Profile

Zeynep Akata is a professor of Computer Science (W3) within the Cluster of Excellence Machine Learning at the University of Tübingen. After completing her PhD at the INRIA Rhone Alpes with Prof Cordelia Schmid (2014), she worked as a post-doctoral researcher at the Max Planck Institute for Informatics with Prof Bernt Schiele (2014-17) and at University of California Berkeley with Prof Trevor Darrell (2016-17). Before moving to Tübingen in October 2019, she was an assistant professor at the University of Amsterdam with Prof Max Welling (2017-19). She received a Lise-Meitner Award for Excellent Women in Computer Science from Max Planck Society in 2014, a young scientist honour from the Werner-von-Siemens-Ring foundation in 2019, an ERC-2019 Starting Grant from the European Commission, The DAGM German Pattern Recognition Award in 2021 and The ECVA Young Researcher Award in 2022. Her research interests include multimodal learning and explainable AI.

Experience

• Professor of Computer Science, University of Tübingen, 2019 – Now
• Senior Researcher at Max Planck Institute for Informatics, 2017 – Now
• Assistant Professor at University of Amsterdam, 2017 – 2019
• Visiting Researcher at UC Berkeley, 2016-2017
• Post Doctoral Researcher at Max Planck Institute for Informatics, 2014-2017

Education

• PhD: University of Grenoble, France, 2014
• MSc: RWTH Aachen, Germany, 2010
• BSc: Trakya University, Turkey, 2008

External Activities

• Program Chair:
  • GCPR-DAGM 2020, IEEE CVPR 2024, IEEE ICCV 2026​
• Area Chair:
  • WACV 2016, IJCAI 2018, ECCV 2018, BMVC 2019, CVPR 2019-2023, ICCV 2019-2023, ICML 2020-2023, ECCV 2020-2022, ICLR 2021-2023
• Associate Editor:
  • Pattern Recognition Journal (Appointment between Aug 2018 - Aug 2020)
  • Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (2020 - Now)
• Reviewer:
  • TPAMI 2015-2017, IJCV 2015-2017
  • ICCV 2015-2017, ECCV 2016, ACCV 2016, CVPR 2015-2018, EMNLP 2018, NIPS 2016-2018, AISTATS 2017, AAAI 2018, ICLR 2018, ICML 2018-2019
• Organization Committees and Invited Talks:
  • Gender Diversity in STEM fields, Springboard training program, 2015
  • Tutorial on Embeddings and Metric Learning, GCPR 2016
  • Tutorial on Zero-Shot Learning, CVPR 2017
  • CD-Make 2018, Cross Domain Conference on Machine Learning and Knowledge Extraction
  • WiCV@ECCV 2018, Women in Computer Vision Workshop
  • Interpretable Machine Learning for Computer Vision Tutorial at CVPR 2020, Invited Speaker
  • Fair, Data-Efficient and Trusted Computer Vision Workshop at CVPR 2020, Invited Speaker
  • Human in the Loop Learning (HILL) Workshop at ICML 2020, Invited Speaker
  • XXAI Workshop at ICML 2020, Invited Speaker
  • Women in Computer Vision (WiCV) Workshop at ECCV 2020, Invited Speaker
  • Task-CV Workshop at ECCV 2020, Invited Speaker
  • RIIAA 2020 - International Meeting on Artificial Intelligence, Invited Speaker
  • Sketching for Human Expressivity (SHE) Workshop at ICCV 2021, Co-organizer
  • Human in the Loop Learning (HILL) Workshop at ICML 2021, Co-organizer
  • Natural XAI: Natural Language Explanations Tutorial at ICML 2021, Co-organizer and Speaker
  • ImageNet: The Past, The Present and The Future Workshop at NeurIPS 2021, Co-organizer

Awards and Funding

• Lise-Meitner Award for Excellent Women in Computer Science from Max Planck Society in 2014
• Explainable Artificial Intelligence (XAI) grant from DARPA in 2017
• ERC Starting Grant from the European Research Council in 2019
• Young Investigator honour from Werner-von-Siemens-Ring Foundation in 2019
• DAGM German Pattern Recognition Award in 2021
• ECVA Young Researcher Award in 2022

Publications

2022

• Learning Graph Embeddings for Open World Compositional Zero-shot Learning. Massimiliano Mancini, Muhammed Ferjad Naeem, Yongqin Xian, Zeynep Akata. IEEE Transactions on Pattern Recognition and Machine Intelligence, TPAMI 2022
• KG-SP: Knowledge Guided Simple Primitives for Open World Compositional Zero-Shot Learning. Shyamgopal Karthik, Massimilano Mancini, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2022
• Integrating Language Guidance into Vision-based Deep Metric Learning. Karsten Roth, Oriol Vinyals, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2022
• Non-isotropy Regularization for Proxy-based DML. Karsten Roth, Oriol Vinyals, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2022
• Large Loss Matters in Weakly Supervised Multi-Label Classification. Youngwoo Kim, Jae Myung Kim, Zeynep Akata, Jungwoo Lee. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2022
• Audio-visual Generalised Zero-shot Learning with Cross-modal Attention and Language. Otniel-Bogdan Mercea, Lukas Riesch, Almut Sophia Koepke, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2022
• VGSE: Visually-Grounded Semantic Embeddings for Zero-Shot Learning. Wenjia Xu, Yongqin Xian, Jiuniu Wang, Bernt Schiele, Zeynep Akata, IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2022

2021

• Robustness via Uncertainty-aware Cycle Consistency. Uddeshya Upadhyay, Yanbei Chen, Zeynep Akata. Neural Information Processing Systems, NeurIPS 2021
• Fine-Grained Zero-Shot Learning with DNA as Side Information. Sarkhan Badirli, Zeynep Akata, George Mohler, Christine Picard, Murat Dundar. Neural Information Processing Systems, NeurIPS 2021
• Human Attention in Fine-grained Classification. Yao Rong, Wenjia Xu, Zeynep Akata, Enkelejda Kasneci. British Machine Vision Conference, BMVC 2021
• Prototype-based Incremental Few-Shot Segmentation. Fabio Cermelli, Massimiliano Mancini, Yongqin Xian, Zeynep Akata, Barbara Caputo. British Machine Vision Conference, BMVC 2021
• Conditional De-Identification of 3D Magnetic Resonance Images. Lennart Van der Goten, Tobias Hepp, Zeynep Akata, Kevin Smith. British Machine Vision Conference, BMVC 2021
• Keep CALM and Improve Visual Feature Attribution. Jae Myung Kim, Junsuk Choe, Zeynep Akata, Seong Joon Oh. IEEE International Conference of Computer Vision, ICCV 2021
• e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks. Maxime Kayser, Oana-Maria Camburu, Leonard Salewski, Cornelius Emde, Virginie Do, Zeynep Akata, Thomas Lukasiewicz. IEEE International Conference of Computer Vision, ICCV 2021
• Uncertainty-Guided Progressive GANs for Medical Image Translation. Uddeshya Uppadhyay, Yanbei Chen, Tobias Hepp, Sergios Gatidis, Zeynep Akata. Medical Image Computing and Computer Assisted Interventions, MICCAI 2021
• Learning Decision Trees Recurrently Through Communication. Stephan Alaniz, Diego Marcos, Bernt Schiele, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021
• Learning Graph Embeddings for Compositional Zero-shot Learning. Mohammad Ferjad Naeem, Yongqin Xian, Federico Tombari, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021
• Distilling Audio-Visual Knowledge by Compositional Contrastive Learning. Yanbei Chen, Yongqin Xian, Almut Sophia Koepke, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021
• Open World Compositional Zero-Shot Learning. Massimiliano Mancini, Mohammad Ferjad Naeem, Yongqin Xian, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021

2020

• Attribute Prototype Network for Zero-Shot Learning. Wenjia Xu, Yongqin Xian, Jiuniu Wang, Bernt Schiele, Zeynep Akata. Neural Information Processing Systems (NeurIPS) 2020
• Semantically Tied Paired Cycle Consistency for Any-Shot Sketch-based Image Retrieval. Anjan Dutta, Zeynep Akata. International Journal of Computer Vision (IJCV), accepted in June 2020
• Towards Recognizing Unseen Categories in Unseen Domains. Massimiliano Mancini, Zeynep Akata, Elisa Ricci, Barbara Caputo. European Conference of Computer Vision (ECCV) 2020
• Learning Robust Representations via Multi-View Information Bottleneck. Marco Federici, Anjan Dutta, Patrick Forre, Nate Kushmann, Zeynep Akata. International Conference on Learning Representations (ICLR) 2020
• Evaluating Weakly Supervised Object Localization Methods Right. Junsuk Choe, Seong Joon Oh, Seungho Lee, Sanghyuk Chun, Zeynep Akata, Hyunjung Shim. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2020
• Manipulating Attributes of Natural Scenes via Hallucination. Levent Karacan, Zeynep Akata, Aykut Erdem, Erkut Erdem. ACM SIGGRAPH 2020 (invited paper)

2019

• Modeling Conceptual Understanding in Image Reference Games. Rodolfo Corona, Stephan Alaniz, Zeynep Akata. Neural Information Processing Systems, NeurIPS 2019 (Spotlight)
• Combining Generative and Discriminative Models for Hybrid Inference. Victor Garcia Satorras, Zeynep Akata, Max Welling. Neural Information Processing Systems, NeurIPS 2019 (Spotlight)
• Manipulating Attributes of Natural Scenes via Hallucination. Levent Karacan, Zeynep Akata, Aykut Erdem, Erkut Erdem. ACM Transactions on Graphics, TOG 2019 (full paper)
• Semantically Tied Paired Cycle Consistency for Zero-Shot Sketch-based Image Retrieval. Anjan Dutta, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019
• f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning. Yongqin Xian, Saurabh Sharma, Bernt Schiele, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019
• Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders. Edgar Schoenfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019
• SPNet: Semantic Projection Network for Zero-Label and Few-Label Semantic Segmentation. Yongqin Xian, Subharata Choudhury, Yang He, Bernt Schiele, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019
• Zero-Shot Learning – A Comprehensive Evaluation of the Good, the Bad and the Ugly. Yongqin Xian, Christoph Lampert, Bernt Schiele, Zeynep Akata. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019

2018

• Grounding Visual Explanations. Lisa Anne Hendricks, Ronghang Hu, Trevor Darrell, Zeynep Akata. European Conference of Computer Vision, ECCV 2018
• Textual Explanations for Self-Driving Vehicles. Jinkyu Kim, Anna Rohrbach, Trevor Darrell, John Canny, Zeynep Akata. European Conference of Computer Vision, ECCV 2018
• Multimodal Explanations: Justifying Decisions and Pointing to the Evidence. Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata, Anna Rohrbach, Bernt Schiele, Trevor Darrell, Marcus Rohrbach. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018 (Spotlight Presentation)
• Feature Generating Networks for Zero-Shot Learning. Yongqin Xian, Tobias Lorenz, Bernt Schiele, Zeynep Akata. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2018

2017

• Gaze Embeddings for Zero-Shot Image Classification. Nour Karessli, Zeynep Akata, Bernt Schiele, Andreas Bulling. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 (Spotlight Presentation)
• Zero-Shot Learning – The Good, the Bad and the Ugly. Yongqin Xian, Bernt Schiele, Zeynep Akata .IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017
• Exploiting saliency for object segmentation from image level labels. Seong Joon Oh, Rodrigo Benenson, Anna Khoreva, Zeynep Akata, Mario Fritz, Bernt Schiele. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017

2016

• Learning What and Where to Draw. Scott Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele and Honglak Lee. Neural Information Processing Systems, NIPS 2016 (Oral Presentation)
• Generating Visual Explanations. Lisa Hendricks, Zeynep Akata, Marcus Rohrbach, Jeff Donahue, Bernt Schiele and Trevor Darrell. European Conference of Computer Vision, ECCV 2016
• Generative Adversarial Text to Image Synthesis. Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Honglak Lee and Bernt Schiele. International Conference of Machine Learning, ICML 2016 (Oral Presentation)
• Learning Deep Representations of Fine-Grained Visual Descriptions. Scott Reed, Zeynep Akata, Honglak Lee and Bernt Schiele. IEEE Conference of Computer Vision and Patter Recognition, CVPR 2016 (Spotlight Presentation)
• Multi-Cue Zero-Shot Learning with Strong Supervision. Zeynep Akata, Mateusz Malinowski, Mario Fritz and Bernt Schiele. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 (Spotlight Presentation)
• Latent Embeddings for Zero-Shot Classification. Yongqin Xian, Zeynep Akata, Gaurav Sharma, Quynh Nguyen, Matthias Hein and Bernt Schiele. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 (Spotlight Presentation)
• Label Embeddings for Image Classification. Zeynep Akata, Florent Perronnin, Zaid Harchaoui, Cordelia Schmid. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol:38, No:7, July 2016

2015 and Earlier

• Evaluation of Output Embeddings for Image Classification. Zeynep Akata, Scott Reed, Daniel Walter, Honglak Lee and Bernt Schiele. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
• Label-Embedding for Attribute-Based Classification. Zeynep Akata, Florent Perronnin, Zaid Harchaoui and Cordelia Schmid. IEEE Computer Vision and Pattern Recognition (CVPR) 2013
• Good Practice in Large-Scale Learning for Image Classification. Zeynep Akata, Florent Perronnin, Zaid Harchaoui and Cordelia Schmid. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014

Teaching

• Leren (Introduction to Machine Learning), 2017 (BSc AI, Y2, P2)
• Leren (Introduction to Machine Learning), 2018 (BSc AI, Y2, P2)
• Philosophy of AI (Guest Lecture), March 2018
• Computer Vision 2 (Guest Lecture), May 2018
• Back2Basic 2018, Annual Computer Science Event, Amsterdam, Invited Speaker
• DSSV 2018, Conference on Data Science, Statistics and Visualization, Invited speaker
• BMVC 2018, British Machine Vision Conference, Invited Speaker
• Advanced topics in Explainable Machine Learning, WS 2019/2020 (MSc of CS, ML, MI)
• TUM-AI Lecture Series 2021, Invited Speaker
• SIKS-AI Lecture Series 2021, Invited Speaker
• Advanced topics in Explainable Machine Learning, WS 2020/2021 (MSc of CS, ML, MI, CogSci)
• Learning with Limited Labeled Data, WS 2020/2021 (MSc of CS, ML, MI, CogSci)

PhD Students

• 2021-Now Shyamgopal Karthik @ University of Tübingen (with Matthias Bethge)
• 2021-Now Jae Myung Kim @ University of Tübingen and INRIA (ELLIS PhD with Cordelia Schmid)
• 2021-Now Karsten Roth @ University of Tübingen and Deepmind (ELLIS PhD with Oriol Vinyals)
• 2021-Now Anders Christensen @ Denmark Technical University and University of Tübingen (co-supervision, ELLIS PhD with Ole Winther)
• 2021-Now Uddeshya Upadhyay @ University of Tübingen (with Sergios Gatidis)
• 2021-Now Otniel Mercea @ University of Tübingen (with Andreas Geiger)
• 2020-Now Thomas Hummel @ University of Tübingen
• 2020-Now Leonard Salewski @ University of Tübingen (with Hendrik Lensch)
• 2019-Now Lennart van Goten @ KTH Stockholm (co-supervision, with Kevin Smith)
• 2017-Now Stephan Alaniz @ University of Tübingen and Max Planck Institute for Informatics
• 2016-2020 Yongqin Xian @ Max Planck Institute for Informatics (with Bernt Schiele)
• 2018-2019 Marco Federici @ University of Amsterdam (with Nate Kushman, Patrick Forre)
• 2017-2019 Victor Garcia @ University of Amsterdam (with Prof. Max Welling)
• 2017-2019 Sadaf Gulshad @ University of Amsterdam (with Prof. Arnold Smeulders)
• 2018-2019 Maartje ter Hoeve @ University of Amsterdam (with Prof. Maarten de Rijke)
• 2018-2019 Rodolfo Corona @ UC Berkeley (with Prof. Trevor Darrell)