PhD Students

Doctoral Fellows

Alexander Immer

My research focuses on probabilistic machine learning and data science. Currently, I am particularly interested in approximate inference for neural networks and biomedical applications. I want to design algorithms that can incorporate prior knowledge, quantify uncertainty, and automatically select the most likely model given data. Especially in the context of neural networks, these problems remain challenging. I have previously worked on methods for time series, e.g., mobility and political data.

Primary Host(s):	Gunnar Rätsch (ETH Zürich)
Exchange Host(s):	Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)

Amir-Hossein Karimi

I am generally interested in human behavior, how intelligence is formed in humans, and how it can be replicated in machines. As a first year PhD student, I am exploring AI methods that are interpretable and explainable, with a focus on probabilistic inference on the organization of entities, or learning compositional and causal generative processes. My research has a broad impact, potentially in three areas: (1) more adoption of machine learning methods in critical social, economic, and public health domains due to the added trust gained from explainable methods; (2) better model selection strategies that point out hazardous practices with the abundance of data, including data leakage of irrelevant factors; (3) state-of-the-art models with improved fidelity/accuracy as we are able to conduct stage-wise learning of abstract objects and concepts and then complex relationships.

Primary Host(s):	Bernhard Schölkopf (Max Planck Institute for Intelligent Systems) Isabel Valera (Saarland University & Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Thomas Hofmann (ETH Zürich)

Andrii Zadaianchuk

My research interests lie in the intersection of unsupervised structured representations learning, dynamics learning and using both for model-based reinforcement learning. I find autonomous learning of environment representations that are modular, independently predictable and controllable as an important step towards efficient and accurate control for many real-life applications.

Primary Host(s):	Georg Martius (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Fanny Yang (ETH Zürich)

Cathrin Elich

My research interests lie in the broad field of computer vision and, more specifically, are currently focused on learning structured scene representations. I'm interested to learn about ways in which humans perceive their environment and how to use these ideas in combination with deep learning methods. Moreover, I want to explore options of combining this work with other tasks like segmentation or 3D reconstruction.

Primary Host(s):	Jörg Stückler (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Marc Pollefeys (ETH Zürich & Microsoft)

Cristina Pinneri

In order to create intelligent machines, we should endow them with features connecting areas like machine learning and optimal control. Reinforcement learning lies at the intersection between these two areas and it will be the focus of my PhD, with a particular interest on model-based approaches and trajectory optimization.

Primary Host(s):	Georg Martius (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Andreas Krause (ETH Zürich)

Despoina Paschalidou

My research interests revolve around Computer Vision and Machine Learning and I am particularly interested in the development of methods capable of describing semantic content.

Primary Host(s):	Andreas Geiger (University of Tübingen & Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Luc Van Gool (ETH Zürich & KU Leuven)

Giambattista Parascandolo

My main research interests are out-of-sample generalization and causality in deep learning.

Primary Host(s):	Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Thomas Hofmann (ETH Zürich)

Hamza Keurti

Generally, I am interested in creating vision systems which understand visual scenes like humans do and which learn to perceive the same way children learn: through embodiment and free interaction (playing) with objects. In particular, my aim is to learn robust and predictive representations from visual scenes with the integration of efferent motor signals, in the absence of tasks. An embodied agent should learn to perceive prior to learning tasks.

Primary Host(s):	Benjamin Grewe (ETH Zürich)
Exchange Host(s):	Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)

Julian Nubert

I am interested in robots that are not only moving in but actively impacting their surroundings. My main field of research lies in the intersection of control, perception, and machine learning, intending to enable mobile robots to perform complex tasks. I am mainly working in the field of construction robotics, specifically on autonomous excavation and manipulation with a walking excavator.

Primary Host(s):	Marco Hutter (ETH Zürich)
Exchange Host(s):	Katherine J. Kuchenbecker (Max Planck Institute for Intelligent Systems)

Kamil Adamczewski

Current neural networks remain large and not fully understood. My research links network compression with model interpretability. This natural connection aims at extracting relevant information from the network while discarding the redundant parameters. This goal of reducing neural networks not only makes models faster, more practical and energy-efficient but also aims to analyze and interpret the relevant features that make up a smaller model. We look at this problem from various perspectives, ranging from probabilistic to game-theoretical approaches. My further interests lie in data generation and differential privacy.

Primary Host(s):	Mijung Park (Max Planck Institute for Intelligent Systems) Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Luc Van Gool (ETH Zürich & KU Leuven)

Mattia Segù

Current state-of-the-art machine learning models often unpredictably fail when dealing with previously unseen settings, proving to be not general and robust enough for a safe deployment in life-critical applications. In the spirit of delivering safe and reliable intelligent systems, my research interests focus on solving the challenges presented by the real world by making artificial intelligence models capable of continuously learning and adapting to previously unknown scenarios.

Primary Host(s):	Fisher Yu (ETH Zürich)
Exchange Host(s):	Bernt Schiele (Max Planck Institute for Informatics & Saarland University)

Max Paulus

I have a broad interest in machine learning, including variational methods, causal inference and probabilistic programming. In the future, I hope to design adaptive machines that leverage prior knowledge to effectively learn in domains where traditional approaches still fail today.

Primary Host(s):	Andreas Krause (ETH Zürich)
Exchange Host(s):	Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)

Maximilian Mordig

After a Bachelor's in Physics and Master's in "Computational Science & Engineering" at EPFL, I worked for Hoffmann-La Roche for roughly two years. My PhD, supervised by Bernhard Schölkopf and Gunnar Rätsch, will focus on causal inference, representation learning and applications to biological datasets. I previously worked on Bayesian optimization, variational inference and Gaussian processes. The beauty of probabilistic modelling thrills me.

Primary Host(s):	Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Gunnar Rätsch (ETH Zürich)

Muhammed Kocabas

I am interested in computer vision and machine learning with a focus on human motion understanding.

Primary Host(s):	Michael J. Black (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Otmar Hilliges (ETH Zürich)

Nadine Rüegg

My research focuses on interaction between humans and their environment, 3D pose and tracking. I hope by combining computer vision and machine learning methods, a holistic understanding of video scenes can be obtained.

Primary Host(s):	Konrad Schindler (ETH Zürich)
Exchange Host(s):	Michael J. Black (Max Planck Institute for Intelligent Systems)

Nicolò Ruggeri

My research interests include, but are not limited to, Probabilistic Learning and Network Science, as well as connected fields. In particular, I aim at understanding how current probabilistic models can be improved upon, both on a representation and training level. I am also fascinated by how different ideas and concepts from within and outside ML interpolate in interesting and novel developments. Therefore, I strive to keep a broader view on theoretical and practical insights originating from different fields.

Primary Host(s):	Caterina De Bacco (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Fanny Yang (ETH Zürich)

Nima Mahkam

My research interests lie in developing flexible and intelligent microrobots as a promising potential approach in medical applications. I am mainly interested in fabricating small-scale mechanisms and characterizing their properties to understand the microscale dynamics better. Analyzing these tiny robots' behavior and identifying their mechanical and biocompatible characteristics are crucial for precisely controlling these micro-mechanisms in tight environments such as the human body. Consequently, my studies aim to explore new design approaches, fabrication techniques, and control principles for intelligent soft small-scale robots, which would have a high impact in healthcare.

Primary Host(s):	Metin Sitti (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Robert Katzschmann (ETH Zürich)

Núria Armengol Urpí

Despite recent advances in robotics, the gap between human and robot skills remains vast. During my PhD I aim to combine the tools from machine learning and control theory in order to advance in the field of autonomous learning for robotics. I try to develop algorithms that provide robots with the ability to efficiently explore new environments and autonomously learn from diverse prior data, so that they can intelligently, reliably and robustly handle the complexities of the real world.

Primary Host(s):	Stelian Coros (ETH Zürich) Otmar Hilliges (ETH Zürich)
Exchange Host(s):	Georg Martius (Max Planck Institute for Intelligent Systems)

Olga Mineeva

I am interested in developing robust and interpretable Machine Learning methods for real-world problems, in particular, that arise in Healthcare and Genomics.

Primary Host(s):	Gunnar Rätsch (ETH Zürich)
Exchange Host(s):	Isabel Valera (Saarland University & Max Planck Institute for Intelligent Systems) Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)

Paul Wrede

My aim is to design microscale robots to revolutionize the treatment and diagnosis of diseases. Besides designing the next generation of smart microrobots I am especially interested in visualizing these tiny man-made machines in-vivo. Consequently, my research interests include microrobotics, bioimaging, and micro/nanotechnologies as well as personalized medicine.

Primary Host(s):	Metin Sitti (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Daniel Razansky (ETH Zürich)

Philippe Wenk

My research focuses on leveraging machine learning methods to model and control time continuous dynamical systems. Inspired by traditional scientific parametric model building, I am working on developing novel strategies for reinforcement learning, system identification and control.

Primary Host(s):	Andreas Krause (ETH Zürich)
Exchange Host(s):	Stefan Bauer (Max Planck Institute for Intelligent Systems) Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)

Sidak Pal Singh

My research focuses on the broad areas of deep learning theory, optimization, and causal representation learning. In particular, I am interested in understanding and answering: (a) why over-parameterized neural networks generalize so well (b) how to incorporate (causal) mechanisms to encourage generalization in the non-iid setting. I also like to utilize tools and perspectives from mathematical areas, such as optimal transport, for approaching problems in machine learning.

Primary Host(s):	Thomas Hofmann (ETH Zürich)
Exchange Host(s):	Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)

Siyeon Jang

I am interested in tiny medical robots that can generate localized electric field stimulation. Since electric fields can affect various biological interactions, such wireless nano/micro-scale robots are expected to be one of the most promising strategies to achieve effective medical applications.

Primary Host(s):	Metin Sitti (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Mehmet Fatih Yanik (ETH Zürich)

Songyou Peng

My general research interest lies in computer vision and machine learning. More specifically, I am interested in how to apply deep learning to 3D vision problems.

Primary Host(s):	Marc Pollefeys (ETH Zürich & Microsoft)
Exchange Host(s):	Andreas Geiger (University of Tübingen & Max Planck Institute for Intelligent Systems)

Timothy Gebhard

Generally, in my research, I am interested in problems at the intersection of machine learning and domain sciences (in particular, astrophysics). More specifically, I want to investigate how we can incorporate and make use of existing scientific domain knowledge about a given problem to build better machine learning models. One specific project that I am currently working on aims to develop new ML-based post-processing algorithms for high-contrast imaging of extrasolar planets.

Primary Host(s):	Bernhard Schölkopf (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Sascha Quanz (ETH Zürich) Thomas Hofmann (ETH Zürich)

Vasileios Choutas

I am interested in modelling the human body, its motion and interaction with objects and scenes, which could then be used to generate new human-like actions and behavior for virtual agents.

Primary Host(s):	Michael J. Black (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Luc Van Gool (ETH Zürich & KU Leuven)

Xu Chen

My research interest lies in computer vision and graphics. Specifically I am interested in 3D deep generative models, with a goal to build learning-based approaches capable of generating photo-realistic simulations of human activity. The resulting data could be useful in the context of training methods for human-centric perception tasks.

Primary Host(s):	Otmar Hilliges (ETH Zürich)
Exchange Host(s):	Michael J. Black (Max Planck Institute for Intelligent Systems) Andreas Geiger (University of Tübingen & Max Planck Institute for Intelligent Systems)

Yao Feng

My primary research is at the intersection between Computer Vision, Computer Graphics and Machine Learning, with a focus on understanding 3-dimensional objects using deep learning technique. Currently, I am especially interested in the modeling and analysis of human faces and bodies.

Primary Host(s):	Michael J. Black (Max Planck Institute for Intelligent Systems)
Exchange Host(s):	Marc Pollefeys (ETH Zürich & Microsoft)

Yufeng Zheng

My general research interest lies in the intersection of computer vision and graphics. More specifically, I’m interested in learning-based 3D modelling and analysis for human-centric applications.

Primary Host(s):	Otmar Hilliges (ETH Zürich)
Exchange Host(s):	Michael J. Black (Max Planck Institute for Intelligent Systems)

Yuntao Ma

Controlling mobile manipulators in difficult environments is challenging and exciting. During my Ph.D., I aim to expand the capability of mobile manipulators with reinforcement learning and demonstrate the results on real machines. Currently, I work on combining control policies for complex tasks.

Primary Host(s):	Marco Hutter (ETH Zürich)
Exchange Host(s):	Georg Martius (Max Planck Institute for Intelligent Systems)

Associated Fellows

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