CV

Education

PhD in Computer Science, Leibniz University Hannover, 2024
MPhil in Systems Engineering and Engineering Management, Chinese University of Hong Kong, 2020
MSc in Advanced Information Systems, Hong Kong Baptist University, 2015

Professional Experience

March 2024-present: Postdoctoral Researcher, CISPA, Germany
March 2020-February 2024: Research Scientist, L3S Research Center, Germany
May 2016-July 2017: Research Associate, Hong Kong Baptist University, Hong Kong
November 2015-May 2016: Research Associate, Hong Kong Polytechnic University, Hong Kong
December 2013-August 2014: Branch Operations Manager, Lorion-Eyiyemi Ventures Limited, Nigeria
November 2012-October 2013: Volunteer Computer Instructor, National Youth Service Corps, Nigeria

Research Interests

Privacy and security for machine learning
Large language models
Graph neural networks
Explainability and trustworthy AI
Health informatics

Technical Skills

Python
PyTorch and PyTorch Geometric
Data science
SQL
PHP
HTML, CSS, JavaScript, and jQuery

Selected Awards

Best Student Paper, IEEE Trust, Privacy and Security in Intelligent Systems and Applications, 2021
Postgraduate Studentship Scholarship, Chinese University of Hong Kong, 2017-2019
High Distinction Scholarship, Hong Kong Baptist University, 2015
Distinction Scholarship, Hong Kong Baptist University, 2014
Corps Liaison Officer National Award, Nigeria, 2013

Publications

Private graph extraction via feature explanations

Iyiola E. Olatunji, Mandeep Rathee, Thorben Funke, and Megha Khosla. (2023). "Private graph extraction via feature explanations." Proceedings on Privacy Enhancing Technologies (PETS).

Releasing graph neural networks with differential privacy guarantees

Iyiola E. Olatunji, Thorben Funke, and Megha Khosla. (2023). "Releasing graph neural networks with differential privacy guarantees." Transactions on Machine Learning Research (TMLR).

Does Black-box Attribute Inference Attacks on Graph Neural Networks Constitute Privacy Risk?

Iyiola E. Olatunji, Anmar Hizber, Oliver Sihlovec, and Megha Khosla. (2023). "Does Black-box Attribute Inference Attacks on Graph Neural Networks Constitute Privacy Risk?" arXiv.

A review of anonymization for healthcare data

Iyiola E. Olatunji, Jens Rauch, Matthias Katzensteiner, and Megha Khosla. (2022). "A review of anonymization for healthcare data." Big Data.

Membership inference attack on graph neural networks

Iyiola E. Olatunji, Wolfgang Nejdl, and Megha Khosla. (2021). "Membership inference attack on graph neural networks." 2021 Third IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA).

Achieving differential privacy for k-nearest neighbors based outlier detection by data partitioning

Jens Rauch, Iyiola E. Olatunji, and Megha Khosla. (2021). "Achieving differential privacy for k-nearest neighbors based outlier detection by data partitioning." arXiv.

Context-Aware Helpfulness Prediction for Online Product Reviews

Iyiola E. Olatunji, Xin Li, and Wai Lam. (2019). "Context-Aware Helpfulness Prediction for Online Product Reviews." Asia Information Retrieval Symposium.

Video analytics for visual surveillance and applications: An overview and survey

Iyiola E. Olatunji and Chun-Hung Cheng. (2019). "Video analytics for visual surveillance and applications: An overview and survey." Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems.

Mtmr-net: Multi-task deep learning with margin ranking loss for lung nodule analysis

Lihao Liu, Qi Dou, Hao Chen, Iyiola E. Olatunji, Jing Qin, and Pheng-Ann Heng. (2018). "Mtmr-net: Multi-task deep learning with margin ranking loss for lung nodule analysis." Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support (DLMIA 2018).

Iyiola Emmanuel Olatunji

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