Maryam Kamgarpour

Edit profile

maryam.kamgarpour@epfl.ch +41 21 693 57 30 https://www.epfl.ch/labs/sycamore

EPFL STI IGM SYCAMORE
ME C1 400 (Bâtiment ME)
Station 9
1015 Lausanne

+41 21 693 57 30
Office: ME C1 400
EPFL > STI > IGM > SYCAMORE

Web site: Web site: https://www.epfl.ch/labs/sycamore/

+41 21 693 57 30
EPFL > STI > STI-SGM > SGM-ENS

vCard
Administrative data

Biography

Maryam Kamgarpour holds a Doctor of Philosophy in Engineering from the University of California, Berkeley and a Bachelor of Applied Science from University of Waterloo, Canada. Her research is on safe decision-making and control under uncertainty, game theory and mechanism design, mixed integer and stochastic optimization and control. Her theoretical research is motivated by control challenges arising in intelligent transportation networks, robotics, power grid systems and healthcare. She is the recipient of NASA High Potential Individual Award, NASA Excellence in Publication Award, and the European Union (ERC) Starting Grant.

Publications

Infoscience publications

Infoscience

Geometric Learning: Leveraging differential geometry for learning and control

B. Fichera

Lausanne, EPFL, 2024. DOI : 10.5075/epfl-thesis-10534.

Maryam Kamgarpour

Biography

Publications

Infoscience publications

Infoscience

Geometric Learning: Leveraging differential geometry for learning and control

Scalable constrained optimization

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Identifiability and Generalizability in Constrained Inverse Reinforcement Learning

Multi-agent Reinforcement Learning for Assembly of a Spanning Structure

Multi-robot task allocation for safe planning against stochastic hazard dynamics

Certification of Bottleneck Task Assignment With Shortest Path Criteria

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

Safe Zeroth-Order Optimization Using Linear Programs

Learning to make mixed-integer robot motion planning easy

Provable Convergence Guarantees for Constrained Inverse Reinforcement Learning

Reinforcement learning for scaffold-free construction of spanning-structures

Constrained Inverse Reinforcement Learning: Challenges and Solutions for Real World Implementation

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Learning and optimization of anticipatory feedback controllers for robot manipulation

Chance-Constrained Trajectory Planning With Multimodal Environmental Uncertainty

Enabling inter-area reserve exchange through stable benefit allocation mechanisms *

Safe Motion Planning against Multimodal Distributions Based on a Scenario Approach

Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation

Coordination and control of a group of ground robots

Optimal Task Assignment and Collision Avoidance for Mobile Robots

Deep Learning Methods for Socially-Aware Human Trajectory Forecasting

A comment on performance guarantees of a greedy algorithm for minimizing a supermodular set function on comatroid

Trajectory planning under environmental uncertainty with finite-sample safety guarantees

Bandit Online Learning of Nash Equilibria in Monotone Games

A market-based approach for enabling inter-area reserve exchange

Performance guarantees of forward and reverse greedy algorithms for minimizing nonsupermodular nonsubmodular functions on a matroid

Optimal Linear Controller for Minimizing DC Voltage Oscillations in MMC-Based Offshore Multiterminal HVDC Grids

Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems

Fast Projection Onto Convex Smooth Constraints

Multi-robot task allocation for safe planning against stochastic hazard dynamics

On the Equivalence of Youla, System-Level, and Input-Output Parameterizations

Actuator Placement for Structural Controllability beyond Strong Connectivity and towards Robustness

RRT*-Based Algorithm for Trajectory Planning Considering Probabilistic Weather Forecasts

Informed scenario-based RRT∗ for aircraft trajectory planning under ensemble forecasting of thunderstorms

Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems

Core-Selecting Mechanisms in Electricity Markets

Safe Mission Planning under Dynamical Uncertainties

Minimizing Regret of Bandit Online Optimization in Unconstrained Action Spaces

First Order Methods For Globally Optimal Distributed Controllers Beyond Quadratic Invariance

Safe non-smooth black-box optimization with application to policy search

Learning the Globally Optimal Distributed LQ Regulator

Sparsity Invariance for Convex Design of Distributed Controllers

System-level, Input-output and New Parameterizations of Stabilizing Controllers, and Their Numerical Computation

Distributed Design for Decentralized Control using Chordal Decomposition and ADMM

Actuator Placement under Structural Controllability using Forward and Reverse Greedy Algorithms

Mixed Strategies for Robust Optimization of Unknown Objectives

Learning to Play Sequential Games versus Unknown Opponents

No-Regret Learning from Partially Observed Data in Repeated Auctions

Contextual Games: Multi-Agent Learning with Side Information

Learning Generalized Nash Equilibria in a Class of Convex Games

Unified Approach to Convex Robust Distributed Control Given Arbitrary Information Structures

Performance guarantees for greedy maximization of non-submodular controllability metrics

Using Uncertainty Data in Chance-Constrained Trajectory Planning

Learning Nash Equilibria in Monotone Games

Log Barriers for Safe Non-convex Black-box Optimization

Safe Convex Learning under Uncertain Constraints

Enabling inter-area reserve exchange through stable benefit allocation mechanisms

On Separable Quadratic Lyapunov Functions for Convex Design of Distributed Controllers

An Input–Output Parametrization of Stabilizing Controllers: Amidst Youla and System Level Synthesis

Actuator Placement for Optimizing Network Performance under Controllability Constraints

Nash and Wardrop Equilibria in Aggregative Games With Coupling Constraints

Privacy of Real-Time Pricing in Smart Grid

Strengthening the Group: Aggregated Frequency Reserve Bidding With ADMM

Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature

No-Regret Learning in Unknown Games with Correlated Payoffs

Designing Coalition-Proof Reverse Auctions Over Continuous Goods

Robust aircraft trajectory planning under uncertain convective environments with optimal control and rapidly developing thunderstorms

Exploiting structure of chance constrained programs via submodularity

Minimizing Regret in Unconstrained Online Convex Optimization

Exploiting Weak Supermodularity for Coalition-Proof Mechanisms

Robust Distributed Control Beyond Quadratic Invariance

Game-theoretic models in energy systems and control DTU Summer School 2018 Modern Optimization in Energy Systems‬

Optimizing HVDC Grid Expansion and Control for Enhancing DC Stability

Scalable analysis of linear networked systems via chordal decomposition