Also see my Google Scholar profile and

Z. Carmichael, T. Redgrave, D. Gonzalez, W. J. Scheirer, "This Probably Looks Exactly Like That: An Invertible Prototypical Network," Proceedings of the European Conference on Computer Vision, Milan, Italy, 2024.
arXiv

Z. Carmichael, "Explainable AI for High-Stakes Decision-Making," Ph.D. Dissertation, Department of Computer Science and Engineering, University of Notre Dame, 2024.
Curate ND

^†Z. Carmichael, S. Lohit, A. Cheerian, M. Jones, W. J. Scheirer, "Pixel‐Grounded Prototypical Part Networks," Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, Waikoloa, Hawaii, 2024.
WACV

^†S. Sarkar, A. Ramesh Babu, S. Mousavi, Z. Carmichael, V. Gundecha, S. Ghorbanpour, R. Luna Gutierrez, A. Guillen, A. Naug, "Benchmark Generation Framework with Custom Distortions for Image Classifier Robustness," Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, Waikoloa, Hawaii, 2024.
WACV

^†§‡Z. Carmichael, W. J. Scheirer, "Unfooling Perturbation-Based Post Hoc Explainers," Proceedings of the AAAI Conference on Artificial Intelligence, Washington D.C., 2023.
AAAI

^†§‡Z. Carmichael, T. Moon, S. A. Jacobs, "Learning Debuggable Models Through Multi-Objective Neural Architecture Search," International Conference on Automated Machine Learning (AutoML) Workshop, 2023.
AutoML

Z. Carmichael, W. J. Scheirer, "How Well Do Feature-Additive Explainers Explain Feature-Additive Predictors?," NeurIPS Workshop XAI in Action: Past, Present, and Future Applications, New Orleans, LA, 2023.
arXiv

S. J. Abraham, K. D. G. Maduranga, J. Kinnison, Z. Carmichael, J. D. Hauenstein, W. J. Scheirer, "HomOpt: A Homotopy‐Based Hyperparameter Optimization Method," Under Review, 2023.
arXiv

^†§‡W. Theisen, D. Gonzalez, Z. Carmichael, T. Weninger, W. J. Scheirer, "Motif Mining: Finding and Summarizing Remixed Image Content," Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, 2023.
WACV

^†‡J. Takeshita, Z. Carmichael, R. Karl, T. Jung, "TERSE: Tiny Encryptions and Really Speedy Execution for Post-Quantum Private Stream Aggregation," Proceedings of the EAI International Conference on Security and Privacy in Communication Networks (SecureComm), Remote, 2022.
SecureComm

^†§N. Soures, D. Chambers, Z. Carmichael, A. Daram, D. P. Shah, K. Clark, L. Potter, D. Kudithipudi, "SIRNet: Understanding Social Distancing Measures with Hybrid Neural Network Model for COVID-19 Infectious Spread," Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) Disease Computational Modeling Workshop, Remote, 2020.
IJCAI

^‡—, —, Proceedings of the International Conference on Machine Learning (ICML) Machine Learning for Global Health Workshop, Remote, 2020.
Poster

^†§Z. Carmichael, H. F. Langroudi, C. Khazanov, J. Lillie, J. L. Gustafson, D. Kudithipudi, "Deep Positron: A Deep Neural Network Using Posit Number System," Proceedings of the IEEE Conference and Exhibition on Design, Automation and Test in Europe (DATE), Florence, Italy, 2019 [24% acceptance rate].
arXiv

^†§Z. Carmichael, D. Kudithipudi. "Stochastic Tucker-Decomposed Recurrent Neural Networks for Forecasting." In IEEE Global Conference on Signal and Information Processing (GlobalSIP 2019), Ottawa, Canada, 2019.
GlobalSIP

^†§Z. Carmichael, H. F. Langroudi, C. Khazanov, J. Lillie, J. L. Gustafson, D. Kudithipudi, "Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks," Proceedings of the ACM Conference for Next Generation Arithmetic (CoNGA), Singapore, 2019.
arXiv

^†§Z. Carmichael, B. Glasstone, F. Cwitkowitz, K. Alexopoulos, R. Relyea, R. Ptucha, "Autonomous Navigation Using Localization Priors, Sensor Fusion, and Terrain Classification," Proceedings of IS&T International Symposium on Electronic Imaging: Image Processing Algorithms and Systems, San Francisco, CA, 2019.

^†§Z. Carmichael, H. Syed, D. Kudithipudi, "Analysis of Wide and Deep Echo State Networks for Multiscale Spatiotemporal Time Series Forecasting," Proceedings of the ACM Neuro Inspired Computational Elements (NICE) Workshop, Albany, NY, 2019.

^‡Z. Carmichael, H. Syed, S. Burtner, D. Kudithipudi, "Mod-DeepESN: Modular Deep Echo State Network," Annual Conference on Cognitive Computational Neuroscience, Philadelphia, PA, 2018.
arXiv

Z. Carmichael. "Towards Lightweight AI: Leveraging Stochasticity, Quantization, and Tensorization for Forecasting." Master's Thesis, Department of Computer Engineering, Rochester Institute of Technology. 2019.
RIT Scholar Works

^† Proceedings Paper | ^§ Oral Presentation | ^‡ Poster Presentation