Lotzi Bölöni is a Professor of Computer Science at the University of Central Florida. He has secondary joint appointments in the Dept. of Electrical and Computer Engineering, at the UCF Center for Research in Computer Vision (CRCV) and the UCF Cluster for Disability, Aging and Technology.

He received a PhD and MSc degree from the Computer Sciences Department of Purdue University and BSc in Computer Engineering from the Technical University of Cluj-Napoca, Romania. He held visiting researcher positions at Computer and Automation Research Institute of the Hungarian Academy of Sciences, University of Rome ``La Sapienza'', Imperial College of London and KTH Royal Institute of Technology, Stockholm, Sweden. He is a senior member of IEEE, member of the ACM, AAAI and the Upsilon Pi Epsilon honorary society.

Selected recent publications and projects:

• Robotics: deep reinforcement learning, deep learning from demonstration, vision-based end-to-end learning
• P. Abolghasemi and L. Bölöni. Accept Synthetic Objects as Real: End-to-End Training of Attentive Deep Visuomotor Policies for Manipulation in Clutter. In Proc. of International Conference on Robotics and Automation (ICRA-2020) pp. 6506-6512, May 2020.   Details   BibTeX   Download  Video New!
• P. Abolghasemi, A. Mazaheri, M. Shah, and L. Bölöni. Pay attention!-Robustifying a Deep Visuomotor Policy through Task-Focused Attention. Proc. of Conference on Computer Vision and Pattern Recognition (CVPR-2019), pp. 4254-4262, 2019.   Download  Video 
• R. Rahmatizadeh, P. Abolghasemi, L. Bölöni, and S. Levine. Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstration. In Proc. of International Conference on Robotics and Automation (ICRA-2018), May 2018.  Download Video 
• R. Rahmatizadeh, P. Abolghasemi, A. Behal, and L. Bölöni. Learning real manipulation tasks from virtual demonstrations using LSTM and MDN. In Proc. of Thirty-Second AAAI Conf. on Artificial Intelligence (AAAI-2018), February 2018.   Download  Video 
• Assistive robotics (NSF funded)
• Human-robot interaction (ARL funded)
• Artificial intelligence: deep learning, computer vision, autonomous agents, human-agent-robot teamwork
• S. Khodadadeh, Saeid Motiian, Zhe Lin, L. Bölöni, and S. Ghadar. Automatic Object Recoloring Using Adversarial Learning. To be presented at IEEE Workshop on Applications of Computer Vision (WACV-2021), January 2021.   Details   BibTeX    New!
• S. Khodadadeh, L. Bölöni, and M. Shah. Unsupervised Meta-Learning For Few-Shot Image Classification. Thirty-third Conference on Neural Information Processing Systems (NeurIPS-2019), pp. 10132-10142, December 2019.   Details   BibTeX   Download  New!
• L.J. Luotsinen and L. Bölöni. Role-Based Teamwork Activity Recognition in Observations of Embodied Agent Actions. In The Seventh Intl. Joint Conf. on Autonomous Agents and Multi-Agent Systems (AAMAS 08), pp. 567–574, 2008.   Download 
• Team activity recognition (NSF, ARL funded)
• Social behavior modeling: Modeling social and cultural behavior
• L. Bölöni, T. S. Bhatia, S. A. Khan, J. Streater, and S. M. Fiore. Towards a computational model of social norms. PLOS ONE, 13(4):e0195331, 2018.   Download 
• T.S. Bhatia, S.A. Khan, and L. Bölöni. Towards an operational model for the propagation of public perception in multi-agent simulation. In 13th International Workshop on Multi-Agent Based Simulation (MABS-2012), pp. 1–12, June 2012.   Download 
• Networking and distributed systems: sensor networks, cloud computing, scheduling
• S. Zehtabian, S. Khodadadeh, L. Bölöni, and D. Turgut. Privacy-Preserving Learning of Human Activity Predictors in Smart Environments. To be presented IEEE International Conference on Computer Communications (INFOCOM-21), July 2021.   Details   BibTeX   Download New!
• P. Gjanci, C. Petrioli, S. Basagni, C.A. Phillips, L. Bölöni, and D. Turgut. Path Finding for Maximum the Value of Sensed Information in Multi-modal Underwater Wireless Sensor Networks. IEEE Transactions on Mobile Computing, 17:404–418, February 2018.  Download 
• D. Turgut and L. Bölöni. IVE: improving the value of information in energy-constrained intruder tracking sensor networks. In IEEE Int. Conf. on Comunications (ICC-2013), pp. 6360–6364, 2013. Best Paper Award   Download 
• Artificial General Intelligence: narrative reasoning
• L. Bölöni. Integrating perception, narrative, premonition and confabulatory continuation. Biologically Inspired Cognitive Architectures, 8:118–129, April 2014.   Download 
• L. Bölöni. Autobiography based prediction in a situated AGI agent. In Seventh Conf. of Artificial General Intelligence (AGI-2014), pp. 11–21, August 2014. Kurzweil Best AGI Idea Prize 2014   Download 
• Xapagy cognitive architecture - a system for narrative reasoning

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