Explainable AI for inflammation

Contact:

Zuse Institut Berlin

Workgroup at Zuse: Explainable AI for Biology
E-Mail:
Sunkara@zib.de
Sunkara@mi.fu-berlin.de

Scientific Career

• Since 2021 Head of Explainable A.I. for Biology (Zuse Institute Berlin)
• 2015-2021 Research Associate at Mathematics of Complex Systems (ZIB) and Biocomputing Group (FU Berlin)
• 2014-2015 Research Associate at the Department of Mathematics and Statistics at University of Adelaide (UOA)
• 2012-2014 Research Associate in Numerical mathematics at the Karlsruhe Institute of Technology (KIT)

Education

• 2004-2008 Bachelors of Mathematics Advanced Honours (First Class), University of Wollongong (Australia)
• 2009-2013 Doctor of Philosophy at the The Australian National University. Title: Analysis and Numerics of the Chemical Master Equation.

Boards and Memberships

Boards

• 2018-2021DFG Centre of Excellence Math+ Board member (postdoc rep)
• 2018-2021 DFG Centre of Excellence Math+ Gender and Diversity Committee

Third Party Funding

• DFG Centre of Excellence Math+ — 2022—2025
• Math Powered Drug Design

Key Publications

Mustafa Chaukair, Christof Schütte, Vikram Sunkara. On the Activation Space of ReLU Equipped Deep Neural Networks.
https://doi.org/10.1016/j.procs.2023.08.200

Vikram Sunkara, Gitta A Heinz, Frederik F Heinrich, Pawel Durek, Ali Mobasheri, Mir- Farzin Mashreghi, Annemarie Lang.
Combining segmental bulk-and single-cell RNA-sequencing to define the chondrocyte gene expression signature in the murine knee joint.
https://doi.org/10.1016/j.joca.2021.03.007

Felix Peppert, Max von Kleist, Christof Schütte, Vikram Sunkara.
On the sufficient condition for solving the Gap-filling problem using Deep Convolutional Neural Networks.
10.1109/TNNLS.2021.3072746

Alexia N. Raharinirina, Felix Peppert, Max von Kleist, Christof Schütte, Vikram Sunkara. Inferring gene regulatory networks from single-cell RNA-seq temporal snapshot data requires higher-order moments
https://doi.org/10.1016/j.patter.2021.100332