Statistics & Machine Learning: Hands on experience in statistical estimation/inference techniques, machine learning algorithms, deep learning methods, time series analysis, knowledge graphs, and explainable AI.
Computational Neuroscience: Proficient in neural decoding, neuroimaging techniques (fMRI, MRI, DTI, EEG), with a focus on neuropsychiatric/neurodegenerative disorders. Experienced in modeling neuronal systems and using neuroimaging software like SPM, FSL, AFNI, PyMVPA, and EEGLAB.
Bioinformatics & Computational Biology: Expertise in multi-omics data analysis, statistical genetics, and GWAS. Skilled in genomic data integration and gene prioritization, aiding in novel therapeutic target discovery.
Network Science: Proficient in analyzing complex systems like the human brain, gene co-expression, and protein interaction networks using graph theory. Skilled in network dynamics, community structure, and hub analysis, with expertise in graph-based libraries including NetworkX, PyTorch Geometric, igraph, and Graphviz.
Optimization & Fuzzy Logic: Operation research in healthcare systems, decision making, linear/non-linear programming, evolutionary algorithms, fuzzy expert systems, fuzzy image processing, fuzzy optimization.
Kargarnovin, S., Karwowski, W., and Farahani, F.V., (2023). Evidence of Chaos in Electroencephalogram Signatures of Human Performance: A Systematic Review. Brain Sciences, 13(5), 813.
Hejazi, S., Karwowski, W., Farahani, F.V., Marek, T., and Hancock, P.A, (2023). Graph-based analysis of brain connectivity in multiple sclerosis using functional MRI: A systematic review. Brain Sciences, 13(2), 246.
Farahani, F.V., Karwowski, W., Esposito, M.D., Betzel, R.F., Douglas, P.K., Bohaterewicz, B., Marek, T. and Fafrowicz, M. (2022). Diurnal variations of resting-state fMRI data: A graph-based analysis. NeuroImage, 256, 119246.
Farahani, F.V., Fiok, K., Lahijanian, B., Karwowski, W., and Douglas, P.K. (2022). Explainable AI: A Review of Applications to Neuroimaging Data. Frontiers in Neuroscience, 16.
Saeidi, M., Karwowski, W., Farahani, F.V., Fiok, K., Hancock, P.A., Sawyer, B.D., Christov-Moore, L. and Douglas, P.K., (2022). Decoding Task-Based fMRI Data with Graph Neural Networks. Brain Sciences, 12(8), p.1094.
Ismail, L., Karwowski, W., Farahani, F.V., Rahman, M., Alhujailli, A., Fernandez-Sumano, R., and Hancock, P.A, (2022). Modeling Brain Functional Connectivity Patterns during an Isometric Arm Force Exertion Task at Different Levels of Perceived Exertion: A Graph Theoretical Approach. Brain Sciences, 12(11), 1575.
Davahli, M.R., Karwowski, W., Fiok, K., Murata, A., Sapkota, N., Farahani, F.V., Al-Juaid, A., Marek, T. and Taiar, R., (2022). The COVID-19 Infection Diffusion in the US and Japan: A Graph-Theoretical Approach. Biology, 11(1), p.125.
Farahani, F.V., Fafrowicz, M., Karwowski, W., Bohaterewicz, B., Sobczak, A.M., Ceglarek, A., Zyrkowska, A., Ostrogorska, M., Sikora-Wachowicz, B., Lewandowska, K. and Oginska, H., (2021). Identifying Diurnal Variability of Brain Connectivity Patterns Using Graph Theory. Brain Sciences, 11(1), p.111.
Saeidi, M., Karwowski, W., Farahani, F.V., Fiok, K., Taiar, R., Hancock, P.A. and Al-Juaid, A., (2021). Neural Decoding of EEG Signals with Machine Learning: A Systematic Review. Brain Sciences, 11(11), p.1525.
Fiok, K., Farahani, F.V., Karwowski, W. and Ahram, T., (2021). Explainable artificial intelligence for education and training. The Journal of Defense Modeling and Simulation, p.15485129211028651.
Sobczak, A. M., Bohaterewicz, B., Fafrowicz, M., ..., Farahani, F.V. & Marek, T. (2021). The Influence of Intraocular Lens Implantation and Alterations in Blue Light Transmittance Level on the Brain Functional Network Architecture Reorganization in Cataract Patients. Brain sciences, 11(11), 1400.
Sobczak, A. M., Bohaterewicz, B., Fafrowicz, M., ..., Farahani, F.V. & Marek, T. (2021). Brain functional network architecture reorganization and alterations of positive and negative affect, experiencing pleasure and daytime sleepiness in cataract patients after intraocular lenses implantation. Brain sciences, 11(10), 1275.
Farahani, F.V., Fafrowicz, M., Karwowski, W., Douglas, P.K., Domagalik, A., Beldzik, E., Oginska, H. and Marek, T., (2019). Effects of chronic sleep restriction on the brain functional network, as revealed by graph theory. Frontiers in Neuroscience, 13, 1087.
Farahani, F.V., Karwowski, W. and Lighthall, N., (2019). Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review. Frontiers in Neuroscience, 13, 585.
Farahani, F.V., Ahmadi, A. and Zarandi, M.H.F., (2018). Hybrid intelligent approach for diagnosis of the lung nodule from CT images using spatial kernelized fuzzy c-means and ensemble learning. Mathematics and Computers in Simulation, 149, pp.48-68.
Mohammadi, H., Farahani, F.V., Noroozi, M. and Lashgari, A., (2017). Green supplier selection by developing a new group decision-making method under type 2 fuzzy uncertainty. The International Journal of Advanced Manufacturing Technology, 93(1-4), pp.1443-1462.
Farahani, F.V., Nebel, M.B., Wager, T.D., and Lindquist, M.A., (2022). Effects of Connectivity Hyperalignment (CHA) on Brain Network Properties: from Coarse-scale to Fine-scale. NeuroImage.
Douglas, P.K., Farahani, F.V., Douglas, D.B., and Bookheimer, S., (2020). Convalescent Blood Treatment for COVID-19: Are Local Donors Enough?. arXiv preprint arXiv:2009.12773.
Douglas, P.K, Farahani, F.V., (2020). On the Similarity of Deep Learning Representations across Didactic and Adversarial Examples. arXiv preprint arXiv:2002.06816. (NeurIPS Workshop, 2019)
Farahani, F.V., Truong, D., Rouhollah, A., Abdel-Azim, G., Whelan, C., Li, S., Molineros, J. “Decoding Major Depressive Disorder Neuroconnectivity: Heterogeneity and Demographic Effects.” Human Brain Mapping Annual Meeting (OHBM), Seoul, South Korea, June 2024.
Ismaila, L.E., Farahani, F.V., Sadowsky, C., Sair, H., Pekar, J., Choe, A.S. “Impact of Spinal Cord Injury (SCI) Level on Cortical Reorganization” International Society for Magnetic Resonance in Medicine (ISMRM), Singapore, May 2024.
Truong, D., Khramtsova, E., Patel, P., Farahani, F.V., Li, Q.S., Chen, G., Vairavan, S., Whelan, C., Sarver, B., Rajagopal, G., Mansi, T., Wittenberg, G., Black, M.H., Li, S., Drevets, W. “Toward precision psychiatry: machine learning-driven patient stratification of major depressive disorder reveals biologically distinct subtypes.” World Congress of Psychiatric Genetics (WCPG), Montreal, Canada, October 2023.
Farahani, F.V., Nebel, M.B., Choe, A.S., Pekar, J.J., Caffo, B., and Lindquist, M. “Head Motion during fMRI Acquisition: A Neurobehavioral Trait.” Human Brain Mapping Annual Meeting (OHBM), Montreal, Canada, July 2023.
Farahani, F.V., Sadowsky, C., Pekar, J.J., Lindquist, M., and Choe, A.S. “Characterization of Cortical Reorganization in Individuals with Chronic Spinal Cord Injury using Mesoscale Graph Measures.” International Society for Magnetic Resonance in Medicine (ISMRM), Toronto, Canada, June 2023.
Farahani, F.V., Lindquist, M., and Wager, T. “Fine-grained Network Analysis using Connectivity-based hyperaligned fMRI data.” Human Brain Mapping Annual Meeting (OHBM), Glasgow, Scotland, June 2022.
Farahani, F.V. and Lindquist, M. “Effect of Connectivity Hyperalignment (CHA) on Global and Local Graph-theoretical Properties.” Human Brain Mapping Annual Meeting (OHBM), Virtual Experience, June 2021.
Dutta, C. N., Christov-Moore, L., Anderson, A., Koch, Z., Kaur, P., Farahani, F.V., and Douglas, P. K. (2020, January). Inter-hemispheric asymmetry patterns in the ADHD brain: a neuroimaging replication study. In 15th International Symposium on Medical Information Processing and Analysis (Vol. 11330, p. 113301C). International Society for Optics and Photonics.
Farahani, F.V., Ahmadi, A. and Zarandi, M.F., (2015, August). Lung nodule diagnosis from CT images based on ensemble learning. In Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2015 IEEE Conference on (pp. 1-7). IEEE.
Farahani, F.V., Zarandi, M.F. and Ahmadi, A., (2015, August). Fuzzy rule based expert system for diagnosis of lung cancer. In Fuzzy Information Processing Society (NAFIPS) held jointly with 2015 5th World Conference on Soft Computing (WConSC), 2015 Annual Conference of the North American (pp. 1-6). IEEE.
Lahijanian, B., Zarandi, M.F. and Farahani, F.V., (2016, October). Proposing a model for operating room scheduling based on fuzzy surgical duration. In Fuzzy Information Processing Society (NAFIPS), 2016 Annual Conference of the North American (pp. 1-5). IEEE [Best Paper].
Lahijanian, B., Zarandi, M.F. and Farahani, F.V., (2016, October). Double coverage ambulance location modeling using fuzzy traveling time. In Fuzzy Information Processing Society (NAFIPS), 2016 Annual Conference of the North American (pp. 1-6). IEEE.
Lahijanian, B., Farahani, F.V. and Zarandi, M.F., (2016, July). A new multiple classifier system for diagnosis of erythemato-squamous diseases based on rough set feature selection. In Fuzzy Systems (FUZZ-IEEE), 2016 IEEE International Conference on (pp. 2309-2316). IEEE.
Douglas, P. K., Farahani, F. V., Anderson, A., & Gilles, J. (2023). Sparse and Data-Driven Methods for Concurrent EEG–fMRI. In EEG-fMRI: Physiological Basis, Technique, and Applications (pp. 727-744). Cham: Springer International Publishing.
Farahani, F. V., & Karwowski, W. (2019). Computational methods for analyzing functional and effective brain network connectivity using fMRI. In Advances in Neuroergonomics and Cognitive Engineering (pp. 101-112). Springer International Publishing.