Navid Hakimi

About Navid Hakimi

At the forefront of clinical mental health research, my role at LIBR involves leveraging…

Experience

1. Research Associate

   Laureate Institute For Brain Research

   Nov 2022 — Present · Tulsa, OK, US

   Received NIH Grant for data analysis on COBRE and clinical mental health and imaging datasets; implemented Bayesian modeling and frequentist techniques for big data, including the UK Biobank.· Modeling and simulation of human behavioral data, emphasizing computational processes in decision-making using active inference and reinforcement learning frameworks. · Developed intricate experimental setups integrating multiple data acquisition modalities such as EEG, pupillometry, respiratory signal analysis, and behavioral data. Spearheaded experimental designs targeting clinical populations (Anxiety and Depression) for precise phenotyping and disorder specification via computational modeling.· Computational Task development and programming using Python and Matlab. Organize, manage, and integrate feedback from various PIs and pilot studies.· Drafted and collaborated on IRBs, ensuring ethical procedures and protocols.· Implemented Bayesian modeling and accompanied frequentist techniques for efficient data analysis on big datasets including UK Biobank, both internal and publicly sourced.· Demonstrated experience in harnessing machine learning techniques for predictive analytics.

Education

• University of Toronto

  Doctor of Philosophy (Ph.D.)

  2014 — 2019

• Ryerson University

  Master’s Degree

  2011 — 2014

• Amirkabir University of Technology - Tehran Polytechnic

  Bachelor’s Degree

  2007 — 2011