Publications

Cecilia O. Alm. 2022. Linguistic data resources for computational emotion sensing and modeling. In Gesine Lenore Schiewer, Jeanette Altarriba, Bee Chin Ng, editors. Language and Emotion: An International Handbook, Vol. 46/1, Handbooks of Linguistics and Communication Science, pages 226-249. Berlin, Boston: De Gruyter Mouton.

Cecilia O. Alm and Reynold Bailey. 2022. Scientific skills, identity, and career aspiration development from early research experiences in computer science. Journal of Computational Science Education, 13(1): 2-16.

Miguel Ballesteros, Yulia Tsvetkov, and Cecilia O. Alm. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorial Abstracts, Seattle, USA. Association for Computational Linguistics 2022, ISBN 978-1-955917-99-5.

Farhad Akhbardeh, Marcos Zampieri, Cecilia O. Alm, and Travis Desell. 2022. Transfer learning methods for domain adaptation in technical logbook datasets. In Proceedings of the 13th Conference on Language Resources and Evaluation, pages 4235-4244, Marseille, France.

Cecilia O. Alm, Reynold Bailey, and Hannah Miller. 2022. Remote early research experiences for undergraduate students in computing. In Proceedings of the SIGCSE Technical Symposium 2022, pages 43-49, Providence, Rhode Island.

Rajesh Titung and Cecilia O. Alm. 2022. Teaching interactively to learn emotions in natural language. In Proceedings of the Second Workshop on Bridging Human--Computer Interaction and Natural Language Processing (at NAACL 2022), pages 40-46.

Camille Mince, Skye Rhomberg, Cecilia O. Alm, Reynold Bailey, and Alex Ororbia. 2022. Multimodal modeling of task-mediated confusion. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop (at NAACL 2022), 188-194.

Akther Al Amin, Saad Hassan, Cecilia O. Alm, and Matt Huenerfauth. 2022. Using BERT embeddings to model word importance in conversational transcripts for Deaf and Hard of Hearing users. In Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion (at ACL 2022), pages 35-40.

Trent Rabe, Anisa Callis, Zhi Zheng, Jamison Heard, Reynold Bailey, and Cecilia O. Alm. 2022. Theory of mind assessment with human-human and human-robot interactions. n: Kurosu, M. (eds) Human-Computer Interaction. Technological Innovation. HCII 2022. Lecture Notes in Computer Science, vol 13303. Springer, Cham. https://doi.org/10.1007/978-3-031-05409-9_41.

Angela Saquinaula, Adriel Juarez, Joe Geigel, Reynold Bailey, and Cecilia O. Alm. 2022. Emotional empathy and facial mimicry of avatar faces. In Proceedings of the IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), pages 770-771, doi: 10.1109/VRW55335.2022.00236.
 

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Cecilia O. Alm, Reynold Bailey, and Hannah Miller. 2022. Remote early research experiences for undergraduate students in computing. In Proceedings of the SIGCSE Technical Symposium 2022, pages43-49, Providence, Rhode Island.

Cecilia O. Alm and Reynold Bailey. 2022. Scientific skills, identity, and career aspiration development from early research experiences in computer science. Journal of Computational Science Education, 13(1): 2-16.

Camille Mince, Skye Rhomberg, Cecilia O. Alm, Reynold Bailey, and Alex Ororbia. 2022. Multimodal modeling of task-mediated confusion. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop (at NAACL 2022), 188-194.

Trent Rabe, Anisa Callis, Zhi Zheng, Jamison Heard, Reynold Bailey, and Cecilia O. Alm. 2022. Theory of mind assessment with human-human and human-robot interactions. n: Kurosu, M. (eds) Human-Computer Interaction. Technological Innovation. HCII 2022. Lecture Notes in Computer Science, vol 13303. Springer, Cham. https://doi.org/10.1007/978-3-031-05409-9_41.

Angela Saquinaula, Adriel Juarez, Joe Geigel, Reynold Bailey, and Cecilia O. Alm. 2022. Emotional empathy and facial mimicry of avatar faces. In Proceedings of the IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), pages 770-771, doi: 10.1109/VRW55335.2022.00236.

Rakshit S. Kothari, Reynold J. Bailey, Christopher Kanan, Jeff B. Pelz, and Gabriel J. Diaz, 2022. EllSeg-Gen, towards Domain Generalization for head-mounted eyetracking. In Proceedings of the ACM on Human-Computer Interaction, 6(ETRA), pp.1-17.

Olivia Greathouse, Anthony Illescas, Nalin Ranjan, Joe Geigel, Reynold Bailey, and Cecilia O. Alm. Quantifying Engagement Levels in Interaction with a Human vs. an Avatar Interlocutor. The Winthrop McNair Research Bulletin, p.9.

Zhizhuo Yang, Gabriel J. Diaz, Brett R. Fajen, Reynold Bailey, and Alexander Ororbia. 2022. A Neural Active Inference Model of Perceptual-Motor Learning. arXiv preprint arXiv:2211.10419.

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Farhad Akhbardeh, Marcos Zampieri, Cecilia O. Alm, and Travis Desell. 2022. Transfer learning methods for domain adaptation in technical logbook datasets. In Proceedings of the 13th Conference on Language Resources and Evaluation, pages 4235-4244, Marseille, France.

Hong Yang and Travis Desell. 2022. A Large-Scale Annotated Multivariate Time Series Aviation Maintenance Dataset from the NGAFID. arXiv preprint arXiv:2210.07317.

Aaron Bergstrom, John Nowatzki, Trevor Witt, Isaac Barnhart, Jordan Krueger, Mark Askelson, Kurt Barnhart, and Travis Desell. 2022. Protecting farm privacy while researching large-scale unmanned aircraft systems platforms for agricultural applications. Agronomy Journal 114(5):2700-2714.

Hitesh Vaidya, Travis Desell, and Alexander G. Ororbia. 2022. Reducing Catastrophic Forgetting in Self Organizing Maps with Internally-Induced Generative Replay (Student Abstract). In Proceedings of the AAAI Conference on Artificial Intelligence 36(11):13069-13070.

Hong Yang, Aidan LaBella, and Travis Desell. 2022, June. Predictive maintenance for general aviation using convolutional transformers. In Proceedings of the AAAI Conference on Artificial Intelligence 36(11):12636-12642.

Deema Alshoaibi, Mohamed Wiem Mkaouer, Ali Ouni, AbdulMutalib Wahaishi, Travis Desell, and Makram Soui. 2022. Search-based Detection of Code Changes Introducing Performance Regression. Swarm and Evolutionary Computation, p.101101.

Aidan P. LaBella, Joshua A. Karns, Farhad Akhbardeh, Travis Desell, Andrew J. Walton, Zechariah Morgan, Brandon Wild, and Mark Dusenbury. 2022. Optimized flight safety event detection in the national general aviation flight information database. In Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing, pp. 1570-1579.

Aizaz Ul Haq, Niranjana Deshpande, AbdElRahman ElSaid, Travis Desell, and Daniel E. Krutz. 2022. Addressing Tactic Volatility in Self-Adaptive Systems Using Evolved Recurrent Neural Networks and Uncertainty Reduction Tactics. arXiv e-prints, pp.arXiv-2204.10308.

Zimeng Lyu and Travis Desell. 2022. ONE-NAS: An Online NeuroEvolution based Neural Architecture Search for Time Series Forecasting. arXiv e-prints, pp.arXiv-2202.

Hong Yang and Travis Desell. 2022. Robust Augmentation for Multivariate Time Series Classification. arXiv e-prints, pp.arXiv-2201.
Michael Kogan, Joshua Karns, and Travis Desell. 2022. Self-adaptation of Neuroevolution Algorithms Using Reinforcement Learning. In Applications of Evolutionary Computation: 25th European Conference, Evo Applications 2022, Held as Part of EvoStar 2022, Madrid, Spain, April 20-22, 2022, Proceedings (Vol. 13224, p. 452). Springer Nature.

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Rakshit S. Kothari, Reynold J. Bailey, Christopher Kanan, Jeff B. Pelz, and Gabriel J. Diaz, 2022. EllSeg-Gen, towards Domain Generalization for head-mounted eyetracking. In Proceedings of the ACM on Human-Computer Interaction, 6(ETRA), pp.1-17.

Zhizhuo Yang, Gabriel J. Diaz, Brett R. Fajen, Reynold Bailey, and Alexander Ororbia. 2022. A Neural Active Inference Model of Perceptual-Motor Learning. arXiv preprint arXiv:2211.10419.

Nathaniel Powell, Xavier Marshall, Gabriel Diaz, Brett Fajen; The visual control of gaze, steering, and obstacle avoidance in experienced quadcopter pilots. Journal of Vision 2022;22(14):4315. doi: https://doi.org/10.1167/jov.22.14.4315.

Zhizhuo Yang, Gabriel J. Diaz, Brett R. Fajen, Reynold Bailey, Alexander Ororbia; An active inference model of anticipation in locomotor interception. Journal of Vision 2022;22(14):4027. doi: https://doi.org/10.1167/jov.22.14.4027.

A. K. Chaudhary, N. Nair, R. J. Bailey, J. B. Pelz, S. S. Talathi and G. J. Diaz, “: From real infrared eye-images to synthetic sequences of gaze behavior,” in IEEE Transactions on Visualization and Computer Graphics, vol. 28, no. 11, pp. 3948-3958, Nov. 2022, doi: 10.1109/TVCG.2022.3203100.

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Prangon Das, Purab Ranjan Sutradhar, Mark Indovina, Sai Manoj Pudukotai Dinakarrao, Amlan Ganguly. “Implementation and Evaluation of Deep Neural Networks in Commercially Available Processing in Memory Hardware,” 2022 IEEE 35th International System-on-Chip Conference (SOCC), 2022, pp. 1-6, doi: 10.1109/SOCC56010.2022.9908126.

Sai Manoj Pudukotai Dinakarrao, Arun Joseph, Amlan Ganguly, Anand Haridass, and Vijay Janappa Reddi. 2022, June. Guest Editors’ Introduction: Special Issue on Benchmarking Machine Learning Systems and Applications, in IEEE Design & Test, vol. 39, no. 3, pp. 5-7. doi: 10.1109/MDAT.2021.3100547.

Amlan Ganguly, Sergi Abadal, Ishan Thakkar, Natalie Enright Jerger, Marc Riedel, Masoud Babaie, Rajeev Balasubramonian, Abu Sebastian, Sudeep Pasricha, and Baris Taskin. 2022, May-June. Interconnects for DNA, Quantum, In-Memory, and Optical Computing: Insights From a Panel Discussion, in IEEE Micro, vol. 42, no. 3, pp. 40-49, 1. doi: 10.1109/MM.2022.3150684.

Abhishek Vashist, Sharan Vidash Vidya Shanmugham, Amlan Ganguly, and Sai Manoj PD. 2022. DQN Based Exit Selection in Multi-Exit Deep Neural Networks for Applications Targeting Situation Awareness, 2022 IEEE International Conference on Consumer Electronics (ICCE), pp. 1-6, doi: 10.1109/ICCE53296.2022.9730182.

Rahul Singh Glia, Sayed Ashraf Mamun, Abhishek Vashist, Amlan Ganguly, Clark Hochgraf, Andres Kwasinski, and Michael E Kuhl .2022. Evaluation of Wireless Connectivity in an Automated Warehouse at 60 GHz,” 2022 IEEE International Conference on Consumer Electronics (ICCE), pp. 1-6. doi: 10.1109/ICCE53296.2022.9730123.

Patents:
Amlan Ganguly, Sai Manoj Pudukotai Dinakarrao, Mark Connolly, Purab Ranjan Sutradhar, Sathwika Bavikadi, and Mark Allen Indovina, Rochester Institute of Technology. 2022. Look-up table containing processor-in-memory cluster for data-intensive applications. U.S. Patent Application 17/717,947.

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S. Singh and J. Heard, “A Human-Aware Decision Making System for Human-Robot Teams,” 2022 17th Annual System of Systems Engineering Conference (SOSE), 2022, pp. 268-273, doi: 10.1109/SOSE55472. 2022.9812641.

D. S. Masanam, G. R. Tsouri and J. Heard, “Non-Contact Human Workload Assessment for Adaptive Intelligent Systems,” 2022 17th Annual System of Systems Engineering Conference (SOSE), 2022, pp. 389-394, doi: 10.1109/SOSE55472.2022.9812669.

L. Nagahanumaiah, S. Singh and J. Heard, “Diagnostic Human Fatigue Classification using Wearable Sensors for Intelligent Systems,” 2022 17th Annual System of Systems Engineering Conference (SOSE), 2022, pp. 424-429, doi: 10.1109/SOSE55472.2022.9812694.

S. Singh and J. Heard, “Human-Aware Reinforcement Learning for Adaptive Human Robot Teaming,” 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2022, pp. 1049-1052. doi:10.1109/HRI53351.2022.9889530.

J. Heard, P. Baskaran, and J.A. Adams. 2022 Sep 13. Predicting task performance for intelligent human-machine interactions. Front Neurorobot, pp. 16:973967. doi: 10.3389/fnbot.2022.973967. PMID:36176571; PMCID: PMC9513063.

T. Rabe, A., Callis, Z. Zheng, J. Heard, R. Bailey, C. Alm. 2022. Theory of Mind Assessment with Human-Human and Human-Robot Interactions. In: Kurosu, M. (eds) Human-Computer Interaction. Technological Innovation. HCII 2022. Lecture Notes in Computer Science, vol 13303. Springer, Cham. https://doi.org/10.1007/978-3-031-05409-9_41.

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Rahul Singh Gulia, Sayed Ashraf Mamun, Abhishek Vashist, Amlan Ganguly, Clark Hochgraf, Andres Kwasinski, and Michael E Kuhl. 2022. Evaluation of Wireless Connectivity in an Automated Warehouse at 60 GHz. 2022 IEEE International Conference on Consumer Electronics (ICCE), 2022, pp. 1-6. doi: 10.1109/ICCE53296.2022.9730123.

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Oliver Alonzo, Sooyeon Lee, Mounica Maddela, Wei Xu, Matt Huenerfauth. 2022. “A Dataset of Word-Complexity Judgements from Deaf and Hard-of-Hearing Adults for Text Simplification.” Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022).

Matt Huenerfauth. 2022. “Human-Computer Interaction and Automatic Text Simplification: Understanding the Perspective of Deaf and Hard of Hearing Users.” Keynote Presentation, Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022), The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022).

Joseph Bochner, Vincent Samar, Emily Prud’hommeaux, and Matt Huenerfauth. 2022. “Phoneme Categorization in Prelingually Deaf Adult Cochlear Implant Users.” Journal of Speech, Language, and Hearing Research, Volume 65, pages 4429–4453, November 2022. https://doi.org/10.1044/2022_JSLHR-22-00038.

Oliver Alonzo, Lisa Elliot, Becca Dingman, Sooyeon Lee, Akhter Al Amin, and Matt Huenerfauth. 2022. “Reading-Assistance Tools Among Deaf and Hard-of-Hearing Computing Professionals in the U.S.: Their Reading Experiences, Interests and Perceptions of Social Accessibility.” ACM Transactions on Accessible Computing, 15, 2, Article 16 (June 2022), 31 pages. https://doi.org/10.1145/3520198.

Saad Hassan, Sooyeon Lee, Dimitris Metaxas, Carol Neidle, and Matt Huenerfauth. 2022. “Understanding ASL Learners’ Preferences for a Sign Language Recording and Automatic Feedback System to Support Self-Study.” In Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ‘22). Association for Computing Machinery, New York, NY, USA, Article 85, 1–5. https://doi.org/10.1145/ 3517428.3550367.

Saad Hassan, Akhter Al Amin, Caluã de Lacerda Pataca, Diego Navarro, Alexis Gordon, Sooyeon Lee, and Matt Huenerfauth. 2022. “Support in the Moment: Benefits and use of video-span selection and search for sign-language video comprehension among ASL learners.” In Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ‘22). Association for Computing Machinery, New York, NY, USA, Article 29, 1–14. https://doi.org/10.1145/3517428.3544883.
Conference Award: Best Paper Nominee, ASSETS 2022. (Top 5% of submissions.)

Saad Hassan, Matthew Seita, Larwan Berke, Yingli Tian, Elaine Gale, Sooyeon Lee, Matt Huenerfauth. 2022. “ASL-Homework-RGBD Dataset: An annotated dataset of 45 fluent and non-fluent signers performing American Sign Language homeworks.” In Proceedings of the LREC2022 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources, at the Language Resources and Evaluation Conference (LREC 2022).

Zhaoyang Xia, Yuxiao Chen, Qilong Zhangli, Matt Huenerfauth, Carol Neidle, Dimitris Metaxas. 2022. “Sign Language Video Anonymization.” In Proceedings of the LREC2022 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources, at the Language Resources and Evaluation Conference (LREC 2022).

Akhter Al Amin, Saad Hassan, Cecilia Alm, Matt Huenerfauth. 2022. “Using BERT Embeddings to Model Word Importance in Conversational Transcripts for Deaf and Hard of Hearing Users.” The Second Workshop on Language Technology for Equality, Diversity and Inclusion (LT-EDI), at the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022), Association for Computational Linguistics. Pages 35-40. https://aclanthology.org/2022.ltedi-1.5 DOI: 10.18653/v1/2022.ltedi-1.5.

Akhter Al Amin, Saad Hassan, Sooyeon Lee, and Matt Huenerfauth. 2022. “Watch It, Don’t Imagine It: Creating a Better Caption-Occlusion Metric by Collecting More Ecologically Valid Judgments from DHH Viewers.” In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI ‘22). Association for Computing Machinery, New York, NY, USA, Article 459, 1–14. https://doi.org/10.1145/3491102.3517681.

Matthew Seita, Sooyeon Lee, Sarah Andrew, Kristen Shinohara, and Matt Huenerfauth. 2022. “Remotely Co-Designing Features for Communication Applications using Automatic Captioning with Deaf and Hearing Pairs.” In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI ‘22). Association for Computing Machinery, New York, NY, USA, Article 460, 1–13. https://doi.org/10.1145/3491102.3501843.

Abraham Glasser, Matthew Watkins, Kira Hart, Sooyeon Lee, and Matt Huenerfauth. 2022. “Analyzing Deaf Abraham Glasser, Matthew Watkins, Kira Hart, Sooyeon Lee, and Matt Huenerfauth. 2022. “Analyzing Deaf and Hard-of-Hearing Users’ Behavior, Usage, and Interaction with a Personal Assistant Device that Understands Sign-Language Input.” In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI ‘22). Association for Computing Machinery, New York, NY, USA, Article 306, 1–12. https://doi.org/10.1145/3491102.3501987.

Oliver Alonzo, Jessica Trussell, Matthew Watkins, Sooyeon Lee, and Matt Huenerfauth. 2022. “Methods for Evaluating the Fluency of Automatically Simplified Texts with Deaf and Hard-of-Hearing Adults at Various Literacy Levels.” In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI ‘22). Association for Computing Machinery, New York, NY, USA, Article 267, 1–10. https://doi.org/10.1145/3491102.3517566.

Saad Hassan, Akhter Al Amin, Alexis Gordon, Sooyeon Lee, and Matt Huenerfauth. 2022. “Design and Evaluation of Hybrid Search for American Sign Language to English Dictionaries: Making the Most of Imperfect Sign Recognition.” In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI ‘22). Association for Computing Machinery, New York, NY, USA, Article 195, 1–13. https://doi.org/10.1145/3491102.3501986.

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Hayes, T.L., Nickel, M., Kanan, C., Denoyer, L., Szlam, A. (2022) Can I see an Example? Active Learning the Long Tail of Attributes and Relations. In: British Machine Vision Conference (BMVC).

Rangnekar, A., Kanan, C., Hoffman, M. (2022) Semantic Segmentation with Active Semi-Supervised Representation Learning. In: British Machine Vision Conference (BMVC). https://bmvc2022.mpi-inf.mpg.de/0229.pdf.

Sur., I., Daniels, Z., Rahman, A., Faber, K., Gallardo, J., Hayes, H., Taylor, C., Gurbuz, M., Smith, J., Joshi, S., Japkowicz, N., Baron, M., Kira, Z., Kanan, C., Corizzo, R., Divakaran, A., Piacentino, M., Hostetler, J., Raghavan, A. (2022) System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games. In: International Conference on AI-ML Systems (AIMLSys).

Shrestha, R., Kafle, K., Kanan, C. (2022) OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses. In: European Conference on Computer Vision (ECCV). [Oral; 2.7% oral accept rate]

Hayes, T.L., Kanan, C. (2022) Online Continual Learning for Embedded Devices. In: Conference on Lifelong Learning Agents (CoLLAs).

Acharya, M., Roy, A., Koneripalli, K., Jha, S., Kanan, C., Divakaran, A. (2022) Detecting out-of-context objects using contextual cues. International Joint Conference on Artificial Intelligence (IJCAI). [15% accept rate]

Mahmood, U., Bates, D., Erdi, Y., Mannelli, L., Corrias, G., Kanan, C. (2022) Deep learning and domain specific knowledge to segment the liver from synthetic dual energy CT iodine scans. Diagnostics. doi:10.3390/diagnostics12030672.

Kothari, R.S., Bailey, R.J., Kanan, C., Pelz, J.B., Diaz, G.J. (2022) EllSeg-Gen, towards Domain Generalization for Head-Mounted Eyetracking. In: ACM Symposium on Eye Tracking Research and Applications (ETRA).

Shrestha, R., Kafle, K., Kanan, C. (2022) An Investigation of Critical Issues in Bias Mitigation Techniques. In: IEEE Winter Applications of Computer Vision Conference (WACV). [35% accept rate]

Zhang, Y., Hayes, T.L., Kanan, C. (2022) Disentangling Transfer and Interference in Multi-Domain Learning. In: AAAI Workshop on Practical Deep Learning in the Wild (PracticalDL).
 

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Rahul Singh Gulia, Sayed Ashraf Mamun, Abhishek Vashist, Amlan Ganguly, Clark Hochgraf, Andres Kwasinski, Michael E Kuhl. “Evaluation of Wireless Connectivity in an Automated Warehouse at 60 GHz,” 2022 IEEE International Conference on Consumer Electronics (ICCE), 2022, pp. 1-6, doi: 10.1109/ICCE53296.2022.9730123.

Ankita Tondwalkar and Andres Kwasinski. 2022. Deep Reinforcement Learning for Distributed and Uncoordinated Cognitive Radios Resource Allocation. arXiv preprint arXiv:2205.13944.

John Jenco, Omar Abdul Latif, Andres Kwasinski, and Muhieddin Amer. 2022. Network Slicing for Wireless Networks Operating in a Shared Spectrum Environment. 2022 IEEE Wireless Communications and Networking Conference (WCNC), pp. 2435-2440.

Andres Kwasinski and Alexis Kwasinski. 2022. Increasing Physical Resiliency of Wireless Networks through Virtual Energy Transfer. 2022 IEEE Wireless Communications and Networking Conference (WCNC), pp. 2541-2546. doi: 10.1109/WCNC51071.2022.9771622.

Rahul Singh Gulia, Sayed Ashraf Mamun, Abhishek Vashist, Amlan Ganguly, Clark Hochgraf, Andres Kwasinski, and Michael E Kuhl. 2022. Evaluation of Wireless Connectivity in an Automated Warehouse at 60 GHz. 2022 IEEE International Conference on Consumer Electronics (ICCE), pp. 1-6. doi: 10.1109/ICCE53296.2022.9730123.

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Tsung-Han Lee, Nicola Lanatà and Gabriel Kotliar, “Accuracy of ghost-rotationally-invariant slave-boson and dynamical mean field theory as a function of the impurity-model bath size”, Phys. Rev. B 107, L121104 (2023).

Alla Chikina, Gargee Bhattacharyya, Davide Curcio, Charlotte E. Sanders, Marco Bianchi, Nicola Lanatà, Matthew Watson, Cephise Cacho, Martin Bremholm and Philip Hofmann, “One-dimensional electronic states in a natural misfit structure”, Phys. Rev. Materials 6, L092001 (2022).

Nicola Lanatà, “Operatorial formulation of the ghost rotationally-invariant slave-Boson theory”, Phys. Rev. B 105, 045111 (2022).

Alfred J. H. Jones, Ryan Muzzio, Sahar Pakdel, Deepnarayan Biswas, Davide Curcio, Nicola Lanatà, Philip Hofmann, Kathleen M. McCreary, Berend T. Jonker, Kenji Watanabe, Takashi Taniguchi, Simranjeet Singh, Roland J. Koch, Chris Jozwiak, Eli Rotenberg, Aaron Bostwick, Jill A. Miwa, Jyoti Katoch and Søren Ulstrup, “Visualizing band structure hybridization and superlattice effects in twisted MoS2/WS2 heterobilayers”, 2D Mater. 9, 015032 (2022).

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Cheng, Z., Liang, J., Choi, H., Tao, G., Cao, Z., Liu, D. and Zhang, X., 2022. Physical Attack on Monocular Depth Estimation with Optimal Adversarial Patches. ECCV 2022.

Cao, Z., Liu, D. and Chen, Y., 2022. Towards Unbiased Label Distribution Learning for Facial Pose Estimation Using Anisotropic Spherical Gaussian. ECCV 2022.

Yan, L., Ma, S., Wang, Q., Chen, Y., Zhang, X., Savakis, A. and Liu, D., 2022. Video Captioning Using Global-Local Representation. IEEE Transactions on Circuits and Systems for Video Technology.

Yan, L., Wang, Q., Cui, Y., Feng, F., Quan, X., Zhang, X. and Liu, D., 2022. GL-RG: Global-Local Representation Granularity for Video Captioning. IJCAI 2022.

Wang, Q., Fang, Y., Ravula, A., Feng, F., Quan, X. and Liu, D., 2022, April. WebFormer: The Web-page Transformer for Structure Information Extraction. In Proceedings of the ACM Web Conference 2022 (pp. 3124-3133).

Wang, Q., Yang, L., Quan, X., Feng, F., Liu, D., Xu, Z., Wang, S., and Ma, H. Learning to Generate Question by Asking Question: A Primal-Dual Approach with Uncommon Word Generation . December 7-11, 2022. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 46 - 61, 2022 Association for Computational Linguistics.

Wang, W., Liang, J., and Liu, D. 2022 Learning Equivariant , Segmentation with Instance-Unique Querying. arXiv preprint arXiv:2210.00911.

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Xumin Liu, Erik Golen, Rajendra K Raj. 2022, March. Introducing Data Science Topics to Non-Computing Majors. SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2, p. 1201. https://doi.org/10.1145/3478432.3499156.

Xumin Liu, Erik Golen, Rajendra K Raj. 2022, March. DSLP: A Web-based Data Science Learning Platform to Support DS Education for Non-Computing Majors. SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2, p. 1181. https://doi.org/10.1145/3478432.3499255.

Moayad Alshangiti, Weishi Shi, Eduardo Lima, Xumin Liu, Qi Yu. 2022, November. Hierarchical Bayesian multi-kernel learning for integrated classification and summarization of app reviews. Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2022), pp. 558-569.

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K. Ruck, J. Manico, D. Kloosterman, A. Loui, and M. Das, “System and method for predictive curation, production infrastructure,” US Patent No. 11,429,832, Aug. 30, 2022.

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Bao, M., Zhang, S., Ten Pas, C., Dollery, S.J., Bushnell, R.V., Yuqing, F.N.U., Liu, R., Lu, G., Tobin, G.J. and Du, K., 2022. Computer vision enabled funnel adapted sensing tube (FAST) for power-free and pipette-free nucleic acid detection. Lab on a Chip.

Yu, Z., Zhu, L. and Lu, G., 2022. Tightly-coupled Fusion of VINS and Motion Constraint for Autonomous Vehicle. IEEE Transactions on Vehicular Technology.

Lu, Y. and Lu, G., 2022. 3D Modeling Beneath Ground: Plant Root Detection and Reconstruction Based on Ground-Penetrating Radar. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 68-77).

Lu, G., 2022, July. Image-based Localization for Self-driving Vehicles Based on Online Network Adjustment in A Dynamic Scope. In 2022 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.

Wee, L.K., Lu, G., Chai, H.Y., Kai, T.Y. and Ravi, R., 2022. Computer vision for clinical images. Multimed Tools Appl 81, 35981–35982 (2022). https://doi.org/10.1007/s11042-022-13888-8.

Lu, Y. and Lu, G., 2022, July. An Unsupervised Approach for Simultaneous Visual Odometry and Single Image Depth Estimation. In 2022 International Joint Conference on Neural Networks (IJCNN) (pp. 01-08). IEEE.

Xie, Z., Niu, J., Yi, L. and Lu, G., 2022. Regularization and attention feature distillation base on light CNN for hyperspectral face recognition. Multimedia Tools and Applications, 81(14), pp.19151-19167.

Walker, C., Wang, Y., Lu, Y. and Lu, G., 2022, May. Inferring Camera Intrinsics Based on Surfaces of Revolution: A Single Image Geometric Network Approach for Camera Calibration. In ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 2654-2658). IEEE.

Wang, H., Zhang, T., Lu, G. and Liang, J., Hdr Image Reconstruction from Ldr Image Pair with Up/Down Exposure. Down Exposure.

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C. Merkel, “Enhancing Adversarial Attacks on Single-Layer NVM Crossbar-Based Neural Networks with Power Consumption Information,” IEEE 35th International System-on-Chip Conference (SOCC), pp. 1-6, 2022.

A. Thangaraju and C. Merkel, “Exploring Adversarial Attacks and Defenses in Deep Learning,” IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), 2022.

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Reem Alsuhaibani, Christian D. Newman, Michael J. Decker, Michael L. Collard, Jonathan I. Maletic, “An
Approach to Automatically Assess Method Names”, 30th International Conference on Program Comprehension,
2022, May 2022, Pages 202–213. https://doi.org/10.1145/3524610.3527780.

Peruma, Anthony and Christian D. Newman. “Understanding Digits in Identifier Names: An Exploratory
Study.” The 1st Intl. Workshop on Natural Language-based Software Engineering, NLBSE ’22, May 8, 2022,
Virtual Event, USA, arXiv:2203.00113v4 [cs.SE] 15 March 2022, to appear

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Ananthanarayana, T., Chaudhary, L. and Nwogu, I., 2022. SignNet: Single Channel Sign Generation using Metric Embedded Learning. arXiv preprint arXiv:2212.02848. Wilkins, N., Johnson, M. and Nwogu, I., 2022, October. Regression with Uncertainty Quantification in Large Scale Complex Data. In 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 827-833). IEEE.

Zee, T., Lakshmana, M. and Nwogu, I., 2022, August. Towards Understanding the Behaviors of Pretrained Compressed Convolutional Models. In 2022 26th International Conference on Pattern Recognition (ICPR) (pp. 3450-3456). IEEE.

Wang, R. and Nwogu, I., 2022. A Probabilistic Model Of Interaction Dynamics for Dyadic Face-to-Face Settings. arXiv preprint arXiv:2207.04566.

Zee, T., Ororbia, A.G., Mali, A. and Nwogu, I., 2022. A Robust Backpropagation-Free Framework for Images. arXiv preprint arXiv:2206.01820.

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Rick Lagiewski, Victor Perotti. Customer experiences and situational vulnerability: An exploration of hotel services during a disaster. International Journal of Hospitality Management, Volume 108, 2023, 103360, ISSN 0278-4319. https://doi.org/10.1016/j.ijhm.2022.103360.

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Lintern, G., Motavalli, A., Chua, Z., Rantanen, E.M., Peres, S.C. and Boorman, D., 2022. Rapid Development of a Hospital Checklist in a Time of COVID-19. Ergonomics in Design, 30(4), pp.5-13.

Bragg, T., Rantanen, E.M., Pelletier, J.M., and Rashedi, E. Cognitive Engineering Modeling of Phishing. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66 (1), pp. 2088-2092. doi: 10.1177/1071181322661330.

Kang, R., Rantanen, E.M., and Youngstrom, E.A. Machine Learning in Healthcare: Two Case Studies. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66 (1), pp. 774-778.

Kulomäki, J., Oksama, L., Rantanen, E. and Hyönä, J., 2022. Attention control in a demanding dynamic time-sharing environment: An eye-tracking study. Attention, Perception, & Psychophysics, 84(2), pp.352-371.

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Robertson, J., Heiden, J. and Cardona-Rivera, R.E., 2023, October. Evolving interactive narrative worlds. In Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (Vol. 19, No. 1, pp. 126-135).

Sulabh Kumra, Shirin Joshi, and Ferat Sahin. 2022. Learning Multi-step Robotic Manipulation Policies from Visual Observation of Scene and Q-value Predictions of Previous Action. arXiv preprint arXiv:2202.11280.

Celal Savur and Ferat Sahin, 2022, October. The 17th IEEE International Conference on Systems and Systems Engineering [Conference Reports], in IEEE Systems, Man, and Cybernetics Magazine, vol. 8, no. 4, pp. 57-59. doi: 10.1109/MSMC.2022.3205492.

Sulabh Kumra, Shirin Joshi, and Ferat Sahin. 2022. GR-ConvNet v2: A Real-Time Multi-Grasp Detection Network for Robotic Grasping. Sensors (Basel, Switzerland), 22(16), p.6208.

Anthony Ambrose, Celal Savur, and Ferat Sahin. 2022, June. Low Cost Real Time Location Tracking with Ultra-Wideband. In 2022 17th Annual System of Systems Engineering Conference (SOSE), pp. 445-450. IEEE.

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Navya Nagananda, Breton Minnehan, and Andreas Savakis. 2022. Robust Lp-Norm Linear Discriminant Analysis with Proxy Matrix Optimization,” International Conference on Machine Learning (ICML) Workshop on Topology, Algebra, and Geometry in Machine Learning (TAG-ML), pp. 277-286.

Divyansh Gupta, Bruno Artacho, and Andreas Savakis. 2022. HandyPose: Multi-level framework for hand pose estimation. Pattern Recognition, 128, p.108674.

Abu Md Niamul Taufique, Breton Minnehan, and Andreas Savakis. 2022. SiamGauss: Siamese region proposal network with Gaussian head for visual object tracking. Journal of Applied Remote Sensing, 16(3), p.036501.

Naomi Caselli, Corrine Occhino, Bruno Artacho, Andreas Savakis, and Matthew Dye. 2022. Perceptual optimization of language: Evidence from American Sign Language. Cognition, 224, p.105040.

Chowdhury Sadman Jahan, Andreas Savakis, Erik Blasch. 2022. SAR Image Classification with Knowledge Distillation and Class Balancing for Long-Tailed Distributions,” 2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), pp. 1-5, doi: 10.1109/IVMSP54334.2022.9816201.

Erik Blasch, Andreas Savakis, Yufeng Zheng, Genshe Chen, Ivan Kadar, Uttam Majumder, and Ali K Raz. 2022, June. Joint data learning panel summary. In Signal Processing, Sensor/Information Fusion, and Target Recognition XXXI, Vol. 12122, pp. 138-154. SPIE.

Chowdhury Sadman Jahan, Andreas Savakis, and Erik Blasch. 2022, May. Cross-modal knowledge distillation in deep networks for SAR image classification. In Geospatial Informatics XII, Vol. 12099, pp. 20-27. SPIE.

Adisree V Ankolekar, Raaga Madappa, and Andreas Savakis. 2022. Can simpler be better? Review of methods for the detection of GAN-generated imagery. Pattern Recognition and Tracking XXXIII, 12101, pp.123-133.

Liqi Yan, Siqi Ma, Qifan Wang, Yingjie Chen, Xiangyu Zhang, Andreas Savakis, and Dongfang Liu. 2022. Video Captioning Using Global-Local Representation. IEEE Transactions on Circuits and Systems for Video Technology.

Abu Md Niamul Taufique, Chowdhury Sadman Jahan, and Andreas Savakis. 2022. Unsupervised Continual Learning for Gradually Varying Domains. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pp. 3740-3750.

C. S. Jahan, A. Savakis and E. Blasch, “SAR Image Classification with Knowledge Distillation and Class Balancing for Long-Tailed Distributions,” IEEE Image Vision and Multidimensional Signal Processing Workshop, 2022.

 

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Bondy, C., Chen, L., Grover, P,, and Shi, P.: Advancing Ubiquitous Collaboration for Telehealth – A Framework to Evaluate Technology-mediated Collaborative Workflow for Telehealth, Hypertension Exam Workflow Study, J Pharmacol Pharm Res, 5(1): 1–20, 2022. DOI: 10.31038/JPPR.2022513.

Zheng, E., Yu, Q., Li, R., Shi, P., and Haake, A. R.: Dual-Level Adaptive Information Filtering for Interactive Image Segmentation, AISTATS, 2022. P. 6862-6879.

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Xiajun Jiang, Maryam Toloubidokhti, Jake Bergquist, Brian Zenger, Wilson W Good, Rob S MacLeod, and Linwei Wang. 2022. Improving Generalization by Learning Geometry-Dependent and Physics-Based Reconstruction of Image Sequences. IEEE Transactions on Medical Imaging.

Maryam Toloubidokhti, Ryan Missel, Xiajun Jiang, Niels Otani, and Linwei Wang. 2022. Neural State-Space Modeling with Latent Causal-Effect Disentanglement. arXiv preprint arXiv:2209.12387.

Carlos O Lousto, Ryan Missel, Harshkumar Prajapati, Valentina Sosa Fiscella, Federico G López Armengol, Prashnna Kumar Gyawali, Linwei Wang, Nathan D Cahill, Luciano Combi, Santiago del Palacio, Jorge A Combi, Guillermo Gancio, Federico García, Eduardo M Gutiérrez, Fernando Hauscarriaga. 2022.

Vela pulsar: single pulses analysis with machine learning techniques. Monthly Notices of the Royal Astronomical Society, 509(4), pp.5790-5808.

Maryam Toloubidokhti, Nilesh Kumar, Zhiyuan Li, Prashnna K Gyawali, Brian Zenger, Wilson W Good, Rob S MacLeod, Linwei Wang. 2022. Interpretable Modeling and Reduction of Unknown Errors in Mechanistic Operators. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 459-468). Springer, Cham.

Xiajun Jiang, Zhiyuan Li, Ryan Missel, Md Shakil Zaman, Brian Zenger, Wilson W Good, Rob S MacLeod, John L Sapp, and Linwei Wang. 2022. Few-Shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-learning. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 46-56). Springer, Cham.

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Book Chapters
M. Di Somma, G. Graditi, B. Yan, “Handbook of Smart Energy Systems,” Chapter 2. Cost-Sustainability Trade-Off Solutions for the Optimal Planning of Local Integrated Energy Systems from Nanogrids to Communities, Springer, 2022.

N. Raghunathan, M. A. Bragin, B. Yan, and P. Luh, “Exploiting Soft Constraints within Decomposition and Coordination Methods for Sub-hourly Unit Commitment,” International Journal of Electrical Power and Energy Systems, Vol. 139, 2022.

Journal Articles
K. Akash, B. Yan, and A. Bilton, “Machine Learning-Based Load Forecasting for Nanogrid Peak Load Cost Reduction,” Energies, vol.15, no. 18, pp.6721. https://doi.org/10.3390/en15186721, 2022.

M. A. Bragin, B. Yan, A. Kumar, N. Yu, and P. Zhang, “Efficient Operations of Micro-Grids with Meshed Topology and Under Uncertainty through Exact Satisfaction of AC-PF, Droop Control and Tap-Changer Constraints,” Energies, Vol. 15, no. 10, pp. 3662, 2022.

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Krishna Prasad Neupane, Ervine Zheng, Yu Kong, and Qi Yu. 2022. A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations. AAAI Conference on Artificial Intelligence (AAAI). https://ui.adsabs.harvard.edu/abs/2022arXiv220400970P (Acceptance rate: 15%).

Ervine Zheng, Qi Yu, Rui Li, Pengcheng Shi, and Anne Haake. Dual-Level Adaptive Information Filtering for Interactive Image Segmentation, AISTATS, 2022 (pp. 6862-6879).

Wentao Bao, Qi Yu, and Yu Kong. 2022. OpenTAL: Towards Open Set Temporal Action Localization. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 2979-2989).

Deep Shankar Pandey and Qi Yu. 2022. Evidential Conditional Neural Processes. arXiv preprint arXiv:2212.00131.

Moayad Alshangiti, Weishi Shi, Eduardo Lima, Xumin Liu, and Qi Yu. 2022, November. Hierarchical Bayesian multi-kernel learning for integrated classification and summarization of app reviews. Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2022) (pp. 558-569).

Hitesh Sapkota and Qi Yu. 2022, August. Balancing Bias and Variance for Active Weakly Supervised Learning. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 1536-1546).

Niranjana Deshpande, Naveen Sharma, Qi Yu and Daniel E Krutz. 2022, July. Online Learning Using Incomplete Execution Data for Self-Adaptive Service-Oriented Systems. In 2022 IEEE International Conference on Web Services (ICWS) (pp. 296-301). IEEE.

Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, and Siqiang Luo. 2022. Spiking Graph Convolutional Networks. arXiv preprint arXiv:2205.02767.

Deep Shankar Pandey and Qi Yu, 2022. Multidimensional Belief Quantification for Label-Efficient Meta-Learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 14391-14400).

Hitesh Sapkota and Qi Yu. 2022. Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 3212-3221).

Y. Zhu, W. Bao, and Q. Yu, 2022, October. Towards Open Set Video Anomaly Detection. In Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXXIV (pp. 395-412). Cham: Springer Nature Switzerland.

H. Sapkota and Q. Yu. Adaptive Robust Evidential Optimization For Open Set Detection from Imbalanced Data. In The Eleventh International Conference on Learning Representations.

L. Wang, Y. Zhang, X. Zheng, Q. Yu, S. Chen, and J. Ding.  2022. Singular value decomposition‐based behavior‐aware cloud service application programming interfaces recommendation for large‐scale software cloud directory platforms. Concurrency and Computation: Practice and Experience, 34(21), p.e7121.

J. Li, Z. Yu, Z. Zhu, L. Chen, Q. Yu, Z. Zheng, S. Tian, R. Wu, R. and C. Meng.  2022. Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. arXiv preprint arXiv:2208.10364.

  
 
 
 
 
 
 
 
 
 

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E.A. AlOmar, J. Liu, K. Addo, M.W. Mkaouer, C. Newman, A. Ouni, and Z. Yu. 2022. On the documentation of refactoring types. Automated Software Engineering 29 (1), 1-40.

Zhe Yu, Jeffrey C. Carver, Gregg Rothermel, and Tim Menzies. 2022, 15 August. Assessing expert system-assisted literature reviews with a case study. ScienceDirect 200, 116958. doi.org/10.1016/j. eswa.2022.116958.

Zhe Yu, Joymallya Chakraborty, and Tim Menzies. 2022. Fairer machine learning software on multiple sensitive attributes with data preprocessing. arXiv:2107.08310. doi.org/10.48550/arxiv.2107.08310.
 

  

 

  

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Trent Rabe, Anisa Callis, Zhi Zheng, Jamison Heard, Reynold Bailey, and Cecilia O. Alm. 2022. Theory of mind assessment with human-human and human-robot interactions. In: Kurosu, M. (eds) Human-Computer Interaction. Technological Innovation. HCII 2022. Lecture Notes in Computer Science, vol 13303. Springer, Cham. https://doi.org/10.1007/978-3-031-05409-9_41.

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