Armin Lederer
Assistant Professor
Works on data-driven control, machine learning in closed-loop systems and safe intelligent robotics.
Armin Lederer's lab at NUS works on planning, control & multi-robot systems. 24 papers since 2023, 9 at top venues, mostly ICML and TAC. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 38%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 7 papers2026 · T1 5 · collecting
- 5 papers2025 · T1 2
- 4 papers2024 · T1 1
- 8 papers2023 · T1 1
T1 venuesOtherVenues: ICML, TAC, ACC, CDC, AISTATS
Research focuspaper titles that use each topic's words
- Planning, control & multi-robot systems19 papers
- safe5 papers
- data-driven1 paper
- intelligent robotics0 papers
- intelligent0 papers
Paper list
From the lab homepage.
20267 papers
- TAC (T1)“Episodic Gaussian Process-Based Learning Control with Vanishing Tracking Errors”
- Proceedings of the European Control Conference“On the Existence of Quadratic Control Lyapunov Functions for Koopman-Operator based Bilinear Systems”
- ICML (T1)“On Uniform Error Bounds for Kernel Regression under Non-Gaussian Noise”
- ICML (T1)“Policy Search via Bayesian Optimization with Temporal Difference Gaussian Processes”
- ICML (T1)“SAD-Flower: Flow Matching for Safe, Admissible, and Dynamically Consistent Planning”
- TAC (T1)“Safe Barrier-Constrained Control of Uncertain Systems via Event-triggered Learning”
- ACC“Safe Event-Triggered Learning for Sampled-Data Systems”
20255 papers
- IEEE Control Systems Letters, 9: 1231-1236“Distributed Risk-Sensitive Safety Filters for Uncertain Discrete-Time Systems”
- AISTATS (T1)“Koopman-Equivariant Gaussian Processes”
- CDC“Learning High-Order CBFs using Gaussian Processes for Systems in Brunovsky Canonical Form”
- TAC (T1)“Risk-Sensitive Safety Filters for Reinforcement Learning with Probabilistic Guarantees”
- Proceedings of the Annual Learning for Dynamics & Control Conference“Toward Near-Globally Optimal Nonlinear Model Predictive Control via Diffusion Models”
20244 papers
- ACC“Cooperative Learning with Gaussian Processes for Euler-Lagrange Systems Tracking Control under Switching Topologies”
- IROS (T1)“Data-driven Force Observer for Human-Robot Interaction with Series Elastic Actuators using Gaussian Processes”
- Proceedings of the European Control Conference“Learning-Based Optimal Control with Performance Guarantees for Unknown Systems with Latent States”
- IEEE Open Journal of Control Systems, 3: 358-374“Stable Inverse Reinforcement Learning: Policies from Control Lyapunov Landscapes”
20238 papers
- Proceedings of the Conference on Learning for Dynamics and Control“Can Learning Deteriorate Control? Analyzing Computational Delays in Gaussian Process-Based Event-Triggered Online Learning”
- IFAC-PapersOnLine 56(2): 847-853“Deep Learning based Uncertainty Decomposition for Real-Time Control”
- NeurIPS (T1)“Koopman Kernel Regression”
- IFAC-PapersOnLine 56(2): 501-506“Model-Based Robot Control with Gaussian Process Online Learning: An Experimental Demonstration”
- IEEE Control Systems Letters, 7: 2665 - 2670“Rigid Motion Gaussian Processes with SE(3) Kernel and Application to Visual Pursuit Control”
- CDC“Risk-Sensitive Inhibitory Control for Safe Reinforcement Learning”
- IFAC-PapersOnLine 56 (2): 2250-2256“Safe Learning-Based Control of Elastic Joint Robots via Control Barrier Functions”
- RA-L“Vision-Based Uncertainty-Aware Motion Planning based on Probabilistic Semantic Segmentation”
Where alumni went
Alumni are not listed on the lab homepage.
Apply to NUSFall 2027
School of Computing PhD in Computer Science
- Round
- Main
- Opens
- —
- GRE
- See program page
- English
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- Fee
- See program page
Not yet confirmed for this intake.
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Data
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