Matthew Eicholtz, Ph.D.
Associate Professor of Computer Science
In the same way that machine learning enables computers to learn from experience, my goal as a teacher is to enable students to learn from experience, connecting the concepts we discuss in class to real-world applications and developing critical thinking and problem solving skills that will benefit them in their future careers.
Biography
Matthew Eicholtz received his B.S. and M.S. in Mechanical Engineering from the Georgia Institute of Technology in 2009 and 2010, respectively, and completed his Ph.D. in Mechanical Engineering at Carnegie Mellon University in 2015. During his graduate studies, Matthew became interested in artificial intelligence and machine learning, or the ability of computers to accomplish impressive computational feats without being explicitly programmed to do so, and so his focus began to shift toward projects at the intersection of computer science and engineering. Matthew is a strong advocate for the interdisciplinary role computer science must play in solving the technological challenges of the 21st century.
From 2015 to 2018, Matthew was a postdoctoral research associate at Oak Ridge National Laboratory in the Imaging, Signals, and Machine Learning group. Now a faculty member at ³Ô¹ÏÍø, his teaching and research interests include introductory programming (especially for non-majors), deep learning, computer vision, and genetic algorithms for image-based applications in education, robotics, neurobiology, biometrics, and engineering.
In his free time, Matthew enjoys playing board games, watching sports, running, and eating at Chick-fil-A.Education
- Ph.D., Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, 2015
- M.S., Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 2010
- B.S., Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 2009
Publications
B. Jafek, J. Hendershott, M. Eicholtz, C. Johnson, R. Ferrell, J. Baba, P. Bingham, D. Bolme, and H. Santos-Villalobos, “Factor analysis in face detection: gender, occlusion, eyewear, brightness, contrast, and focus measure,” to appear in Proc. SPIE DS134, Disruptive Technologies in Information Sciences, Orlando, FL, Apr. 17-18, 2018.M. Eicholtz, D. Rose, and D. Solecki, D., “How deep is deep enough? Deep convolutional neural networks for medical image analysis,” presented at 5th Annu. Oak Ridge Postgraduate Association Research Symposium, Oak Ridge, TN, Aug. 18, 2017.
M. Eicholtz, D. Rose, R. Kerekes, T.-Y. Eom, and D. Solecki, “Image processing and machine learning techniques for neurobiological applications,” presented at 4th Annu. Oak Ridge Postgraduate Association Research Symposium, Oak Ridge, TN, Aug. 8, 2016.
M. Eicholtz and L. B. Kara, “Recognizing planar kinematic mechanisms from a single image using evolutionary computation,” presented at Bennett Graduate Student Symposium, Pittsburgh, PA, Apr. 25, 2014. [BEST POSTER AWARD]
M. R. Eicholtz and S. H. Collins, “Two-dimensional parameter study to characterize performance of ankle-foot orthosis joint impedance control,” in Proc. 36th Annu. Meeting American Society of Biomechanics, Gainesville, FL, Aug. 15-18, 2012.
M. R. Eicholtz and S. H. Collins, “Design of an ankle-foot orthosis to reduce metabolic cost of walking,” in 6th Annu. Meeting Dynamic Walking, Jena, Germany, Jul. 18-21, 2011, pp. 80-81.
M. R. Eicholtz, S. Sprigle, A. Ferri, J. J. Caspall, P. V. Dao, and S. Wang, “iMachine: measuring manual wheelchair mass properties,” presented at Georgia Tech Research and Innovation Conf. (GTRIC ’10), Atlanta, GA, Feb. 8, 2010.
P. V. Dao, S. Sprigle, J. J. Caspall, A. Ferri, M. R. Eicholtz, and S. Wang, “Anatomical Model Propulsion System: measuring manual wheelchair efficiency,” presented at Georgia Tech Research and Innovation Conf. (GTRIC ’10), Atlanta, GA, Feb. 8, 2010.
S. S. Sprigle and M. R. Eicholtz, “Temperature and relative humidity at the buttock-wheelchair cushion interface,” presented at Biomedical Engineering Society Annual Meeting (BMES 2009), Pittsburgh, PA, Oct. 7-10, 2009.
P. V. Dao, S. Sprigle, J. J. Caspall, A. Ferri, M. R. Eicholtz, and S. Wang, “Anatomical Model Propulsion System: measuring manual wheelchair efficiency,” presented at Biomedical Engineering Society Annual Meeting (BMES 2009), Pittsburgh, PA, Oct. 7-10, 2009.
M. R. Eicholtz and S. Sprigle, “Analysis of temperature and relative humidity variation in wheelchair cushion monitoring tests,” presented at 4th Annu. Undergraduate Research Spring Symposium, Atlanta, GA, Apr. 1, 2009.