Ahmad Farhat

Paris, France. I am a Lebanese-American currently living in Dubai with my wife Reem Khalil and two children, Adam (11) and Luna (1). I worked for Verizon Telecommunications, New York on client server applications automation and database administration. I also taught at the City University of New York. I currently work in data science with a focus on neuroanatomical research. I am a soccer/football fanatic (Liverpool fan)

How to find me?

Dioscuri Centre in Topological Data Analysis
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Publications

(BibTeX)
  1. Reem Khalil, Ahmad Farhat, Pawel Dlotko, Developmental changes in pyramidal cell morphology in multiple visual cortical areas using cluster analysis. Frontiers in Computational Neuroscience (). https://doi.org/10.3389/fncom.2021.667696
  2. Adam Mahdi, Piotr Błaszczyk, Paweł Dłotko, Dario Salvi, Tak-Shing Chan, John Harvey, Davide Gurnari, Yue Wu, Ahmad Farhat, Niklas Hellmer, Alexander Zarebski, Bernie Hogan, Lionel Tarassenko, Oxford COVID-19 Database: a multimodal data repository for better understanding the global impact of COVID-19, Scientific Reports (), https://doi.org/10.1038/s41598-021-88481-4.
  3. Reem Khalil, Sadok Kallel, Ahmad Farhat, Pawel Dlotko, Topological Sholl Descriptors for Neuronal Clustering and Classification. , bioRrxiv. (). bioArxiv
  4. Elsayed, Y., Kanan, S., & Farhat, A., Meteorological patterns, technical validation, and chemical comparison of atmospheric dust depositions and bulk sand in the Arabian Gulf region., Environmental pollution, 269, 116190 (). https://doi.org/10.1016/j.envpol.2020.116190
  5. Adam Mahdi, Piotr Błaszczyk, Paweł Dłotko, Dario Salvi, Tak-Shing Chan, John Harvey, Davide Gurnari, Yue Wu, Ahmad Farhat, Niklas Hellmer, Alexander Zarebski, Bernie Hogan, Lionel Tarassenko, Oxford COVID-19 Database: a multimodal data repository for better understanding the global impact of COVID-19, University of Oxford (), medRxiv.
  6. Habbal, O., Farhat, A., & Khalil, R., A mechanized device for mounting histological tissue sections., Journal of neuroscience methods, 320, 72�78. (). https://doi.org/10.1016/j.jneumeth.2019.03.012

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