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Deep Models and Optimization
Embodied Social Interaction
Human Aspects of Machine Learning
Learning and Dynamical Systems
Mechanics for Intelligent Structures
Neuromechanics of Movement
Organizational Leadership and Diversity
Robotic Composites and Compositions
Robust Machine Learning
Safety- and Efficiency- aligned Learning
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Robotics
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Max Planck House Tübingen
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Melis Ilayda Bal
Learning and Dynamical Systems
Doctoral Researcher
72076 Tübingen
+49 7071 601
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Overview
I am a second-year PhD student at the Max Planck Institute for Intelligent Systems, in Tübingen, Germany, at the Learning and Dynamical Systems (LDS) research group and EPFL-LIONS group, co-advised by Dr. Michael Muehlebach and Prof. Volkan Cevher. I am also a doctoral fellow through the Amazon-MPI Science Hub. I hold an M.Sc. in Operations Research and a B.Sc. in Industrial Engineering, with a minor in Computer Engineering, from Middle East Technical University (METU) in Turkey. My research focuses on optimization for machine learning, specifically aimed at developing techniques that enhance the robustness and training efficiency of machine learning models. Previously, I delved into the intersection of algorithmic decision-making and multi-agent systems, examining the intricate interplay between game theory and stochastic optimization. This exploration spanned various contexts, including reinforcement learning, Bayesian optimization, and protein design.
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