I am currently working as a Doctoral Researcher at INSERM and Grenoble Institut des Neurosciences in Grenoble, France.

Previous Positions Held

Artificial Intelligence Research Internship
Grenoble Institut des Neurosciences and INSERM (May - Oct ‘20)

This work was a part of the European Union Horizon 2020 Project.

Developed an unsupervised Spiking Neural Network (SNN) with Spike-Timing-Dependent-Plasticity (STDP) for classification of vocalizations.

• Encoded raw analog audio into discrete spike trains with ‘time-to-first-spike’ encoding.
• Implemented a Low-Threshold-Spiking (LTS) Neuron model to mimic the activity of biological neurons by introducing a temporal dimension to the activation of neurons.
• Implemented the STDP learning rule to enhance learning by updating the synaptic weights of the network.

Research Internship
BrainTech laboratory and Université Grenoble Alpes (May - Oct ‘18)

Analyzed vocalization data and attempted to cluster them with Machine Learning algorithms like Principal Component Analysis (PCA) in order to facilitate mapping with cortical activity; critical for the development of a Brain-Computer Interface (BCI).

• Analyzed Minipig Vocalization Data (MVD) to facilitate mapping between MVD and cortical data.
• Studied spectrograms and labelled audio files of the vocalization data as grunts, squeals and screams using Spike2.
• Performed data cleaning and dimensionality reduction of the data through spectrogram analysis and noise removal.
• Coded functions to successfully implement clustering algorithms like PCA and t-SNE using MATLAB.
• Techniques Used: Spectrogram Analysis, Principal Component Analysis, t-SNE, Independent Component Analysis

Summer School

BrainCom Summer School - Barcelona, Spain. (September 2018)