I am a Postdoctoral Researcher hosted by Jon Tamir in the Chandra Family Department of Electrical and Computer Engineering at UT Austin and Ken-Pin Hwang in the Department of Imaging Physics at MD Anderson Cancer Center. I am interested in the application of signal processing, optimization, and machine learning to address acquisition and reconstruction problems in Magnetic Resonance Imaging.

I previously received my PhD in Electrical Engineering and Computer Science at MIT advised by Elfar Adalsteinsson and Berkin Bilgic in June 2023. I was funded in part by the National Science Foundation Graduate Research Fellowship and the Neuroimaging Training Program Fellowship. I recieved a S.M. in Electrical Engineering and Computer Science from MIT in 2019 and a B.S. in Electrical Engineering from Rice University in 2017.

Yamin Arefeen

yaminarefeen@gmail.com

Research

Journal Publications

  • Zero-DeepSub: Zero-Shot Deep Subspace Reconstruction for Rapid Multiparametric Quantitative MRI Using 3D-QALAS

    Yohan Jun, Yamin Arefeen, Jaejin Cho, Shohei Fujita, Xiaoqing Wang, Ellen Grant, Borjan Gagoski, Camilo Jaimes, Michael Gee, Berkin Bilgic

    Magnetic Resonance in Medicine (2024)

  • Latent Signal Models: Learning Compact Representations of Signal Evolution for Improved Time-Resolved, Multi-contrast MRI

    Yamin Arefeen, Junshen Xu, Molin Zhang, Zijing Dong, Fuyixue Wang, Jacob White, Berkin Bilgic, Elfar Adalsteinsson

    Magnetic Resonance in Medicine (2023)

  • Stochastic-offset-enhanced restricted slice excitation and 180° refocusing designs with spatially non-linear ΔB0 shim array fields

    Molin Zhang, Nicolas Arango, Yamin Arefeen, Georgy Guryev, Jason P. Stockmann, Jacob White, Elfar Adalsteinsson

    Magnetic Resonance in Medicine (2023)

  • Scan Specific Artifact Reduction in K-space (SPARK) Neural Networks Synergize with Physics-based Reconstruction to Accelerate MRI

    Yamin Arefeen, Onur Beker, Jaejin Cho, Heng Yu, Elfar Adalsteinsson, Berkin Bilgic

    Magnetic Resonance in Medicine (2022)

Preprints

  • INFusion: Diffusion Regularized Implicit Neural Representations for 2D and 3D accelerated MRI reconstruction

    Yamin Arefeen, Brett Levac, Zach Stoebner, Jonathan Tamir

    arXiv (2024)

  • A Benchmark of Domain-Adapted Large Language Models for Generating Brief Hospital Course Summaries

    Asad Aali, Dave Van Veen, Yamin Arefeen, Jason Hom, Christian Bluethgen, Eduardo Pontes Reis, Sergios Gatidis, Namuun Clifford, Joseph Daws, Arash Tehrani, Jangwoon Kim, Akshay Chaudhari

    arXiv (2024)

Conference Proceedings

  • Parallel Imaging Reconstruction in Public Datasets Biases Downstream Analysis in Retrospective Sampling Studies

    Evan Frenklak, Yamin Arefeen, Jon Tamir

    To Appear In the proceedings of the International Society for Magnetic Resonance in Medicine (2024)

  • GSURE Denoising enables training of higher quality generative priors for accelerated Multi-Coil MRI Reconstruction

    Asad Aali, Marius Arvinte, Sidharth Kumar, Yamin Arefeen, Jonathan Tamir

    To Appear In the proceedings of the International Society for Magnetic Resonance in Medicine (2024)

  • Improved T1 and T2 mapping in 3D-QALAS using temporal subspaces and flip angle optimization enabled by auto-differentiation

    Yamin Arefeen, Borjan Gagoski, Yohan Jun, Berkin Bilgic, Elfar Adalsteinsson

    In proceedings of the International Society for Magnetic Resonance in Medicine (2023)

  • Zero-Shot Self-Supervised Joint Temporal Image and Sensitivity Map Reconstruction via Linear Latent Space

    Molin Zhang, Junshen Xu, Yamin Arefeen, Elfar Adalsteinsson

    Medical Imaging with Deep Learning (2023)

  • SubZero: Subspace Zero-Shot MRI Reconstruction

    Heng Yu, Yamin Arefeen, Berkin Bilgic

    In proceedings of the International Society for Magnetic Resonance in Medicine (2023)

  • Zero-DeepSub: Zero-Shot Deep Subspace Reconstruction for Multiparametric Quantitative MRI Using QALAS

    Yohan Jun, Yamin Arefeen, Jaejin Cho, Xiaoqing Wang, Michael Gee, Borjan Gagoski, Berkin Bilgic

    In proceedings of the International Society for Magnetic Resonance in Medicine (2023)

  • Learning compact latent representations of signal evolution for improved shuffling reconstruction

    Yamin Arefeen, Junshsen Xu, Molin Zhang, Jacob White, Berkin Bilgic, Elfar Adalsteinsson

    In proceedings of the International Society for Magnetic Resonance in Medicine (2022)

  • Improved acquisition efficiency in T2-weighted fetal MRI with optimized variable flip angles and prospective wave-encoding

    Yamin Arefeen, Borjan Gagoski, Berkin Bilgic, Ellen Grant, Elfar Adalsteinsson

    In proceedings of the International Society for Magnetic Resonance in Medicine (2022)

  • Design of Novel RF Pulse for Fetal MRI Refocusing Trains using Rank Factorization (SLfRank) to Reduce SAR and Improve Image Acquisition Efficiency

    Sebastian Diaz, Yamin Arefeen, Borjan Gagoski, Ellen Grant, Elfar Adalsteinsson

    In proceedings of the International Society for Magnetic Resonance in Medicine (2022)

  • Zero-Shot Self-Supervised Learning for 2D T2-shuffling MRI reconstruction

    Molin Zhang, Junshen Xu, Yamin Arefeen, Elfar Adalsteinsson

    In proceedings of the International Society for Magnetic Resonance in Medicine (2022)

  • Predicting Critical Biogeochemistry of the Southern Ocean for Climate Monitoring

    Ellen Park, Jae Deok Kim, Nadege Aoki, Yumeng Melody Cao, Yamin Arefeen, Matthew Beveridge, David Nicholson, Iddo Drori

    Tackling Climate Change with Machine Learning workshop at NeurIPS (2022)

  • Rapid fetal HASTE imaging using variable flip angles and simultaneous multislice wave-LORAKS

    Yamin Arefeen, Tae Hyung Kim, Justin Haldar, Ellen Grant, Borjan Gagoski, Berkin Bilgic, Elfar Adalsteinsson

    In proceedings of the International Society for Magnetic Resonance in Medicine (2021)

  • Towards Accelerating 3D 1H-MRSI Using Randomly Undersampled Spatial and Spectral Spirals with Low-rank Subspaces

    Yamin Arefeen, Borjan Gagoski, Elfar Adalsteinsson

    In proceedings of the International Society for Magnetic Resonance in Medicine (2021)

  • Extending Scan-specific Artifact Reduction in K-space (SPARK) to Advanced Encoding and Reconstruction Schemes

    Yamin Arefeen, Onur Beker, Heng Yu, Elfar Adalsteinsson, Berkin Bilgic

    In proceedings of the International Society for Magnetic Resonance in Medicine (2021)

  • eRAKI: Fast Robust Artificial neural networks for K-space Interpolation (RAKI) with Coil Combination and Joint Reconstruction

    Heng Yu, Zijing Dong, Yamin Arefeen, Congyu Liao, Kawin Setsompop, Berkin Bilgic

    In proceedings of the International Society for Magnetic Resonance in Medicine (2021)

  • Single-shot T2-weighted Fetal MRI with variable flip angles, full k-space sampling, and nonlinear inversion: towards improved SAR and sharpness

    Yamin Arefeen, Borjan Gagoski, Esra Turk, Ellen Grant, Jacob White, Kawin Setsompop, Elfar Adalsteinsson

    In proceedings of the International Society for Magnetic Resonance in Medicine (2020)

  • Improving cartesian single-shot 2D T2 shuffling and reducing radial streaking artifacts with golden angle radial T2 shuffling

    Yamin Arefeen, Fei Han, Borjan Gagoski, Jacob White, Elfar Adalsteinsson

    In proceedings of the International Society for Magnetic Resonance in Medicine (2020)

  • Refined-subspaces for two iteration single shot T2-Shuffling using dictionary matching

    Yamin Arefeen, Nick Arango, Siddharth Iyer, Borjan Gagoski, Kawin Setsompop, Jacob White, Elfar Adalsteinsson

    In proceedings of the International Society for Magnetic Resonance in Medicine (2019)

  • Real-time, data-driven system to learn parameters for multisite pacemaker beat detection

    Yamin Arefeen, Philip Taffet, Daniel Zdeblick, Jorge Quintero, Greg Harper, Behnaam Aazhang, Joseph Cavallaro, Mehdi Razavi

    In proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers (2017)

Teaching

Thank you to Vasilios Mavroudis for the template