I-Ping Tu, Ph.D.

Research Fellow/Deputy Director

The Institute of Statistical Science, Academia Sinica

128, Academia Rd. Sec. 2, Taipei 115, Taiwan, R.O.C.
Tel: 886-2-2787-1952
: 886-2-2788-6833
Emai: iping@stat.sinica.edu.tw


Research Areas

Statistical Analysis for Biological Image Data, Clustering Analysis, Dimension Reduction, Scan statistics, Sequential Analysis, Statistical Machine learning, Block Chain.




updated 2020.12.31


Recent Publications


Journal Papers

1.          Shao-Hsuan Wang, Yi-Ching Yao, Wei-Hau Chang and I-Ping Tu* (2020). “Quantification of model bias underlying the phenomenon of Einstein from Noise”. Statistica Sinica (accepted). DOI: 10.5705/ss.202020.0334.

2.          Szu-Chi Chung, Shao-Hsuan Wang, Po-Yao Niu, Su-Yun Huang, Wei-Hau Chang and I-Ping Tu* (2020). “Two-stage dimension reduction for noisy high-dimensional images and application to Cryogenic Electron Microscopy”. Annals of Mathematical Sciences and Applications 5, 283-316.

3.          Szu-Chi Chung, Hsin-Hung Lin, Po-Yao Niu, Shih-Hsin Huang, I-Ping Tu* and Wei-Hau Chang* (2020). “Pre-pro is a fast pre-processor for single-particle cryo-EM by enhancing 2D classification”. Communications Biology 3.

4.          Ren Chen, I-Ping Tu, Kai-Er Chuang, Qin-Xue Lin, Shih-Wei Liao, Wanjiun Lia* (2020). “Endex: Degree of mining power decentralization for proof-of-work based blockchain systems”. IEEE Network 34, 266-271.

5.          I-Ping Tu*, Su-Yun Huang and Dai-Ni Hsieh (2019). “The generalized degrees of freedom of multilinear principal component analysis”. Journal of Multivariate Analysis 173, 26-37.

6.          Jheng-Syong Wu, Cheng-Yu Hung, Tzu-yun Chen, Sam Song-yao Lin, Shu-Yu Lin, I-Ping Tu, Hung-Ta Chen and Wei-Hau Chang* (2019). “Deriving a sub-nanomolar affinity peptide from TAP to enable smFRET analysis of RNA polymerase II complexes”. Methods 159-160, 59-69.

7.          Ting-Li Chen, Dai-Ni Hsieh, Hung Hung, I-Ping Tu*, Pei-Shien Wu, Yi-MingWu, Wei-Hau Chang and Su-Yun Huang (2014). “γ-SUP: a clustering algorithm for cryo-electron microscopy images of asymmetric particles”.  Annals of Applied Statistics 8, 259-285.

8.          I-Ping Tu*, Shao-Hsuan Wang and Yuan-Fu Huang (2013). “Estimating the Occurrence Rate of DNA Palindromes”, Annals of Applied Statistics 7, 1095-1110.

9.          I-Ping Tu (2013). “The Maximum of a Ratchet Scanning Process over a Poisson Random Field”, Statistica Sinica, 23, 1541-1551.

10.      Hung Hung, Pei-Hsien Wu, I-Ping Tu* and Su-Yun Huang (2012). “On Multilinear Principal Component Analysis of Order-Two Tensors”, Biometrika 99,569-583.

11.      Hao-Chih Lee, Bo-Lin Lin, Wei-Hau Chang and I-Ping Tu* (2012). “Towards Automated De-Noising of Single Molecular FRET Data: ADN for smFRET”. Journal of Biomedical Optics, 17.

12.      Hock Peng Chan*, and I-Ping Tu (2011). “Log-linear, Logistic Model Fitting and Local Score Statistics for Cluster Detection with Covariate Adjustments. Statistics in Medicine, 30, 91-100.

13.      Wei-Hau Chang*, Michael T.-K. Chiu, Chin-Yu Chen, Chi-Fu Yen, Yen-Cheng Lin, Yi-Ping Weng, Ji-Chau Chang, Yi-Min Wu, Holland Cheng, Jianhua Fu, and I-Ping Tu (2010).Zernike phase plate cryo-electron microscopy facilitates single particle analysis of unstained asymmetric protein complexesStructure,  18, 17-27.

14.      Chen, Y.-P., Huang, H.-C., and Tu, I.-P.* (2010). "A New Approach for Selecting the Number of Factors". Computational Statistics and Data Analysis, 54, 2990-2998.

15.      Hock Peng Chan*, I-Ping Tu and Nancy Zhang (2009). “Boundary crossing probability computations in the analysis of scan statistics” in Scan Statistics--Theory and Applications, eds J. Glaz and V. Pozdnyakov and S. Wallenstein, Birkhauser.

16.      I-Ping Tu*, Hung Chen, Xin Chen (2009). “An Eigenvector Variability Plot”. Statistica Sinica. 19, 1741-1754.  

17.      I-Ping Tu (2009). “Asymptotic Overshoot for Arithmetic IID Random Variables”. Statistica Sinica, 19, 315-323.


Conference Papers

1.          Yu-Jing Lin, Po-Wei Wu, Cheng-Han Hsu, I-Ping Tu and Shih-Wei Liao (2019). “An Evaluation of Bitcoin Address. Classification based on Transaction History Summarization”. In 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 302-310.

2.          Chi-Ning Chou, Yu-Jing Lin, I-Ping Tu and Shih-Wei Liao (2018). “Personalized Difficulty Adjustment for Countering the Double-Spending Attack in Proof-of-Work Consensus Protocols”. In 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 1456-1462.


Presentations in 2018

1.      2018.2.17-21 “A Dimension Reduction Method for cryo-EM Image Analysis”. The Computational Methods and Bioinformatics Session of Biophysics Society 2018 meeting. (Invited Speaker).

2.      2018.6.25 “Double Spending Fork Attack in Blockchain”, The Workshop for Blockchains, Probability and Statistics in Modern Financial Markets, Academia Sinica. (Invited Speaker).

3.      2018.6.26, “Statistical Analysis for Cryo-electron Microscopy Images”, Big data in health sciences conference, NHRI, Taipei. (Invited Speaker).

4.      2018.6.30-7.1 “A Model Bias Problem in Cryo-Electron Microscopy Image Analysis”, The Seventh International Biostatistics Workshop of Jilin University, Changchun, China. (Invited Speaker).

5.      2018.7.2-7.5 “A Model Bias Problem in Cryo-Electron Microscopy Image Analysis”, International Chinese Statistical Association China Conference with the Focus on Data Science, Qingdao, China.

6.      2018.9.3 “Einstein from noise and statistical de-nosing”, ASCEM’s Grand Opening Symposium and Workshop, Academia Sinica.

7.      2018.12.28 “ASCEP: A speedy and robust cryo-EM processing platform”, Symposium on Molecular Imaging, Biorhythms, and Quantitative Science in Biomedicine and Public Health, Academia Sinica.


Presentations in 2019

  1. 2019.7.26 “Why is it so hard to learn statistics?”, at the library of life science, Academia Sinica.
  2. 2019.8.14 "Statistical Methods for cryo-EM image analysis”, DSSV at Doshisha University, Kyoto, Japan.
  3. 2019.8.26 “Statistical Analysis for cryo-EM Images”, 2019 ONE DAY SYMPOSIUM ON DATA-DRIVEN AND PHYSICS-BASED ANALYTICS, Academia Sinica.
  4. 2019.11.6-7 “Introduction to PCA, KEPCA and its Application to cryo-EM images”, Waseda University –Academia Sinica Data Science Workshop, Tokyo, Japan.
  5. 2019.11.21-23 “A two-stage dimension reduction method and its applications on highly contaminated image sets”, as a keynote speech in the International Symposium on Theories and Methodologies for Large Complex Data, Tsukuba, Japan.


Presentations in 2020

  1. 2020.3.9 “Statistical Analysis for cryo-EM Images“, NTU Mathematics Colloquium.
  2. 2020.6.9 “Applications and Extensions of Principal Component Analysis: from a Top to Protein Structure Determination”, Colloquium at Institute of Physics, Academia Sinica.
  3. 2020.10.29 “Two-stage dimension reduction (2SDR) for noisy high-dimensional images and application to Cryogenic Electron Microscopy, invited lecture, NSYSU, The Department of Applied Mathematics.
  4. 2020.12.29 “Two-stage dimension reduction (2SDR) for noisy high-dimensional images and application to Cryogenic Electron Microscopy, 2020 ICCM on line presentation. (Invited Speaker).