
Emre Aksan
PhD student
Advanced Interactive Technologies Lab, ETH Zürich
- eaksan@inf.ethz.ch
- Address
- Stampfenbachstrasse 48, 8092 Zürich, Switzerland
- Room
- ETH Zurich, Department of Computer Science, STD, H 27
Biography
I am a PhD student at ETH Zurich, working in the Advanced Interactive Technologies lab with Professor Otmar Hilliges. I received my BSc (2013) and MSc (2015) degrees from Middle East Technical University (METU) in Computer Engineering. Prior to joining ETH, I worked on pattern analysis of functional magnetic resonance imaging at METU.
Research Interests
My research interests lie at the intersection of machine learning, computer vision, and human-computer interaction, with a primary focus on the perception and synthesis of human activities, aiming to digitize humans in various aspects. Technically, I am interested in deriving new machine learning algorithms, particularly generative temporal models to capture human dynamics and generate human-like interactions. My current research focuses on deep generative temporal models with applications in the tasks of 3D motion modeling and prediction, building 3D face avatars, and modeling and synthesis of free-form human actions such as digital representations of drawings and handwritten text.
If you are interested in Semester/Master project in our group, you can check our available projects. If you have your own topic related with my research, you are welcome to contact me.
You can also find me on Twitter, Linkedin, and Google scholar.
Publications
Theses
An fMRI Segmentation Method Under Markov Random Fields for Brain Decoding — MSc Thesis, METU
Academic Activities
Reviewing
- 2022
- CVPR, SIGGRAPH, TMLR, T-PAMI
- 2021
- CVPR, ICCV, ICLR, NeurIPS (Outstanding Reviewer Award)
- 2020
- CVPR, ECCV, ICLR, T-PAMI
- 2019
- ICCV
Student Thesis
- 2020
- MA Doruk Çetin Learning in-the-wild Temporal 3D Pose Estimation from MoCap Data
- 2019
- MA Şahan Ayvaz A Study of Sparse Policy Networks for Deep Reinforcement Learning
- MA Lukas Jendele Learning Functionally Decomposed Hierarchies for Continuous Navigation Tasks
- MA Sami Hamdan Stochastic Temporal Convolutional Networks for Speech Enhancement
- 2018
- MA Andreas Blöchliger Representation Learning for Sketch Suggestions based on the Combination of CNNs and RNNs
- BA Şahan Ayvaz Emergence and Imitation of Locomotion in 2D and 3D Environments
- BA Martin Blapp Evaluation of Human Motion Models
- 2017
- MA Manuel Kaufmann A Deep Learning Approach to Human Motion Sequences Infilling
- MA Adrian Spurr Semi-supervised Information Maximising Generative Adversarial Networks
Teaching
- Machine Perception (D-INFK) — Spring 2020
- Machine Perception (D-INFK) — Spring 2019
- Visual Computing (D-INFK) — Autumn 2018
- Machine Perception (D-INFK) — Spring 2018
- User Interface Engineering (D-INFK) — Spring 2017
- User Interface Engineering (D-INFK) — Spring 2016