| 2025 | CoDIT | Disentangled Object-Centric Configuration Representation Learning for Articulated Robot Arms. | Daniel Nikovski |
| 2025 | ICINCO | Observation-Based Inverse Kinematics for Visual Servo Control. | Daniel Nikovski |
| 2025 | SAC | Learning Visual Servoing for Nonholonomic Mobile Robots with Uncalibrated Cameras. | Jen-Wei Wang, Daniel Nikovski |
| 2024 | CoDIT | Adaptive Velocity Estimators for Learning Control. | Daniel Nikovski, William Yerazunis |
| 2024 | CoDIT | Memory-Based Global Iterative Linear Quadratic Control. | Daniel Nikovski, Junmin Zhong, William Yerazunis |
| 2024 | ICINCO | Memory-Based Learning of Global Control Policies from Local Controllers. | Daniel Nikovski, Junmin Zhong, William Yerazunis |
| 2024 | ICMLA | Learning Time-Optimal Control of Gantry Cranes. | Junmin Zhong, Daniel Nikovski, William Yerazunis, Taishi Ando |
| 2023 | ANT | Travel-time prediction using neural-network-based mixture models. | Abhishek Sharma, Jing Zhang, Daniel Nikovski, Finale Doshi-Velez |
| 2023 | ANT | Estimating traffic density using transformer decoders. | Yinsong Wang, Jing Zhang, Daniel Nikovski, Takuro Kojima |
| 2023 | CoDIT | Model-Based Learning Controller Design for a Furuta Pendulum. | Daniel Nikovski, William Yerazunis, Abraham Goldsmith |
| 2023 | ICMLA | Stochastic Learning Manipulation of Object Pose With Under-Actuated Impulse Generator Arrays. | Chuizheng Kong, William Yerazunis, Daniel Nikovski |
| 2023 | IROS | Constrained Dynamic Movement Primitives for Collision Avoidance in Novel Environments. | Seiji Shaw, Devesh K. Jha, Arvind U. Raghunathan, Radu Corcodel, Diego Romeres, George Konidaris, Daniel Nikovski |
| 2022 | ICMLA | Transfer Learning for Bayesian Optimization with Principal Component Analysis. | Hideyuki Masui, Diego Romeres, Daniel Nikovski |
| 2022 | IJCNN | Deep Reinforcement Learning for Optimal Sailing Upwind. | Takumi Suda, Daniel Nikovski |
| 2021 | AAAI | Personalizing Individual Comfort in the Group Setting. | Emil Laftchiev, Diego Romeres, Daniel Nikovski |
| 2021 | ICRA | Tactile-RL for Insertion: Generalization to Objects of Unknown Geometry. | Siyuan Dong, Devesh K. Jha, Diego Romeres, Sangwoon Kim, Daniel Nikovski, Alberto Rodriguez |
| 2020 | CoRL | Deep Reactive Planning in Dynamic Environments. | Kei Ota, Devesh K. Jha, Tadashi Onishi, Asako Kanezaki, Yusuke Yoshiyasu, Yoko Sasaki, Toshisada Mariyama, Daniel Nikovski |
| 2020 | ICML | Can Increasing Input Dimensionality Improve Deep Reinforcement Learning? | Kei Ota, Tomoaki Oiki, Devesh K. Jha, Toshisada Mariyama, Daniel Nikovski |
| 2020 | ICRA | Local Policy Optimization for Trajectory-Centric Reinforcement Learning. | Patrik Kolaric, Devesh K. Jha, Arvind U. Raghunathan, Frank L. Lewis, Mouhacine Benosman, Diego Romeres, Daniel Nikovski |
| 2020 | IJCNN | Personalized Destination Prediction Using Transformers in a Contextless Data Setting. | Athanasios Tsiligkaridis, Jing Zhang, Hiroshi Taguchi, Daniel Nikovski |
| 2019 | ICRA | Sim-to-Real Transfer Learning using Robustified Controllers in Robotic Tasks involving Complex Dynamics. | Jeroen van Baar, Alan Sullivan, Radu Cordorel, Devesh K. Jha, Diego Romeres, Daniel Nikovski |
| 2019 | ICRA | Semiparametrical Gaussian Processes Learning of Forward Dynamical Models for Navigating in a Circular Maze. | Diego Romeres, Devesh K. Jha, Alberto Dalla Libera, Bill Yerazunis, Daniel Nikovski |
| 2019 | IROS | Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning. | Kei Ota, Devesh K. Jha, Tomoaki Oiki, Mamoru Miura, Takashi Nammoto, Daniel Nikovski, Toshisada Mariyama |
| 2018 | ICML | Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control. | Yangchen Pan, Amir-massoud Farahmand, Martha White, Saleh Nabi, Piyush Grover, Daniel Nikovski |
| 2018 | IJCAI | Time Series Chains: A Novel Tool for Time Series Data Mining. | Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh |
| 2018 | SAFEProcess | Anomaly Detection in Discrete Manufacturing Systems using Event Relationship Tables. | Emil Laftchiev, Xinmaio Sun, Hoang Anh Dau, Daniel Nikovski |
| 2017 | AISTATS | Value-Aware Loss Function for Model-based Reinforcement Learning. | Amir Massoud Farahmand, Andr Barreto, Daniel Nikovski |
| 2017 | ICDM | Matrix Profile VII: Time Series Chains: A New Primitive for Time Series Data Mining (Best Student Paper Award). | Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh |
| 2016 | IJCNN | Regularized covariance matrix estimation with high dimensional data for supervised anomaly detection problems. | Daniel Nikovski, Kiran Byadarhaly |
| 2006 | SAC | Induction of compact decision trees for personalized recommendation. | Daniel Nikovski, Veselin Kulev |
| 2004 | ICRA | Optimal Parking in Group Elevator Control. | Matthew Brand, Daniel Nikovski |
| 2004 | MFCS | Theory and Applied Computing: Observations and Anecdotes. | Matthew Brand, Sarah F. Frisken Gibson, Neal Lesh, Joe Marks, Daniel Nikovski, Ronald N. Perry, Jonathan S. Yedidia |
| 2003 | UAI | Marginalizing Out Future Passengers in Group Elevator Control. | Daniel Nikovski, Matthew Brand |
| 2002 | IROS | Learning probabilistic models for state tracking of mobile robots. | Daniel Nikovski, Illah R. Nourbakhsh |
| 2002 | IROS | Learning probabilistic models for optimal visual servo control of dynamic manipulation. | Daniel Nikovski, Illah R. Nourbakhsh |
| 2000 | AAAI | Grounding State Representations in Sensory Experience for Reasoning and Planning by Mobile Robots. | Daniel Nikovski |
| 2000 | ICML | Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots. | Daniel Nikovski, Illah R. Nourbakhsh |
| 1996 | AAAI | Amelia. | Reid G. Simmons, Sebastian Thrun, Greg Armstrong, Richard Goodwin, Karen Zita Haigh, Sven Koenig, Shyjan Mahamud, Daniel Nikovski, Joseph O'Sullivan |
| 1992 | AIMSA | Prognostic Expert Systems on a Hybrid Connectionist Environment. | Nikola K. Kasabov, Daniel Nikovski |