General Lab Information

Yuewei Lin

Senior Computational Scientist, Comput. Sci. Mach. Learning, Computational Science Initiative

Yuewei Lin

Brookhaven National Laboratory

Computational Science Initiative
Bldg. 725
P.O. Box 5000
Upton, NY 11973-5000

(631) 344-8704
ywlin@bnl.gov

Expertise | Education | Appointments | Publications | Awards


Expertise

  • Computer vision: image/video analysis
  • Machine learning/computer vision applications in scientific data analysis
  • Security and safety of machine learning

Education

  • Ph.D., University of South Carolina, Columbia, S.C.
  • M.E., Chongqing University, China
  • B.S., Sichuan University, China

Professional Appointments

  • Senior Computational Scientist, Brookhaven National Laboratory. 2024 — Present.
  • Research Associate Professor,  Stony Brook University. 2019 — Present.
  • Computational Scientist, Brookhaven National Laboratory. 2020 — 2023.
  • Associate Computational Scientist, Brookhaven National Laboratory. 2018 — 2020.
  • Assistant Computational Scientist, Brookhaven National Laboratory. 2016 — 2018.

Selected Publications

  • Kwon J, Kim S, Lin Y, et al (2024) AesFA: An Aesthetic Feature-Aware Arbitrary Neural Style Transfer. Proceedings of the AAAI Conference on Artificial Intelligence 38:13310–13319. https://doi.org/10.1609/aaai.v38i12.29232
  • Wang H, Deng Y, Yoo S, Lin Y (2024) Exploring Robust Features for Improving Adversarial Robustness. IEEE Transactions on Cybernetics 1–11. https://doi.org/10.1109/tcyb.2024.3380437
  • Lin, Z., Zhang, X., Nandi, P. et al (2024) Correlative single-cell hard X-ray computed tomography and X-ray fluorescence imaging. Communications Biology 7, 280.
  • Wei Y, Chen AX, Lin Y, et al (2024) Allosteric regulation in SARS-CoV-2 spike protein. Physical Chemistry Chemical Physics 26:6582–6589.
  • Yu X, Wu L, Lin Y, et al (2024) Ultrafast Bragg coherent diffraction imaging of epitaxial thin films using deep complex-valued neural networks. npj Computational Materials 10:. https://doi.org/10.1038/s41524-024-01208-7
  • Sun H, Ma J, Guo Q, et al (2023) Coarse-to-fine Task-driven Inpainting for Geoscience Images. IEEE Transactions on Circuits and Systems for Video Technology 1–1. https://doi.org/10.1109/tcsvt.2023.3276719
  • Zheng S, Wei Y, Lin Y, Wei T (2023) Graphic contrastive learning analyses of discontinuous molecular dynamics simulations: Study of protein folding upon adsorption. Applied Physics Letters 122:. https://doi.org/10.1063/5.0157933
  • Wang H, Sreejith S, Lin Y, et al (2023) Neural Network Based Point Spread Function Deconvolution For Astronomical Applications. The Open Journal of Astrophysics 6:. https://doi.org/10.21105/astro.2210.01666
  • Liu X, Lin Y, Yang Q, Fan H (2023) Transferable Adversarial Attack on 3D Object Tracking in Point Cloud. Lecture Notes in Computer Science 446–458. https://doi.org/10.1007/978-3-031-27818-1_37
  • Wang H, Sreejith S, Slosar A, et al (2022) Galaxy deblending using residual dense neural networks. Physical Review D 106:. https://doi.org/10.1103/physrevd.106.063023
  • Lian R, Huang B, Wang L, et al (2022) End-to-end orientation estimation from 2D cryo-EM images. Acta Crystallographica Section D Structural Biology 78:174–186. https://doi.org/10.1107/s2059798321011761
  • Wang H, Deng Y, Yoo S, et al (2021) AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). https://doi.org/10.1109/iccv48922.2021.00756
  • Fan H, Miththanthaya HA, Harshit H, et al (2021) Transparent Object Tracking Benchmark. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). https://doi.org/10.1109/iccv48922.2021.01056
  • Liu P, Lin Y, Meng Z, Lu L, Deng W, Zhou JT, Yang Y (2021) Point Adversarial Self-Mining: A Simple Method for Facial Expression Recognition. IEEE Transactions on Cybernetics 1–12. doi: 10.1109/tcyb.2021.3085744
  • Sun H, Lin Y, Zou Q, et al (2021) Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy Environments. 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). https://doi.org/10.1109/iccvw54120.2021.00085
  • Fan H, Yang F, Chu P, Lin Y, Yuan L, Ling H (2021) TracKlinic: Diagnosis of Challenge Factors in Visual Tracking. 2021 IEEE Winter Conference on Applications of Computer Vision (WACV). doi: 10.1109/wacv48630.2021.00101
  • Lin Y, Topsakal M, Timoshenko J, Lu D, Yoo S, Frenkel AI (2020) Machine-Learning Assisted Structure Determination of Metallic Nanoparticles: A Benchmark. Handbook on Big Data and Machine Learning in the Physical Sciences 127–140. doi: 10.1142/9789811204579_0007
  • Zhang Z, Zou Q, Lin Y, Chen L, Wang S (2020) Improved Deep Hashing With Soft Pairwise Similarity for Multi-Label Image Retrieval. IEEE Transactions on Multimedia 22:540–553. doi: 10.1109/tmm.2019.2929957
  • Li H, Lin Y, Mueller K, Xu W (2020) Interpreting Galaxy Deblender GAN from the Discriminator's Perspective. Lecture Notes in Computer Science 239–250. doi: 10.1007/978-3-030-64559-5_18
  • Song S, Yu H, Miao Z, Zhang Q, Lin Y, Wang S (2019) Domain Adaptation for Convolutional Neural Networks-Based Remote Sensing Scene Classification. IEEE Geoscience and Remote Sensing Letters 16:1324–1328. doi: 10.1109/lgrs.2019.2896411
  • Li X, Lin Y, Liu Q, McSweeney S, Yoo S (2019) Picking Particles in Cryo-EM Micrographs without Knowing the Particle Size. 2019 New York Scientific Data Summit (NYSDS). doi: 10.1109/nysds.2019.8909792
  • Zakharov DN, Tkachenko A, Qu X, Wang H, Lin Y, Horwath JP, Yoo S, Stach EA (2019) Characterization and Modeling of Coarsening Mechanisms in Supported Nanoparticle Ensemble. Microscopy and Microanalysis 25:1420–1421. doi: 10.1017/s1431927619007839
  • Zakharov DN, Lin Y, Megret R, Yoo S, Voorhees P, Horwath JP, Stach EA (2018) Towards Real Time Quantitative Analysis of Supported Nanoparticle Ensemble Evolution Investigated by Environmental TEM. Microscopy and Microanalysis 24:540–541. doi: 10.1017/s1431927618003197
  • Timoshenko J, Lu D, Lin Y, Frenkel AI (2017) Supervised Machine-Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles. The Journal of Physical Chemistry Letters 8:5091–5098. doi: 10.1021/acs.jpclett.7b02364
  • Lin Y, Chen J, Cao Y, Zhou Y, Zhang L, Tang YY, Wang S (2017) Cross-Domain Recognition by Identifying Joint Subspaces of Source Domain and Target Domain. IEEE Transactions on Cybernetics 47:1090–1101. doi: 10.1109/tcyb.2016.2538199
  • Lin Y, Tong Y, Cao Y, Zhou Y, Wang S (2017) Visual-Attention-Based Background Modeling for Detecting Infrequently Moving Objects. IEEE Transactions on Circuits and Systems for Video Technology 27:1208–1221. doi: 10.1109/tcsvt.2016.2527258
  • Zheng K, Fan X, Lin Y, Guo H, Yu H, Guo D, Wang S (2017) Learning View-Invariant Features for Person Identification in Temporally Synchronized Videos Taken by Wearable Cameras. 2017 IEEE International Conference on Computer Vision (ICCV). doi: 10.1109/iccv.2017.311
  • Lin Y, Zakharov D, Megret R, Yoo S, Stach E (2017) Near real time ETEM streaming video analysis. 2017 New York Scientific Data Summit (NYSDS). doi: 10.1109/nysds.2017.8085054
  • Rodman J, Lin Y, Sprouster D, Ecker L, Yoo S (2017) Automated X-ray diffraction of irradiated materials. 2017 New York Scientific Data Summit (NYSDS). doi: 10.1109/nysds.2017.8085053
  • Cisek D, Mahajan M, Dale J, Pepper S, Lin Y, Yoo S (2017) A transfer learning approach to parking lot classification in aerial imagery. 2017 New York Scientific Data Summit (NYSDS). doi: 10.1109/nysds.2017.8085049
  • Yu H, Zhou Y, Simmons J, Przybyla CP, Lin Y, Fan X, Mi Y, Wang S (2016) Groupwise Tracking of Crowded Similar-Appearance Targets from Low-Continuity Image Sequences. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). doi: 10.1109/cvpr.2016.109
  • Lin Y, Abdelfatah K, Zhou Y, Fan X, Yu H, Qian H, Wang S (2015) Co-Interest Person Detection from Multiple Wearable Camera Videos. 2015 IEEE International Conference on Computer Vision (ICCV). doi: 10.1109/iccv.2015.503
  • Xiaochuan Fan, Kang Zheng, Yuewei Lin, Wang S (2015) Combining local appearance and holistic view: Dual-Source Deep Neural Networks for human pose estimation. 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). doi: 10.1109/cvpr.2015.7298740
  • Lin Y, Chen J, Cao Y, Zhou Y, Zhang L, Wang S (2015) Cross-domain recognition by identifying compact joint subspaces. 2015 IEEE International Conference on Image Processing (ICIP). doi: 10.1109/icip.2015.7351447
  • Chen J, Yan Tang Y, Philip Chen CL, Fang B, Shang Z, Lin Y (2015) NNMap: A method to construct a good embedding for nearest neighbor classification. Neurocomputing 152:97–108. doi: 10.1016/j.neucom.2014.11.014
  • Chen J, Tang YY, Chen CLP, Lin Y (2014) Dual Fuzzy Hypergraph Regularized Multi-label Learning for Protein Subcellular Location Prediction. 2014 22nd International Conference on Pattern Recognition. doi: 10.1109/icpr.2014.97
  • Chen J, Tang YY, Chen CLP, Lin Y (2014) Dual Fuzzy Hypergraph Regularized Multi-label Learning for Protein Subcellular Location Prediction. 2014 22nd International Conference on Pattern Recognition. doi: 10.1109/icpr.2014.97
  • Chen J, Tang YY, Chen CLP, Fang B, Shang Z, Lin Y (2014) Similarity Measure Learning in Closed-Form Solution for Image Classification. The Scientific World Journal 2014:1–15. doi: 10.1155/2014/747105
  • Lin Y, Tang YY, Fang B, Shang Z, Huang Y, Wang S (2013) A Visual-Attention Model Using Earth Mover's Distance-Based Saliency Measurement and Nonlinear Feature Combination. IEEE Transactions on Pattern Analysis and Machine Intelligence 35:314–328. doi: 10.1109/tpami.2012.119
  • Cao Y, Barrett D, Barbu A, Narayanaswamy S, Yu H, Michaux A, Lin Y, Dickinson S, Siskind JM, Wang S (2013) Recognize Human Activities from Partially Observed Videos. 2013 IEEE Conference on Computer Vision and Pattern Recognition. doi: 10.1109/cvpr.2013.343
  • Yang W, Tang YY, Fang B, Shang Z, Lin Y (2013) Visual saliency detection with center shift. Neurocomputing 103:63–74. doi: 10.1016/j.neucom.2012.08.029

Awards & Recognition

  • Department of Energy (DOE) NNSA Joule Award, 2022.
  • Department of Energy (DOE) NNSA Joule Award, 2020.
  • 2017's Top-10 Discoveries and Scientific Achievements at Brookhaven National Laboratory, 2017.
  • Outstanding Graduate Researcher of the Department of Computer Science and Engineering, University of South Carolina, 2016.
  • Best 10% Paper Award, International Conference on Image Processing, 2015.
  • IEEE Signal Processing Society Travel Grant, 2015.
Yuewei Lin

Brookhaven National Laboratory

Computational Science Initiative
Bldg. 725
P.O. Box 5000
Upton, NY 11973-5000

(631) 344-8704
ywlin@bnl.gov

Yuewei's Links