Megha Khosla

Assistant Professor, Delft University of Technology (TU Delft)


Van Mourik Broekmanweg 6

2628 XE Delft

The Netherlands

I am an Assistant Professor in the Multimedia Computing Group in the Intelligent Systems Department at TU Delft. My primary area of research is machine learning on graph structured data. Specifically, I develop algorithms to enable effective, interpretable, and privacy preserving learning on graphs. Prior to my being a faculty member at TUD, I was a senior research at the L3S Research Centre, and the Leibniz University Hannover. I have also managed several collaborative projects both in Academia and in the industry where I spent a three-year stint after my PhD. I completed my PhD from the Max Planck Institute for Informatics (MPII), in Algorithms and the Complexity group, Saarbruecken, Germany.


May 25, 2022 MuCoMiD: A Multitask graph Convolutional Learning Framework for miRNA-Disease Association Prediction with Ngan Dong and Stefanie Mücke is now accepted for publication in IEEE/ACM Transactions of Computational Biology and Bioinformatics.
Dec 15, 2021 Our paper Membership Inference Attack on Graph Neural Networks together with Emmanuel Iyiola and Wolfgang Nejdl won the best student paper award at IEEE TPS 2021.

selected publications

  1. ZORRO: Valid, Sparse, and Stable Explanations in Graph Neural Networks
    Funke, Thorben, Khosla, Megha, Rathee, Mandeep, and Anand, Avishek
    IEEE Transactions on Knowledge and Data Engineering 2022
  2. A multitask transfer learning framework for the prediction of virus-human protein-protein interactions
    Dong, Thi Ngan, Brogden, Graham, Gerold, Gisa, and Khosla, Megha
    BMC Bioinform. 2021
  3. A Comparative Study for Unsupervised Network Representation Learning
    Khosla, Megha, Setty, Vinay, and Anand, Avishek
    IEEE Trans. Knowl. Data Eng. 2021
  4. Membership Inference Attack on Graph Neural Networks
    Olatunji, Iyiola E., Nejdl, Wolfgang, and Khosla, Megha
    In IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications, (TPS-ISA) 2021
  5. Node Representation Learning for Directed Graphs
    Khosla, Megha, Leonhardt, Jurek, Nejdl, Wolfgang, and Anand, Avishek
    In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part I 2019