Longxiang Zhang's Homepage
I studied and researched in the field of Physics for most of my professional life, earninig a BS
and MS
degree in physics from Zhejiang university (Hangzhou, Zhejiang, China) and University of
Illinois Urbana
Champaign (Champaign, Illinois, USA) respectively. I then switched career and earned a master's
degree in
Computational Data Science from Carnegie Mellon University (Pittsburgh, Pennsylvania, USA) in
2019. My
professional development then has been in the field of Machine Learning/Deep Learning/Natural
Language
Processing (NLP), and I have since worked at multiple companies focusing on providing data
science
and deep learning solutions to industrial and healthcare clients.
My current interest lies in AI-based healthcare, focusing on how to apply NLP technology to
automate clinical
visit flow for physicians and help them create "Time-to-Care" (see Physician
Burnout). I
still harbor undying enthusiasm for Physics, following frontier research in Quantum Information,
String Theory, and Material Sciences.
Education:
MCDS, Language Technologies Institute, Carnegie Mellon University, USA (2019)
MS in Physics, Department of Physics, University of Illinois Urbana Champaign, USA (2017)
Publication:
Machine Learning/Deep Learning
Su, Jing, Longxiang Zhang, Hamid Reza Hassanzadeh, and Thomas Schaaf. "Extract and Abstract
with
BART for Clinical Notes from Doctor-Patient Conversations." Proc. Interspeech 2022 (2022):
2488-2492.
https://www.isca-speech.org/archive/pdfs/interspeech_2022/su22b_interspeech.pdf
Grambow, Colin, Longxiang Zhang, and Thomas Schaaf. In-Domain
Pre-Training Improves Clinical Note Generation from Doctor-Patient Conversations. In Proceedings of
the
First Workshop on Natural Language Generation in Healthcare, pp. 9-22. 2022.
https://aclanthology.org/2022.nlg4health-1.2.pdf
Longxiang Zhang, Renato Negrinho, Arindam Ghosh, Vasudevan Jagannathan, Hamid Reza Hassanzadeh, Thomas Schaaf,
and
Matthew R. Gormley. 2021. Leveraging Pretrained
Models for Automatic Summarization of Doctor-Patient Conversations. In Findings of the
Association
for Computational Linguistics: EMNLP 2021, pages 3693–3712, Punta Cana, Dominican Republic.
Association for Computational Linguistics. https://aclanthology.org/2021.findings-emnlp.313/
Schaaf, Thomas, Longxiang Zhang, Alireza Bayestehtashk, Mark Fuhs, Shahid Durrani, Susanne Burger, Monika
Woszczyna,
and Thomas Polzin. "Are You Dictating to Me? Detecting Embedded Dictations in Doctor-Patient Conversations."
In 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), pp. 587-593. IEEE,
2021.
https://ieeexplore.ieee.org/abstract/document/9688118
Physics
Bian, Guang, Longxiang Zhang, Yang Liu, T. Miller, and T-C. Chiang. "Illuminating the surface spin texture of the
Giant-Rashba quantum-well system Bi/Ag (111) by circularly polarized photoemission." Physical Review
Letters 108, no. 18 (2012): 186403. https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.108.186403
Liu, Y., Longxiang Zhang, M. K. Brinkley, G. Bian, T. Miller, and T-C. Chiang. "Phonon-induced gaps in graphene
and
graphite observed by angle-resolved photoemission." Physical review letters 105, no. 13
(2010):
136804. https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.105.136804
Hong, Hawoong, Aaron Gray, Ruqing Xu, Longxiang Zhang, and T-C. Chiang. "Quantum growth of a metal/insulator
system:
Lead on sapphire." Applied Physics Letters 97, no. 24 (2010): 241908. https://aip.scitation.org/doi/abs/10.1063/1.3526727
Ren, J., Fu, L., Bian, G., Su, J., Zhang, H., Velury, S., Yukawa, R., Zhang, L., Wang, T., Zha, G. and Guo, R.,
2016.
An Effective Approach to Improving Cadmium Telluride (111) A Surface by Molecular-Beam-Epitaxy Growth of
Tellurium
Monolayer. ACS applied materials & interfaces, 8(1), pp.726-735. https://pubs.acs.org/doi/abs/10.1021/acsami.5b09863
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