Reza Abbasi-Asl, PhD
Assistant Professor
Neurology
School of Medicine

More specifically, our research program revolves around the development of interpretable machine learning tools to (1) integrate multi-modal data collected from the brain (and body) in both microscopic and macroscopic resolutions, (2) predict functions of biological systems in different resolutions, and (3) determine the functional differences across neurological disorders. We are a part of the Neuroscape Center and Cognitive Neuroscience division at UCSF and our team is supported through funding from NIH National Institute of Mental Health, NIH National Institute of Aging, Weill Neurohub, Sandler Program for Breakthrough in Biomedical Research, UCSF Innovation Ventures, and Google.

• Interpretable Video-Based Tracking and Quantification of Parkinsonism Clinical Motor States
  medRxiv preprint 2023 D. Deng, J. L. Ostrem, V. Nguyen, D. D. Cummins, J. Sun, A. Pathak, S. Little*, R. Abbasi-Asl*
• Interpretable prototype discovery in deep learning based time series classification
  Integrated Systems: Innovations and Applications, Springer book chapter 2023 Gaurav Ghosal, R. Abbasi-Asl
• Journal of Vision
  Reconstructing visual experience from a large-scale biologically realistic model of mouse primary visual cortex 2023 R. Abbasi-Asl, Y. Chi, H. Yang, K. Dai, A. Arkhipov
• Neurology
  Diurnal Step Count Patterns in Progressive Multiple Sclerosis 2023 D. Navani, V. Block, B. Cree, R. Abbasi-Asl
• The entropic heart: Tracking the psychedelic state via heart rate dynamics
  bioRxiv preprint 2023 F. E. Rosas, P. A. M. Mediano, C. Timmermann, A. I Luppi, D. Candia-Rivera, R. Abbasi-Asl, A. Gazzaley, M. L. Kringelbach, S. D. Muthukumaraswamy, D. Bor, S. Garfinkel, R. Carhart-Harris
• Unsupervised pattern discovery in spatial gene expression atlas reveals mouse brain regions beyond established ontology
  bioRxiv preprint 2023 R. Cahill*, Y. Wang*, Patrick Xian, A. Lee, H. Zeng, B. Yu, B. Tasic, R. Abbasi-Asl
• Machine Learning for Uncovering Biological Insights in Spatial Transcriptomics Data.
  ArXiv 2023 Lee AJ, Cahill R, Abbasi-Asl R
• Editorial: Functional microcircuits in the brain and in artificial intelligent systems.
  Frontiers in computational neuroscience 2023 Lee JH, Choe Y, Ardid S, Abbasi-Asl R, McCarthy M, Hu B
• Compression-enabled interpretability of voxel-wise encoding models
  bioRxiv preprint 2022 F Kamali, AA Suratgar, M Menhaj, R Abbasi-Asl
• Robust Registration of Medical Images in the Presence of Spatially-Varying Noise
  Algorithms 2022 Reza Abbasi-Asl, Aboozar Ghaffari, Emad Fatemizadeh
• Journal of Vision
  A large-scale standardized survey of neural receptive fields in an entire column in mouse V1 2021 R. Abbasi-Asl, A. Muslim, J. Larkin, K. Takasaki, D. Millman, D. Denman, J. Lecoq, A, Arkhipov, N. W Gouwens, J. Waters, R C. Reid, S. EJ de Vries
• Multi-Modal Prototype Learning for Interpretable Multivariable Time Series Classification
  arxiv 2021 Gaurav R Ghosal, Reza Abbasi-Asl
• Structural Compression of Convolutional Neural Networks with Applications in Interpretability.
  Frontiers in big data 2021 Abbasi-Asl R, Yu B
• Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex.
  Neuron 2020 Billeh YN, Cai B, Gratiy SL, Dai K, Iyer R, Gouwens NW, Abbasi-Asl R, Jia X, Siegle JH, Olsen SR, Koch C, Mihalas S, Arkhipov A
• Superficial Bound of the Depth Limit of Two-Photon Imaging in Mouse Brain.
  eNeuro 2020 Takasaki K, Abbasi-Asl R, Waters J
• Definitions, methods, and applications in interpretable machine learning.
  Proceedings of the National Academy of Sciences of the United States of America 2019 Murdoch WJ, Singh C, Kumbier K, Abbasi-Asl R, Yu B
• 3-Photon Calcium Imaging of Deep Cortical Layers for Functional Connectomics
  Optics and the Brain 2019 Kevin Takasaki, Josh Larkin, Reza Abbasi-Asl, Dan Denman, Dan Millman, Saskia de Vries, Marc Takeno, Nuno M da Costa, R Clay Reid, Jack Waters
• Brain-Computer Interface in Virtual Reality
  9th International IEEE EMBS Conference on Neural Engineering (NER) 2019 R. Abbasi-Asl, M. Keshavarzi, D. Y. Chan
• Visual physiology of the layer 4 cortical circuit in silico.
  PLoS computational biology 2018 Arkhipov A, Gouwens NW, Billeh YN, Gratiy S, Iyer R, Wei Z, Xu Z, Abbasi-Asl R, Berg J, Buice M, Cain N, da Costa N, de Vries S, Denman D, Durand S, Feng D, Jarsky T, Lecoq J, Lee B, Li L, Mihalas S, …
• The DeepTune framework for modeling and characterizing neurons in visual cortex area V4
  bioArxiv 2018 Reza Abbasi-Asl, Yuansi Chen, Adam Bloniarz, Michael Oliver, Ben DB Willmore, Jack L Gallant, Bin Yu
• Interpreting Convolutional Neural Networks Through Compression
  NIPS 2017 Symposium on Interpretable Machine Learning 2017 Reza Abbasi-Asl, Bin Yu
• Do retinal ganglion cells project natural scenes to their principal subspace and whiten them?
  IEEE Proceedings of 50th Asilomar Conference on Signals, Systems and Computers 2016 R. Abbasi-Asl, C. Pehlevan, B. Yu and D. B. Chklovskii
• Automatic b-spline image registration using histogram-based landmark extraction
  IEEE-EMBS Conference on Biomedical Engineering and Sciences 2012 Abdollah Ghanbari, Reza Abbasi-Asl, Aboozar Ghaffari, Emad Fatemizadeh
• Estimation of muscle force with emg signals using hammerstein-wiener model
  5th Kuala Lumpur International Conference on Biomedical Engineering 2011 Reza Abbasi-Asl, Rahman Khorsandi, Shahrokh Farzampour, Edmond Zahedi
• Hammerstein-Wiener model: A new approach to the estimation of formal neural information
  Basic and Clinical Neuroscience Reza Abbasi-Asl, Rahman Khorsandi, Bijan Vosooghi-Vahdat