Emre Aksan

Emre Aksan

PhD student
Advanced Interactive Technologies Lab, ETH Zürich

E-Mail
eaksan@inf.ethz.ch
Address
Universitätstrasse 6, 8092 Zürich, Switzerland
Room
ETH Zurich, Department of Computer Science, CNB, H 102

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, human computer interaction and graphics, focusing mainly perception and synthesis of human activities via generative modeling. I am currently working on deep generative temporal models in the following application domains:

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.


Teaching


Publications

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DeepWriting: Making Digital Ink Editable via Deep Generative Modeling

AuthorsE. Aksan, F. Pece, O. Hilliges
In ProceedingsSIGCHI Conference on Human Factors in Computing Systems, Montréal, Canada, 2018

Honorable Mention Best Paper Award

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Learning Human Motion Models for Long-term Predictions

AuthorsP. Ghosh, J. Song, E. Aksan, O. Hilliges
In Proceedings3D Vision (3DV), 2017 International Conference on, 2017

Best Paper Award

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Guiding InfoGAN with Semi-Supervision

AuthorsA. Spurr, E. Aksan, O. Hilliges
In ProceedingsECML PKDD, Skopje, Macedonia, 2017

Learning Deep Temporal Representations for Brain Decoding

Authors O. Firat, E.Aksan, I. Oztekin, F. T. Yarman Vural
ICML - Medical Imaging Workshop, Lille, France, July. 2015

Modelling the Brain Connectivity for Pattern Analysis

Authors I. Onal, E.Aksan, B. Velioglu, M. Ozay, O. Firat, I. Oztekin, F. T. Yarman Vural
22nd International Conference on Pattern Recognition (ICPR), Stockholm, Sweeden, Aug. 2014

Functional Networks of Anatomic Brain Regions

Authors B. Velioglu, E.Aksan, I. Onal, O. Firat, M. Ozay, F. T. Yarman Vural
13th IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC), London, UK, Aug. 2014

Large Scale Functional Connectivity for Brain Decoding

Authors O. Firat, I. Onal, E.Aksan, B. Velioglu, I. Oztekin, F. T. Yarman Vural
11th IASTED International Conference on Biomedical Engineering (BioMed), Zürich, Switzerland, June. 2014

Theses

An fMRI Segmentation Method Under Markov Random Fields for Brain Decoding — MSc Thesis, METU



Student Projects

A Deep Learning Approach to Human Motion Sequences Infilling, Manuel Kaufmann, 2017, MSc — now PHD in our group

Semi-supervised Information Maximising Generative Adversarial Networks, Adrian Spurr, 2016, MSc — now PHD in our group