Scholarly Works

Publications (Peer Reviewed)

  1. A Lesage-Landry, J A Taylor, I Shames, “Second-order Online Nonconvex Optimization”, in IEEE Transactions on Automatic Control, 2021. DOI: 10.1109/TAC.2020.3040372
  2. A Pavlov, I Shames, C Manzie, “Interior Point Differential Dynamic Programming” in IEEE Transaction on Control Systems Technology, 2021. DOI: 10.1109/TCST.2021.3049416
  3. Marzoughi and A. V. Savkin, “Autonomous Navigation of a Team of Unmanned Surface Vehicles for Intercepting Intruders on a Region Boundary,” Sensors, vol. 21, no. 1, p. 297, 2021. https://doi.org/10.3390/s21010297
  4. Savkin and H. Huang, “Bioinspired Bearing Only Motion Camouflage UAV Guidance for Covert Video Surveillance of a Moving Target,” IEEE Syst. J., 2020.
  5. Savkin and H. Huang, “Navigation of a UAV Network for Optimal Surveillance of a Group of Ground Targets Moving Along a Road,” IEEE Trans. Intell. Transp. Syst., 2021.
  6. Savkin and H.Huang, “Navigation of a Network of Aerial Drones for Monitoring a Frontier of a Moving Environmental Disaster Area”, IEEE Systems Journal. DOI: 10.1109/JSYST.2020.2966779.
  7. A .V. Savkin, H.Huang and W.Ni, “Securing UAV Communication in the Presence of Stationary or Mobile Eavesdroppers via Online 3D Trajectory Planning”, IEEE Wireless Communications Letters. DOI: 10.1109/LWC.2020.2986291.
  8. Fischer T, Milford M. “Event-Based Visual Place Recognition with Ensembles of Temporal Windows”. IEEE Robotics and Automation Letters 5(4):6924-6931
  9. Zhu, H. Liu, A. Ataei, Y. Munk, T. Daniel, and I. C. Paschalidis, “Learning from animals: How to Navigate Complex Terrains,” PLoS Comput. Biol., vol. 16, no. 1, p. e1007452, 2020.
  10. L. Molloy, T. Fischer, M. Milford, G.N. Nair, “Intelligent Reference Curation for Visual Place Recognition via Bayesian Selective Fusion”. IEEE Robotics and Automation Letters 6(2):588-595, 2021, with parallel presentation at ICRA, May 2021.
  11. Pavlov, I. Shames, and C. Manzie. “Minimax strategy in approximate model predictive control”. Automatica, 111:108649, 2020.
  12. Spiridonoff, A. Olshevsky, and I. C. Paschalidis, “Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions.,” Mach. Learn. Res., vol. 21, no. 58, pp. 1–47, 2020.
  13. Alexander AS, Carstensen LC, Hinman JR, Raudies F, Chapman GW, Hasselmo ME (2020) “Egocentric boundary vector tuning of the retrosplenial cortex”. Science Advances, 6: eaaz2322. DOI: 10.1126/sciadv.aaz2322.
  14. Alexander AS, Robinson JC, Dannenberg H, Kinsky NR, Levy SJ, Mau W, Chapman GW, Sullivan DW, Hasselmo ME (2020) “Neurophysiological coding of space and time in the hippocampus, entorhinal cortex and retrosplenial cortex”. Brain Neurosci. Adv. 4: 2398212820972871. DOI: 10.1177/2398212820972871
  15. Artin Spiridonoff, Alex Olshevsky, and I. C. Paschalidis, “Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions” Journal on Machine Learning Research, Vol. 21, No. 58, pages 1–47, 2020, doi: http://jmlr.org/papers/v21/18-813.html.
  16. Burkitt A.N., Hogendoorn, H. (2021) “Predictive visual motion extrapolation emerges spontaneously and without supervision at each layer of a hierarchical neural network with spike-timing-dependent plasticity”, Journal of Neuroscience 22 April 2021, JN-RM-2017-20; DOI: 10.1523/JNEUROSCI.2017-20.2021
  17. Dannenberg, H., Lazaro, H., Nambiar, P., Hoyland, A., Hasselmo, M.E. (2020) “Effects of visual inputs on neural dynamics for coding of location and running speed in medial entorhinal cortex”. eLife, 9: e62500. DOI: 7554/eLife.62500.
  18. David M. Rosen, Kevin J. Doherty, Antonio Teran Espinoza, and John J. Leonard. “Advances in Inference and Representation for Simultaneous Localization and Mapping”. Annual Review of Control, Robotics, and Autonomous Systems. DOI https://doi.org/10.1146/annurev-control-072720-082553.
  19. Elham Saraee, Mona Jalal, Margrit Betke. “Visual complexity analysis using deep intermediate-layer features,” Computer Vision and Image Understanding. Volume 195, 2020, 102949, ISSN 1077-3142, https://doi.org/10.1016/j.cviu.2020.102949.
  20. Huang, A. V. Savkin, and W. Ni, “Online UAV Trajectory Planning for Covert Video Surveillance of Mobile Targets,” IEEE Trans. Autom. Sci. Eng., 2021.
  21. Huang and A. V. Savkin, “Autonomous Navigation of a Solar-Powered UAV for Secure Communication in Urban Environments with Eavesdropping Avoidance,” Future Internet, vol. 12, no. 10, p. 170, 2020.
  22. Huang and A. V. Savkin, “Energy-Efficient Autonomous Navigation of Solar-Powered UAVs for Surveillance of Mobile Ground Targets in Urban Environments,” Energies, vol. 13, no. 21, p. 5563, 2020.
  23. Huang and A. V. Savkin, “Energy-efficient decentralized navigation of a team of solar-powered UAVs for collaborative eavesdropping on a mobile ground target in urban environments,” Ad Hoc Netw., vol. 117, p. 102485, 2021.
  24. Huang and A. V. Savkin, “Navigating UAVs for Optimal Monitoring of Groups of Moving Pedestrians or Vehicles,” IEEE Trans. Veh. Technol., vol. 70, no. 4, pp. 3891–3896, 2021.
  25. Huang and A. V. Savkin, “Path Planning for a Solar-Powered UAV Inspecting Mountain Sites for Safety and Rescue,” Energies, vol. 14, no. 7, p. 1968, 2021.
  26. Huang, A. V. Savkin, and C. Huang, “Decentralised Autonomous Navigation of a UAV Network for Road Traffic Monitoring,” IEEE Trans. Aerosp. Electron. Syst., 2021.
  27. Huang, A. V. Savkin, and X. Li, “Reactive Autonomous Navigation of UAVs for Dynamic Sensing Coverage of Mobile Ground Targets,” Sensors, vol. 20, no. 13, p. 3720, 2020.
  28. Huang, A.V. Savkin and W.Ni, “Energy-Efficient 3D Navigation of a Solar-Powered UAV for Secure Communication in the Presence of Eavesdroppers and No-Fly Zones”, Energies, 13(6): 1445, 2020. doi:10.3390/en13061445.
  29. Hasselmo ME, Alexander AS, Hoyland A, Robinson JC, Bezaire MJ, Chapman GW, Saudargiene A, Carstensen LC, Dannenberg H. “The Unexplored Territory of Neural Models: Potential Guides for Exploring the Function of Metabotropic Neuromodulation”. Neuroscience. 2021 Feb 21;456:143-158. doi: 10.1016/j.neuroscience.2020.03.048. Epub 2020 Apr 8. PMID: 32278058; PMCID: PMC7541517.
  30. Hausler S, Chen Z, Hasselmo ME, Milford M. (2020). “Bio-inspired multi-scale fusion”.  Cybern. 114(2):209-229, doi: 10.1007/s00422-020-00831-z.
  31. Henghui Zhu, Hao Liu, Armin Ataei, Yonatan Munk, Thomas Daniel, and I. C. Paschalidis, “Learning from Animals: How to Navigate Complex Terrains”, PLOS Computational Biology, 16(1): e1007452, 2020, doi:10.1371/journal.pcbi.1007452.
  32. Henghui Zhu, I. C. Paschalidis, Allen Chang, Chantal E. Stern, Michael E. Hasselmo, “A Neural Circuit Model for a Contextual Association Task Inspired by Recommender Systems”, Hippocampus, Special Issue: Computational models of hippocampus and related structures–Part I, Vol. 30, Issue 4 (April), pages 384-395, 2020, doi: 10.1002/hipo.23194.
  33. Levy SJ, Kinsky NR, Mau W, Sullivan DW, Hasselmo ME (2021) “Hippocampal spatial memory representations in mice are heterogeneously stable.” Hippocampus 31(3): 244-260. DOI: 10.1002/hipo.23272.
  34. Lian, Y., Almasi, A., Grayden, D.B., Kameneva, T., Burkitt, A.N, Meffin, H. (2021) “Learning receptive field properties of complex cell”s in V1, PLOS Computational Biology 17 (3): e1007957, doi: 10.1371/journal.pcbi.1007957
  35. Manjesh K. Hanawal, Hao Liu, Henghui Zhu, and I. C. Paschalidis, “Learning Policies for Markov Decision Processes from Data”, IEEE Transactions on Automatic Control, Vol. 64, Issue 6, June 2019, pages 2298–2309, doi:10.1109/TAC.2018.2866455.
  36. Mau W, Hasselmo ME, Cai DJ (2020) “The brain in motion: How ensemble fluidity drives memory-updating and flexibility”. ELife. 9:e63550. DOI: 10.7554/eLife.63550
  37. Biggar, M Zamani, I Shames, “An Expressiveness Hierarchy of Behavior Trees and Related Architectures “, IEEE Robotics and Automation Letters, 2021. DOI: 10.1109/LRA.2021.3074337
  38. Shi Pu, Alex Olshevsky, and I. C. Paschalidis, “Asymptotic Network Independence in Distributed Stochastic Optimization for Machine Learning”, IEEE Signal Processing Magazine, Vol. 37, No. 3, pages 114-122, 2020, doi:10.1109/MSP.2020.2975212.
  39. Elmokadem and A. V. Savkin, “A Method for Autonomous Collision-Free Navigation of a Quadrotor UAV in Unknown Tunnel-Like Environments,” Robotica, 2021. DOI: https://doi.org/10.1017/S0263574721000849
  40. Tingting Xu, Henghui Zhu, and I. C. Paschalidis, “Learning Parametric Policies and Transition Probability Models of Markov Decision Processes from Data”, European Journal of Control, doi:10.1016/j.ejcon.2020.04.003.
  41. Yanbo Lian, Anthony N. Burkitt. “Learning an efficient hippocampal place map from entorhinal inputs using non-negative sparse coding,” Accepted, doi: https://doi.org/10.1101/2020.08.12.248534
  42. Zhu, H, Paschalidis, IC, Chang, A, Stern, CE, Hasselmo, ME. “A neural circuit model for a contextual association task inspired by recommender systems”. Hippocampus. 2020; 30: 30: 384– 395. https://doi.org/10.1002/hipo.23194
  43. Zoltán Kócsi, Trevor Murray, Hansjürgen Dahmen, Ajay Narendra, and Jochen Zeil. “The Antarium: A Reconstructed Visual Reality Device for Ant Navigation Research.” Frontiers in Behavioral Neuroscience. 14, 2020. DOI=10.3389/fnbeh.2020.599374

Book Chapters (Peer Reviewed)

  1. Ruidi Chen and Ioannis Ch. Paschalidis (2020), “Distributionally Robust Learning”, Foundations and Trends® in Optimization: Vol. 4: No. 1-2, pp 1-243. http://dx.doi.org/10.1561/2400000026

Conference Papers (Peer Reviewed)

  1. C. Wang, M. Bahreinian, and R. Tron, “Chance Constraint Robust Control with Control Barrier Functions,” presented at the American Control Conference, 2021. [Online]. Available: arXiv preprint arXiv:2012.10573
  2. Chenhongyi Yang, Vitaly Ablavsky, Kaihong Wang, Qi Feng, and Margrit Betke, “Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes” 16th European Conference on Computer Vision: ECCV’20 Online. August, 2020. https://doi.org/10.1007/978-3-030-58523-5_31, pp 530-546.
  3. D. Fourie, A. Teran Espinoza, M. Kaess, and J. Leonard. “Characterizing Marginalization and Incremental Operations on the Bayes Tree.” In Proceedings of the Workshop on Algorithmic Foundations of Robotics (WAFR), June, 2020.
  4. D. Fourie, N. R. Rypkema, S. D. Claassens, P. Vaz Teixeira, J. Leonard. “Towards Real-Time Non-Gaussian SLAM for Underdetermined Navigation.” In Proceedings of the International Conference on Robots and Systems, Las Vegas, October, 2020.
  5. Elad Michael, Daniel Zelazo, Tony A. Wood, Chris Manzie, and Iman Shames. “Optimization with Zeroth-Order Oracles in Formation.” Published in 2020 59th IEEE Conference on Decision and Control (CDC) Dec. 14-18, 2020. DOI: 10.1109/CDC42340.2020.9304272
  6. G. Colabufo, P. Dower, and I. Shames. “Newton’s method: sufficient conditions for practical and input-to-state stability”. IFAC World Congress, 2020.
  7. Garg S, Fischer T, Milford M, “Where is your place, Visual Place Recognition?”, Proceedings of the International Joint Conference on Artificial Intelligence, 2021.
  8. H. Hailong, A. V. Savkin, and W. Ni, “Decentralized Covert and Collaborative Radio Surveillance on a Group of Mobile Ground Nodes by a UAV Swarm,” presented at the IEEE Industrial Informatics Conference (INDIN2020), 2020.
  9. Hausler S, Garg S, Xu M, Milford M, Fischer T, “Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021.
  10. H. Huang, A.V.Savkin and W.Ni, “A Method for Covert Video Surveillance of a Car or a Pedestrian by an Autonomous Aerial Drone via Trajectory Planning”, IEEE International Conference on Control, Automation and Robotics, 2020.
  11. J. Queeney, I. C. Paschalidis, and C. G. Cassandras, “Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach,” 35th AAAI Conference on Artificial Intelligence (AAAI-21), Feb. 2021
  12. Jiahui Fu, Qiangqiang Huang, Kevin Doherty, Yue Wang, and John J. Leonard. “A Multi-Hypothesis Approach to Pose Ambiguity in Object-Based SLAM.” Under Review, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021). 9/​27/2021 – 10/1/2021. Prague, Czech Republic
  13. John Baillieul and Feiyang Kang, “Visual Navigation with a 2-pixel Camera—Possibilities and Limitations,” In Proceedings of the 21st IFAC World Congress in Berlin, Germany, July 12-17, 2020. Also available from http://arxiv.org/abs/2103.00285.
  14. J. Baillieul, “Perceptual Control with Large Feature and Actuator Networks,”  2019 IEEE 58th Conference on Decision and Control (CDC), Nice, France, December 11-13, 2019, pp. 3819-3826, doi: 10.1109/CDC40024.2019.9029615.
  15. Ok, K. Liu, and N. Roy, “Hierarchical Object Map Estimation for Efficient and Robust Navigation,” presented at the Proceedings of the IEEE Conference on Robotics and Automation (ICRA), Virtual, 2021.
  16. Kaihong Wang, Chenhongyi Yang, and Margrit Betke. “Consistency Regularization with High-dimensional Non-adversarial Source-guided Perturbation for Unsupervised Domain Adaptation in Segmentation”. The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), February 2021. 9 pages.
  17. M. Bahreinian, E. Aasi, and R. Tron, “Robust Planning and Control For Polygonal Environments via Linear Programming,” presented at the American Control Conference, 2021. [Online]. Available: arXiv preprint arXiv:1910.07976
  18. M. Gnanasekera, A.V.Savkin and J.Katupitiya, “Range Measurements Based UAV Navigation for Intercepting Ground Targets”, IEEE International Conference on Control, Automation and Robotics, 2020.
  19. Pavlov, Andrei and Muller, Matthias an Manzie, Chris and Shames, Iman, “Complexity minimisation of suboptimal MPC without terminal constraints”, IFAC World Congress, 2020.
  20. Q. Huang, C. Pu, D. Fourie, K. Khosoussi, J. P. How, and J. J. Leonard. “NF-iSAM: Incremental Smoothing and Mapping via Normalizing Flows”. In IEEE Intl. Conf. on Robotics and Automation (ICRA), Prague, Czech Republic, May, 2021.
  21. Renganathan, Venkatraman and Shames, Iman and Summers, Tyler H, “Towards Integrated Perception and Motion Planning with Distributionally Robust Risk Constraints”, IFAC World Congress, 2020.
  22. Ruidi Chen and I. C. Paschalidis, “A Distributionally Robust Optimization Approach for Multivariate Linear Regression under the Wasserstein Metric”, Proceedings of the 58th IEEE Conference on Decision and Control}, pages 3655–3660, December 11-13, 2019, Nice, France,  doi: 10.1109/CDC40024.2019.9029832.
  23. T. Elmokadem, “A 3D Reactive Navigation Method for UAVs in Unknown Tunnel-like Environments,” in 2020 Australian and New Zealand Control Conference (ANZCC), 2020, pp. 119–124.
  24. T. Elmokadem, “A Control Strategy for the Safe Navigation of UAVs Among Dynamic Obstacles using Real-Time Deforming Trajectories,” in 2020 Australian and New Zealand Control Conference (ANZCC), 2020, pp. 97–102.
  25. L. Molloy, G.N. Nair, “Smoothing-Averse Control: Covertness and Privacy from Smoothers”. In Proc. American Control Conference, May 2021.
  26. Taiyao Wang and I. C. Paschalidis, “Convergence of Parameter Estimates for  Regularized Mixed Linear Regression Models”, Proceedings of the 58th IEEE Conference on Decision and Control, pages 3664-3669, December 11-13, 2019, Nice, France, doi: 10.1109/CDC.2018.8619435.
  27. V. Amblard, T. Osedach, A. Croux, A. Speck, John J. Leonard. “Lidar-Monocular Surface Reconstruction Using Line Segments”. In IEEE Intl. Conf. on Robotics and Automation (ICRA), Prague, Czech Republic, May, 2021.
  28. Wang, Q., Zheng, Y., & Betke, M. (2020). “A method for detecting text of arbitrary shapes in natural scenes that improves text spotting”. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE. doi:10.1109/cvprw50498.2020.00278
  29. X. Li, H. Huang and A.V. Savkin, “Autonomous Drone Shark Shield: A Novel Shark Repelling System for Protecting Swimmers and Surfers,” IEEE International Conference on Control, Automation and Robotics, 2020.
  30. X. Li, H. Huang, and A. V. Savkin, “Use of A UAV Base Station for Searching and Bio-inspired Covert Video Surveillance of Tagged Wild Animals,” in 2020 Australian and New Zealand Control Conference (ANZCC), 2020, pp. 87–90.
  31. Y. Zhang and J. J. Leonard. “A Front-End for Dense Monocular Visual Odometry using a Learned Outlier Mask Prior Localization and Mapping”. In IEEE Intl. Conf. on Robotics and Automation (ICRA), Prague, Czech Republic, May, 2021.
  32. Yi Zheng, Wenda Qin, Derry Wijaya, and Margrit Betke “LAL: Linguistically Aware Learning for Scene Text Recognition.” MM ’20: Proceedings of the 28th ACM International Conference on Multimedia. October 12–16, 2020, Seattle, WA, USA. https://dl.acm.org/doi/pdf/10.1145/3394171.3413913
  33. Yiwen Gu, Shreya Pandit, Elham Saraee, Timothy Nordahl, TerryEllis, and Margrit Betke. “Home-based Physical Therapy with an Interactive Computer Vision System”. Assistive Computer Vision and Robotics Workshop at the International Conference on Computer Vision Workshop, Seoul, South Korea, October 2019.
  34. Z. Zhang and I. C. Paschalidis, “Provable Hierarchical Imitation Learning via EM,” ICML 2020 Workshop on Theoretical Foundations of Reinforcement Learning, Jul. 2020. [Online]. Available: https://wensun.github.io/rl_theory_workshop_2020_ICML.github.io/
  35. Z. Zhang and I. Paschalidis, “Provable Hierarchical Imitation Learning via EM,” in International Conference on Artificial Intelligence and Statistics, 2021, pp. 883–891.
  36. Zheng, Y., Qin, W., Wijaya, D., & Betke, M. (2020). “LAL: Linguistically Aware Learning for Scene Text Recognition”. In Proceedings of the 28th ACM International Conference on Multimedia. ACM. doi:10.1145/3394171.3413913

    Theses

    1. Chiara Boretti and Philippe Bich, “Dictionary of Motion Primitives for Vision-Based Navigation Using Optical Flow,” A Masters Degree Thesis in Mechatronic Engineering, Politecnico di Torino, April, 2021. Co-Advisor: Baillieul.
    2. Andrei Pavlov, “Efficient Methods for Control of Dynamical Systems”, PhD in Electrical and Electronic Engineering, University of Melbourne, 2021, Advisor: Shames.
    3. Ruidi Chen, “Distributionally Robust Learning under the Wasserstein Metric”, Ph.D. in Systems Engineering, Boston University, September 2019. Advisor: Paschalidis.
    4. Tingting Xu, “Machine Learning for Effective Predictions and Prescriptions in Health Care”, Ph.D. in Systems Engineering, Boston University, May 2020. Advisor: Paschalidis.
    5. Henghui Zhu, “Making Decisions Based on Context: Models and Applications in Cognitive Sciences and Natural Language Processing”, Ph.D. in Systems Engineering, Boston University, December 2019. Advisor: Paschalidis.