Conditional Attribute Subsampling Toolkit for Fine-grained Evaluation, Waikoloa, Hawaii – IEEE/CVF Winter Conf. on Applications of Computer Vision (WACV), W. Robbins, S. Zhou, A. Bhatta, C. Mello, V. Albiero, K. W. Bowyer, T. E. Boult, January 4-6, 2023
Cross-Subject Deep Transfer Models for Evoked Potentials in Brain-Computer Interface, Montréal Québec – 26th Int. Conf. on Pattern Recognition (ICPR), C. Mello, T. Weingart, E. Rudd, August 21-25, 2022
An Approach to Teaching Applied Machine Learning with Autonomous Systems Integration, Online (Due to COVID) – 14th Int. Conf. on Computer Supported Education (CSEDU), C. Mello, A. De Freitas, T. Weingart, April 22-24, 2022
Towards the Amelioration of Classification Models for Evoked Potentials in Brain-Computer Interface, Colorado Springs, Colorado – PhD Dissertation, University of Colorado, C. Mello, December 2020
Rough Sets: Visually Discerning Neurological Functionality During Thought Processes, St. Raphael, Limassol – 24th Int. Symposium on Methodologies for Intelligent Systems (ISMIS '18), R. Lewis, C. Mello, Y. Zhuang, M. K. -C. Yeh, Y. Yan, D. Gopstein, Oct. 21-29, 2018
Classifying & Localizing Epileptic Brain States Using Structural Features of Neuronal Sugihara Causation Networks, U of Mich, Ann Arbor, Michigan – Advanced Computational Neuroscience Network (ACNN) Midwest Workshop on Big Neuroscience Data, Tools, Protocols & Services, K. Kamalaldin, R. Lewis, C. Mello, D. R. Cserpan, S. Zoltan, P. Erdi, Z. Borhegyi, Sep. 20-21, 2016
Machine Intelligence: The Neuroscience of Chordal Semantics & its Association with Emotion Constructs and Social Demographics, Lyon, France – 22nd Int. Symposium on Methodologies for Intelligent Systems, R. Lewis, M. Bihn, C. Mello, Oct. 21-23, 2015
Semi-Autonomous Neuroclustering: Supervised Learning for the Neurosurgery ICU Using Single-Layer Perceptron Classifiers, Warsaw, Poland – Int. Conf. on Brain Informatics and Health (BIH), C. A. Mello, R. Lewis, August 11-14, 2014
Domain Adaptation for Pathologic Oscillations, Halifax, NS, Canada – Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 14th Int. Conf., R. Lewis, C. A. Mello, J. Ellenberger, A. M. White, Oct. 11-14, 2013
Autonomous Neuroclustering of Pathologic Oscillations Using Discretized Centroids, New York City, USA – 8th Int. Conf. on Mass Data Analysis of Images and Signals in Medicine, R. Lewis, C. A. Mello, A. Brooks-Kayal, J. Carlsen, H. Grabenstatter, A. M. White, July 13, 2013
Semi-Autonomous Neuroclustering: Using Centroidal Displacement Analysis, New York City, USA – 9th Int. Conf. on Machine Learning & Data Mining (MLDM), R. Lewis, C. A. Mello, A. Brooks-Kayal, J. Carlsen, H. Grabenstatter, A. M. White, July 13-16, 2013
Identification of Seizures in Prolonged Video-EEG Recordings, San Diego, CA – 66th American Epilepsy Society Annual Meeting, J. Carlsen, H. Grabenstatter, R. Lewis, C. A. Mello, A. Brooks-Kayal, A. M. White, Dec. 4, 2012
Tracking Epileptogenesis Progressions with Layered Fuzzy K-Means and K-Medoid Clustering, Omaha, Nebraska – Proceedings of the Int. Conf. on Computational Science (ICCS), R. Lewis, C. A. Mello, A. M. White, June 4-6, 2012