Call for interns

Please check the website for details of possible available projects.

Medical Image Analysis

1. Sheng He, Yi Guan ,Chia H. Cheng, Tara Moore, Jennifer I. Luebke, Ron Killiany, Douglas L. Rosene, Bang-Bon Koo, Yangming Ou
   Human-to-Monkey Transfer Learning Identifies the Frontal White Matter as Key Determinant for Predicting Monkey Brain Age.
   Front. Aging Neurosci. 2023

2. Sheng He, Yanfang Feng, P Ellen Grant, Yangming Ou.
   Segmentation Ability Map: Interpret deep features for medical image segmentation.
   Medical Image Analysis. (MeDIA), 2023 [arXiv][GitHub]

3. Sheng He, Yanfang Feng, P Ellen Grant, Yangming Ou.
   Deep Relation Learning for Regression and Its Application to Brain Age Estimation.
   IEEE Trans. on Medical Imaging. (TMI), 2022 [arXiv][GitHub]

4. Sheng He, P Ellen Grant, Yangming Ou.
   Global-Local transformer for brain age estimation.
   IEEE Trans. on Medical Imaging. (TMI), 2022 [arXiv][GitHub]

5. Sheng He, Diana Pereira, Juan David Perez, Randy L Gollub, Shawn N Murphy, Sanjay Prabhu, Rudolph Pienaar, Richard L Robertson, P Ellen Grant, Yangming Ou.
   Multi-Channel attention-fusion neural network for brain age estimation: accuracy, generality, and interpretation with 16,705 healthy MRIs across lifespan.
   Medical Image Analysis. (MeDIA), 2021

6. Sheng He, Leon G Leanse, Yanfang Feng.
   Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases.
   Advanced Drug Delivery Reviews, 2021

   Document image analysis

7. Sheng He, Lambert Schomaker.
   CT-Net: Cascade T-shape deep fusion networks for document binarization.
   Pattern Recognition.(PR),vol.118, 2021.

8. Sheng He, Lambert Schomaker.
   GR-RNN: Global-context residual recurrent neural networks for writer identification.
   Pattern Recognition.(PR),vol.117, 2021. [GitHub]

9. Sheng He, Lambert Schomaker.
   FragNet: Writer Identification using Deep Fragment Networks.
   IEEE Trans. on Information Forensics and Security. (T-IFS), vol. 15, pp. 3013-3022, 2020 dataset [arXiv] [GitHub]

10. Pornntiwa Pawara, Emmanuel Okafor, Marc Groefsema, Sheng He, Lambert RB Schomaker, Marco A Wiering.
    One-vs-One classification for deep neural networks.
    Pattern Recognition.(PR),vol.108, 2020.

11. Sheng He, Lambert Schomaker.
    DeepOtsu: Document Enhancement and Binarization using Iterative Deep Learning.
    Pattern Recognition.(PR),vol.91, pp. 379-390, 2019. [arXiv] Monk Cuper Set (MCS) Dataset[tar.gz][zip][Tensorflow Code]

12. Sheng He, Lambert Schomaker.
    Deep Adaptive Learning for Writer Identification based on Single Handwritten Word Images.
    Pattern Recognition.(PR),vol.88,pp.64-74, 2018 [arXiv]

13. Sheng He, Lambert Schomaker.
    Writer identification using curvature-free features.
    Pattern Recognition. (PR), vol. 63, pp. 451-464, 2017. [PDF][C++ of COLD]

14. Sheng He, Lambert Schomaker.
    Beyond OCR: Multi-faceted understanding of handwritten document characteristics.
    Pattern Recognition. (PR), vol. 63, pp. 321-333, 2017 [PDF]

15. Sheng He, Petros Samara, Jan Burgers, Lambert Schomaker.
    A multiple-label guided clustering algorithm for historical document dating and localization.
    IEEE Trans. on Image Processing. (TIP), vol. 25, pp. 5252-5265, 2016 [PDF]

16. Sheng He, Petros Samara, Jan Burgers, Lambert Schomaker.
    Historical manuscript dating based on temporal pattern codebook.
    Computer Vision and Image Understanding (CVIU), vol. 152, pp.167-175,2016. [PDF]

17. Sheng He, Petros Samara, Jan Burgers, Lambert Schomaker.
    Image-based historical manuscript dating using contour and stroke fragments.
    Pattern Recognition(PR), Vol. 59, pp. 159-171, 2016 [PDF]

18. Sheng He,Marco Wiering, Lambert Schomaker.
    Junction detection in handwritten documents and its application to writer identification.
    Pattern Recognition(PR), 2015 [PDF][dataset & code]

19. Junwei Han, Sheng He, Xiaoliang Qian, Dongyang Wang, Lei Guo, Tianming Liu.
    An Object-oriented Visual Saliency Detection Framework Based on Sparse Coding Representations.
    IEEE Transactions on Circuits and Systems for Video Technology.2013 [PDF][bibtex]

Conference publications:

Find more on my previous webpage

Instructor

Boston Children's Hospital, Harvard Medical School

Email: heshengxgd[at]gmail[dot]com

Google Scholar

I am an Instructor in Investigation at Boston Children's Hosptial and Harvard Medical School. I gained a cum laude Ph.D. degree in artificial intelligence from the University of Groningen, the Netherlands, in 2017. From 2017 to 2018, I was a Postdoctoral fellow at the University of Groningen. From 2018 to 2022, I joined Harvard Medical School as a research fellow. My research interests include handwritten document analysis, deep learning, and medical image analysis.

Services (selected):

Ad-hoc Reviews: Pattern Recognition, IEEE Trans. on Medical Imaging, Medical Image Analysis, etc.