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cv
Prabhanjan Mutalik
url text
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Education

KTH Royal Institute of Technology 2016 - 2018

Stockholm, Sweden

PES Institute of Technology 2010 - 2014

Bangalore, India


Publications

Koshy George, Prabhanjan Mutalik.
IEEE Transactions on Systems, Man, and Cybernetics: Systems.
[PDF] [BibTeX] [www]

Koshy George, Prabhanjan Mutalik.
International Joint Conference on Neural Networks.
[PDF] [BibTeX] [www] [repo]

Koshy George, Sachin Prabhu, Prabhanjan Mutalik.
Springer, Cham.
[PDF] [BibTeX] [www]

Prabhanjan Mutalik
Masters Thesis.
[PDF] [BibTeX] [www]


Experience

KTH Royal Institute of Technology 2020 - Present

Research Scientist

PES University 2018 - 2020

Research Associate

Infosys 2014 - 2015

Systems Engineer


Current Projects

In collaboration with Karolinska Institute and National Institute of Malaria Research

In collaboration with KTH Royal Institute of Technology

Metacognition

In collaboration with Center for Intelligent Systems, PES University, Bangalore


Previous Projects

  • Temporal Sequences in the Brain: An investigation into the role of sequential activity in the brain and its effect on behaviour. The project sought to review the existing literature and identify neural sequences using the Tempotron learning rule.
  • Biologically Plausible Learning Algorithms: The project surveys and tests the latest biologically plausible models in deep learning with the aim of finding the optimal model that satisfies the computational requirements simultaneously maintaining fidelity to the biological structure.
  • Neuroevolution Algorithm for Time Series Prediction: The aim of the project was to compare Back-propagation Algorithm and Evolutionary Algorithms in the context of time series prediction.
  • Translation Optimization based on Language Similarity: Machine Translation (a Seq2Seq TensorFlow model) was optimized based on the distance between the languages on the language tree.
  • Symptom Sorter: I have built a symptoms recommendation systems featuring simple probabilistic learning.
  • Metacognitive System for Time Series Prediction: The online prediction model consists of a cognitive element (a single layer feedforward network) and a metacognitive layer that controls the hyperparameters of the network.

Programming Languages

  • Python
  • MATLAB
  • HTML and CSS
  • Java
  • SQL