World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
5280
World Ranking
7720
National Ranking
3330

Overview

Yusu Wang is a researcher affiliated with the University of California, San Diego, in the United States, with a focus primarily on computer science. Their research spans several subfields including computational theory and mathematics, artificial intelligence, computer vision and pattern recognition, materials chemistry, and biophysics.

The main topics of Yusu Wang's work include:

  • Topological and Geometric Data Analysis
  • Advanced Graph Neural Networks
  • Cell Image Analysis Techniques
  • Data Management and Algorithms
  • Graph Theory and Algorithms
  • Machine Learning in Materials Science
  • Homotopy and Cohomology in Algebraic Topology

Yusu Wang has contributed substantially to the academic literature, with frequent publications in venues such as:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Cambridge University Press eBooks
  • Discrete & Computational Geometry
  • Proceedings of the AAAI Conference on Artificial Intelligence

Among the recent papers associated with Wang are:

  • Hierarchically structured bioinspired nanocomposites, 2022, Nature Materials
  • A Note on Over-Smoothing for Graph Neural Networks, 2020, arXiv (Cornell University)
  • Composition design of high-entropy alloys with deep sets learning, 2022, npj Computational Materials
  • Persistent Laplacians: Properties, Algorithms and Implications, 2022, SIAM Journal on Mathematics of Data Science
  • Semantic segmentation of microscopic neuroanatomical data by combining topological priors with encoder-decoder deep networks, 2020, Nature Machine Intelligence

Yusu Wang has collaborated frequently with several researchers, including:

  • Tamal K. Dey
  • Zhengchao Wan
  • Lucas Magee
  • Chen Cai
  • Facundo Mémoli

Best Publications

  • Discrete laplace operator on meshed surfaces

    Mikhail Belkin;Jian Sun;Yusu Wang

  • Near-Linear Time Approximation Algorithms for Curve Simplification

    Pankaj K. Agarwal;Sariel Har-Peled;Nabil H. Mustafa;Yusu Wang

  • Constructing Laplace operator from point clouds in Rd

    Mikhail Belkin;Jian Sun;Yusu Wang

  • Extreme Elevation on a 2-Manifold

    Pankaj K. Agarwal;Herbert Edelsbrunner;John Harer;Yusu Wang

  • Fréchet distance for curves, revisited

    Boris Aronov;Sariel Har-Peled;Christian Knauer;Yusu Wang

  • Persistent Heat Signature for Pose-oblivious Matching of Incomplete Models

    Tamal K. Dey;Kuiyu Li;Chuanjiang Luo;Pawas Ranjan

  • Computing Topological Persistence for Simplicial Maps

    Tamal K. Dey;Fengtao Fan;Yusu Wang

  • Measuring Distance between Reeb Graphs

    Ulrich Bauer;Xiaoyin Ge;Yusu Wang

  • Exact algorithms for partial curve matching via the Fréchet distance

    Kevin Buchin;Maike Buchin;Yusu Wang

  • Data Skeletonization via Reeb Graphs

    Xiaoyin Ge;Issam I. Safa;Mikhail Belkin;Yusu Wang

  • Metrics for comparing neuronal tree shapes based on persistent homology.

    Yanjie Li;Dingkang Wang;Giorgio A. Ascoli;Partha Mitra

  • Post-placement voltage island generation under performance requirement

    Huaizhi Wu;I-Min Liu;M. D. F. Wong;Yusu Wang

  • A Note on Over-Smoothing for Graph Neural Networks

    Chen Cai;Yusu Wang

  • An efficient computation of handle and tunnel loops via Reeb graphs

    Tamal K. Dey;Fengtao Fan;Yusu Wang

  • Unperturbed: spectral analysis beyond Davis-Kahan

    Justin Eldridge;Mikhail Belkin;Yusu Wang

  • A randomized O(m log m) time algorithm for computing Reeb graphs of arbitrary simplicial complexes

    William Harvey;Yusu Wang;Rephael Wenger

  • Reeb Graphs: Approximation and Persistence

    Tamal K. Dey;Yusu Wang

  • Shape Fitting with Outliers

    Sariel Har-Peled;Yusu Wang

  • Distance-Sensitive information brokerage in sensor networks

    Stefan Funke;Leonidas J. Guibas;An Nguyen;Yusu Wang

  • Approximating gradients for meshes and point clouds via diffusion metric

    Chuanjiang Luo;Issam Safa;Yusu Wang

  • A Topological Regularizer for Classifiers via Persistent Homology

    Chao Chen;Xiuyan Ni;Qinxun Bai;Yusu Wang

  • Supplementary Material for SIGGRAPH 2013 paper: An Efficient Computation of Handle and Tunnel Loops via Reeb Graphs

    Tamal K. Dey;Fengtao Fan;Yusu Wang

Frequent Co-Authors

Tamal K. Dey
Tamal K. Dey Purdue University West Lafayette
Pankaj K. Agarwal
Pankaj K. Agarwal Duke University
Mikhail Belkin
Mikhail Belkin University of California, San Diego
Sariel Har-Peled
Sariel Har-Peled University of Illinois at Urbana-Champaign
Jian Sun
Jian Sun Megvii
Srinivasan Parthasarathy
Srinivasan Parthasarathy The Ohio State University
Leonidas J. Guibas
Leonidas J. Guibas Stanford University
Herbert Edelsbrunner
Herbert Edelsbrunner Institute of Science and Technology Austria
Peer-Timo Bremer
Peer-Timo Bremer Lawrence Livermore National Laboratory
Z. Josh Huang
Z. Josh Huang Cold Spring Harbor Laboratory

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degree options in computer science can open diverse career pathways. Many students start by earning an online associate degree to build foundational skills in programming, IT, and networking. These programs often offer flexibility for working adults and those seeking an affordable entry into tech.

For further advancement, choosing which master's degree is most in demand in usa can be crucial. Specializing at the graduate level in areas such as data science, cybersecurity, or artificial intelligence can greatly enhance your career prospects and salary potential.

Budget-conscious students can search for the cheapest online college programs, which lower barriers to entry and help minimize student debt. Additionally, those concerned about past academic performance should explore online schools that accept low gpa. These institutions provide second chances through accessible admissions policies.

With flexible online learning, advanced degree choices, and a range of affordable options, pursuing computer science in the USA is more accessible than ever.

Best Scientists Citing Yusu Wang

Trending Scientists