Associate Professor of Statistics
Department of Statistics
250 N. University Street
West Lafayette, IN 47907-2066
Email : firstname.lastname@example.org
Office : MATH 218
Phone : 765-494-3899
Current Research Interests:
Machine Learning and Data Mining, Big Data, Cybersecurity, Metabolomics
Publication by Area
Adversarial Machine Learning/AI
Adversarial Machine Learning for Cyber Security and
Computer Vision: Current Developments and Challenges,
in Wiley Interdisciplinary Reviews: Computational Statistics, 2020
- Bowei Xi, Yujie Chen, Fei Fan, Zhan Tu, Xinyan Deng,
Attack Against Deep Neural Networks , 1--5,
Proceedings of the Workshop on Artificial Intelligence Safety (SafeAI 2020)
co-located with 34th AAAI Conference on Artificial Intelligence (AAAI 2020),
New York, USA, Feb 7, 2020.
- Zhou, Y., Kantarcioglu, M., Xi, B.,
A Survey of Game Theoretic Approaches for Adversarial Machine Learning,
Wiley Interdisciplinary Reviews: Data Mining and Knowledge
Discovery, 9(3): e1259, 2019
- Zhou, Y., Kantarcioglu, M., Xi, B., Breaking
Transferability of Adversarial Samples with Randomness, submitted
Preprint is available as arXiv:1805.04613)
Invited talk slides, Adversarial Machine Learning: Big Data
Meets Cyber Security, 2018
Three hour tutorial,
Adversarial Data Mining: Big Data
Meets Cyber Security, the 23rd ACM Conference on
Computer and Communications Security, Vienna, Austria, October
24-28, 2016, by Kantarcioglu and Xi. Abstract is in Proceedings
of the 2016 ACM SIGSAC Conference on Computer and Communications
Security (CCS 2016), pages 1866--1867.
Here is the tutorial slides.
- Zhou, Y., Kantarcioglu, M., Xi, B., Adversarial Active Learning,
- Wei, W., Xi, B., Kantarcioglu, M., Adversarial
Clustering: A Grid Based Defensive Clustering Algorithm against
Preprint is available as arXiv:1804.04780)
- Zhou, Y., Kantarcioglu, M., Xi, B., A Survey of Game Theoretic Approaches for
Adversarial Machine Learning, to appear in WIREs Data Mining and
- Zhou, Y., Kantarcioglu, M., Xi, B., (Hot Topic Essay)
Adversarial Learning: Mind Games with the Opponent, ACM
Computing Reviews, August, 2017
- Kantarcioglu, M., and Xi, B.,
Adversarial Data Mining,
North Atlantic Treaty Organization (NATO) SAS-106 Symposium
on Analysis Support to Decision Making in Cyber Defence, 1--11,
June, 2014, Estonia.
- Zhou, Y., Kantarcioglu, M., Thuraisingham, B., and Xi, B.,
Adversarial Support Vector Machine Learning, in Proceedings of
the 18th ACM SIGKDD International Conference on Knowledge
Discovery and Data Mining (KDD 2012), 1059--1067, New York, NY.
Classifier Evaluation and Attribute Selection against Active
Data Mining and Knowledge Discovery, 22(1-2),
291-335 (45 pages), 2011,
by Murat Kantarcioglu, Bowei Xi, Chris Clifton.
(An earlier version is
Technical Report No.09-01, Department of Statistics, Purdue University).
Other Machine Learning and Data Mining Topics
- Sharabati, W., Xi, B.,
Robust Weighted Regression for
Ultrasound Image Super-Resolution, IEEE
Workshop on Machine Learning and Artificial Intelligence for
Multimedia Creation (co-located with IEEE International
Conference on Multimedia and Expo (ICME)), 1--6, San Diego, CA,
- Sharabati, W., Xi, B.,
A Neighborhood Regression Approach
for Removing Multiple Types of Additive Noises,
EURASIP Journal on Image and Video Processing, 2018:19, 1--14
(Featured Article, March-April 2018).
- Jiang, J., Xi, B., Kantarcioglu, M.,
Spatial Counts under
Differential Privacy Mechanism on Changing Spatial Scales,
to appear in Computer & Security
- Tong, X., Xi, B., Kantarcioglu, M., Inan, A.,
Mixture of Gaussian Models for Classification and Hypothesis Testing
under Differential Privacy, The 31st Annual IFIP WG
11.3 Conference on Data and Applications Security and Privacy
(DBSec 2017), LNCS 10359, 123–141, Springer 2017.
- Sharabati, W., Xi, B.,
Polynomial Local Regression
for Speckle Noise Removal, 1--6, the 23rd
International Conference on Pattern Recognition (ICPR 2016), Cancun,
Mexico, Dec, 2016 (Selected for oral presentation).
- Xi, B., Tan, K.M., and Liu, C.,
Logarithmic Transformation Based Gamma
Random Number Generators, Journal of Statistical
Software, 2013, 55(4), 1--17.
Xi, B., Kantarcioglu, M., Inan, A.,
Mixture of Gaussian Models and Bayes Error under Differential Privacy,
of the first
ACM Conference on Data and Application Security and Privacy (CODASPY 2011),
2011, San Antonio, Texas
Fuentes, M., Xi, B., and Cleveland, W.S.,
Trellis Display for
Modeling Data from Designed Experiments, Statistical Analysis and
Data Mining, 4(1), 133--145, 2011.
Xia, Y., and Xi, B.,
Conceptual Clustering Categorical Data
with Uncertainty, in Proceedings of the 19th IEEE International
Conference on Tools with Artificial Intelligence
(ICTAI 2007), 329--336,
Patras, Greece, October 2007.
Xi, B., Liu, Z., Raghavachari, M., Xia, C., and Li, Z.,
A Smart Hill-Climbing Algorithm for Application Server Configuration,
in Proceedings of the 13th International Conference on World Wide
Web (WWW 2004), 287--296, New York City, May 2004.
(US Patents #7272707 and #7490234).
Multifractal and Gaussian Fractional
Sum-Difference Models for Internet Traffic,
Performance Evaluation, 107 (2017),
1-33 (33 pages) ,
D. Anderson, W. S. Cleveland, B. Xi (an earlier version is a 52 page
Technical Report 15-02, Department of Statistics, Purdue University)
Large Complex Data: Divide and Recombine (D&R) with
RHIPE, STAT, 1(1), 53-67, 2012, by
Guha, S., Hafen, R., Rounds, J., Xia, J., Li, J., Xi, B., and
( Project Website:
Xi, B., Yang, X., Nair, V.N., and Michailidis, G.,
Statistical Issues in Computer Networks and Traffic Analysis,
Purdue Statistics Tech Report No.15-01, 2015
Analysis and Modeling of Internet VoIP Traffic for Network
Engineering, the Electronic Journal of Statistics, 4,
58-116 (59 pages), 2010,
by Xi, B., Chen, H., Cleveland, W.S., and Telkamp, T.
Denby, L., Landwehr J., Mallows C., Meloche J., Tuck J., Xi, B.,
Michailidis G., and Nair, V.,
Statistical Aspects of the Analysis of
Data Networks, Technometrics, 49(3), 318--334, 2007.
Lawrence, E., Michailidis, G., Nair, V.N., and Xi, B.,
Network Tomography: A Review and Recent Developments, Frontiers in
Statistics, 1--20, editors Jianqing Fan and Hira L. Koul, published by World
Scientific, USA, July 2006.
Estimating Network Loss Rates Using Active Tomography,
Journal of the American Statistical Association, Volume 101, Number 476, December 2006 ,
pp. 1430-1448 (19 pages),
by Bowei Xi, George Michailidis, and Vijayan N. Nair.
Xi, B., Michailidis, G., and Nair, V.N.,
Estimates of Network Link Loss Probabilities
Using End-to-End Multicast Measurements, in Proceedings of
the 37th Annual Conference on Information Sciences and
Systems (CISS 2003), 1--6, Johns Hopkins
University, March 2003.
Metabolomics and Biomarker Discovery
- Cheng, L. Y., Xi, B., A Likelihood Ratio Approach for
Precise Discovery of Truly Relevant Protein Markers, submitted.
Preprint is available as arXiv:1804.04249)
- Kwadwo, Owusu-Sarfo, Vincent M. Asiago, Lingli Deng, Haiwei Gu, Siwei
Wei, Narasimhamurthy Shanaiah, G. A. Nagana Gowda, Bowei Xi,
Elena G. Chiorean and Daniel Raftery,
NMR-based Metabolite Profiling of Pancreatic Cancer,
Current Metabolomics, 2(3), 204-212, 2014
(Editor Choice Articles; US patent application US 2015/0056605).
Xi, B., Gu, H., Hamid Baniasadi, and Daniel Raftery,
Statistical Analysis and Modeling of Mass
Spectrometry-Based Metabolomics Data, Mass Spectrometry in
Metabolomics: Methods and Protocols (2014): 333-353.
Gu, H., Pan, Z., Xi, B., Asiago, V.,
Musselman, B., and Raftery, D.,
Principal Component Directed Partial Least Squares Analysis for
Combining NMR and MS Data in Metabolomics:
Application to the Detection of Breast Cancer,
Analytica Chimica Acta, 686(1-2), 57--63, 2011.
(Evaluated by a Member of the Faculty of 1000, and placed in the
F1000 library of the top 2% of published
articles in biology and medicine, 2011)
Gu, H., Pan, Z., Xi, B., Hainline, B., Shanaiah, N.,
NaganaGowda, G.A., and Raftery, D.,
1H NMR Metabolomics Study of Age
Profiling in Children, NMR in Biomedicine, 22(8), 826-833,
Gu, H., Chen, H., Pan, Z., Jackson, A.U., Talaty, N., Xi, B.,
Kissinger, C., Duda, C., Mann, D., Raftery, D., and Cooks, R.G.,
Monitoring Diet Effects from Biofluids and Their Implications for
Metabolomics Studies, Analytical Chemistry, 79(1), 89--97, 2007.
(13th most cited article in 2007).
Purdue University Department of Statistics