I-Ping Tu, Ph.D. Research Fellow/Deputy Director The
Institute of Statistical Science, Academia Sinica |
Research Areas |
Statistical Analysis for Biological Image Data, Clustering Analysis, Dimension Reduction, Scan statistics, Sequential Analysis, Statistical Machine learning, Block Chain.
|
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 complexes” Structure,
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 |
Presentations in 2020 |