Apoorva Vikram Singh

Apoorva Vikram Singh

Masters Student in Neural Information Processing

Eberhard Karls University of Tübingen, Germany


Hello, I’m Apoorva. I am currently a final year master’s student studying Neural Information Processing at the Graduate Training Centre of Neuroscience at the Eberhard Karls University of Tübingen, Germany.

I am interested in understanding the neural computational theories that form the basis of information processing in neuronal networks. To do so, I am interested in analyzing neural data to form hypotheses and building theoretical models to conduct causal investigations of these hypotheses. I like reading about network structure, function, and dynamics studied through the framework of spiking networks, deep learning, and connectomics (and a combination of these).

  • Theoretical Neuroscience
  • Connectomics
  • Deep Learning
  • M.S. in Neural Information Processing, 2021-2023

    Eberhard Karls University of Tübingen, Germany

  • B.Tech in Electrical Engineering, 2017-2021

    National Institute Of Technology, Silchar

  • Higher Secondary Education (ISC), 2014-2017

    City Montessori School, Lucknow


Lab Rotation and Master Thesis
Nov 2022 – Present Tubingen, Germany
  • Working with Prof.Anna Levina (Martius) and Dr. Victor Buendia.
  • Lab Rotation: Theoretically modeled and studied the effect of inhomogeneity on scaling in Branching Networks
  • Master Thesis: Effect of cortical feedback on timescales in dLGN in mice
Essay Rotation
Sep 2022 – Nov 2022 Tubingen, Germany
  • Supervised by Dr. Richard Gao.
  • Essay on “Criticality in Neuroscience: What do we know till now and Why do we care?”
Research Assistant
May 2022 – Apr 2023 Tubingen, Germany
  • Supervised by Dr. Charley M Wu.
  • Established VR lab for developing behavioural experiments.
  • Worked on Unity to build a Hide and Seek game to study the theory of mind.
Student Developer
Jun 2021 – Aug 2021 Rhode Island, U.S.A
  • Worked on the project Equivariant Neural Networks for Dark Matter Morphology with Strong Gravitational Lensing under Prof. Sergei Gleyzer and Michael Toomey.
Research Intern
Dec 2020 – Dec 2021 Rhode Island, U.S.A
Guest Researcher
Jun 2020 – Feb 2021 Magdeburg, Germany
  • Working under Prof. Peter Benner and Dr. Pawan Goyal in the research group Computational Methods in Systems and Control Theory.
  • Working on methods of inverse imaging problems using deep learning.
Undergraduate Research Intern
May 2019 – Jul 2019 Hyderabad, India
  • Worked in Artificial Intelligence (AI) Laboratory, UoH, under Prof. Atul Negi, School of Computer and Information Sciences.
  • Worked on developing efficient drug repositioning techniques by using ontological medical data and medical text corpus.
Machine Learning Engineer
Dec 2017 – Aug 2018 Silchar, India
  • Worked to develop a deep learning based engine that analysed the client’s monthly health data to anticipate any health risks.
  • The data was collected through wearables and uploaded on monthly basis to a cloud server.

Recent Publications

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(2021). DynG2G: An Efficient Stochastic Graph Embedding Method for Temporal Graphs. arXiv preprint arXiv:2109.13441.

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(2020). A Hybrid Classification Approach using Topic Modeling and Graph Convolution Networks. 2020 International Conference on Computational Performance Evaluation (ComPE).

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(2020). Debunking Fake News by Leveraging Speaker Credibility and BERT Based Model. IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'20).

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(2020). Predictive approaches for the UNIX command line: curating and exploiting domain knowledge in semantics deficit data. Multimedia Tools and Applications.

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(2020). Seq2Seq and Joint Learning Based Unix Command Line Prediction System. arXiv preprint arXiv:2006.11558.

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