Area of Expertise
Medical image computing, neuroimaging and analysis applied in finding subtypes inpsychiatric disorder
Multivariate modelling, Machine Learning, Deep Learning and statistical learning for feature selection, pattern recognition, classification
Transfer Learning Assisted Classification and Detection in psychiatric diseases.
Past Experience
Oct 2019 Present
Postdoctoral Researcher
Ludwig-Maximilian-University Munich
Department of Psychiatry & Psychotherapy
Topic: Multi-scale, multimodal stratification and comorbidity analysis in psychiatric disorders
Apr 2016 Sep 2019
PhD Researcher
Max Planck Institute of Psychiatry, Munich
Research Group Statistical Genetics, Translational Research in Psychiatry
Topic: Multivariate methods for analyzing Combined Multimodal Omics- and multimodal neuroimaging records.
a) Unsupervised clustering method using structural brain imaging data (Voxel-Based Morphometry clustering) to define volume based networks. Automated and purely data driven grey matter parcellation for developing VBM (voxel-based morphometry) based atlas system
b) Mixed model-based clustering to detect the subtypes in the depression data.
c) An unsupervised clustering approach to detect subtypes in the depression using functional MRI datasets.
Nov 2015 Mar 2016
Scientific Researcher
Robert Bosch Krankenhaus, Stuttgart
Neuroimaging Department
Worked as a scientific Researcher in Neuroimaging group in Robert Bosch Krankenhaus, Germany. I developed a framework for task MRI image analysis based on stress study in sports.
Mar 2014 Aug 2014
Student Research Assistant
Max Planck Institute for Bio Cybernetics, Tübingen
Bio Cybernetics
a) Project 1 : Worked as a student research assistant in the topic of “Statistical analysis of netfMRI data” by applying different machine learning and statistical analysis algorithm.
b)Project 2: Worked as a student assistant in 9.4 T MRI scan for developing proper parameter for image registration as well as image segmentation by using MIPAV, SPM, FSL software toolboxes. Learned the MIPAV and LIPSIA environment and tried various data to verify the registration and segmentation results.
Jun 2014 Dec 2014
Master Thesis Student
Max Planck Institute for Bio Cybernetics, Tübingen
Bio Cybernetics
Worked as a master thesis student in the topic- the viability of EEG measurement of in 8 degrees of freedom vehicle simulator by using EEGLAB, ERPLAB and MATLAB programming. My thesis work was related to analyzing mental workload by using signal processing techniques and classifying them using support vector machine classifier and also measuring signal to noise ratio in a motion simulator during different motion conditions and mental workload measuring tasks (auditory oddball task, auditory n-back task)
Nov 2013 May 2014
Student Research Intern
Max Planck Institute for Bio Cybernetics, Tübingen
Bio Cybernetics
Worked as intern student in the topic - the viability of EEG measurement of in 8degrees of freedom vehicle simulator by using auditory oddball experimental task with EEGLAB and MATLAB programming