Lotzi Bölöni is a Professor of
Computer Science at the University of Central
Florida. He is a co-director of the AI Things Laboratory. 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
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.
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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.
- 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.
- Assistive robotics (NSF funded)
- Human-robot interaction (ARL funded)
- Artificial intelligence: deep learning, computer vision, autonomous agents, human-agent-robot teamwork
- S. Khodadadeh, S. Zehtabian,
S. Vahidian, W. Wang, B. Lin, and L. Bölöni . Unsupervised
Meta-Learning through Latent-Space Interpolation in Generative Models. To be presented at the International Conference
on Learning Representations (ICLR-2021), July 2021.
- S. Khodadadeh, Saeid Motiian, Zhe Lin, L.
Bölöni, and S. Ghadar. Automatic Object Recoloring Using Adversarial Learning. Proc. of IEEE
Workshop on Applications of Computer Vision (WACV-2021), January 2021.
S. Khodadadeh, L. Bölöni, and M. Shah. Unsupervised
For Few-Shot Image Classification. Thirty-third Conference on Neural Information Processing Systems (NeurIPS-2019), pp. 10132-10142, December 2019.
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- 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.
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.
- 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.
- 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.
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- 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
- Artificial General Intelligence: narrative reasoning
- L. Bölöni. Integrating perception, narrative, premonition and confabulatory continuation. Biologically Inspired Cognitive Architectures,
8:118–129, April 2014.
- 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
cognitive architecture - a system for narrative reasoning
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