职称：教授/硕士生导师
个人简介：
主要研究领域：机器学习和数据科学原创性研究，及其在生物医学信息学，健康信息学,多媒体及文本大数据里的应用。
科研成果：
[1] Nezhad, MZ, Sadati, N, Yang, Kand Zhu, D.A deep active survival analysisapproach for precision treatment recommendations: application of prostatecancer.Expert Systems with Applications. Vol. 15, 16-26.
[2] Zheng, J, Gao, L, Zhang, H, Zhu,D, Wang, H, Gao, Q and Leung, V.Joint energy management andinterference coordination with Max-Min fairness in ultra-dense hetnets.IEEEAccess, Vol. 6, 32588-32600.
[3] Wang, L, Zhu, D, Towner, E andDong, M (2018)Obesity risk factors ranking usingmulti-task learning. IEEEConference on Biomedical and HealthInformatics(IEEE-BHI 2018), Las Vegas, March, 2018.
[4] Li, X and Zhu, D (2018)Robust feature selection via l 2, 1 -normin finite mixture of regression.Pattern Recognition Letters,https://doi.org/10.1016/j.patrec.2018.02.021.
[5] Wang, L, Zhu, D and Dong, M(2018)Clustering over-dispersed data withmixed feature types.Statistical Analysis and Data mining,11(2), 55-65, April 2018.
[6] Li, X, Zhu, D and Dong, M(2018)Multinomial classification withclass-conditional overlapping sparse feature groups.PatternRecognition Letters, vol 101, Jan. 2018, pp 37-43Source Code.
[7] Wang, L, Acharya, L, Bai, C andZhu, D (2017)Transcriptome assembly strategies forprecision medicine.Quantitative Biology, pp 1-11,https://doi.org/10.1007/s40484-017-0109-2.
[8] Wang, L, Zhu, D*,Li, Y andDong, M (2017)ModelingOver-dispersion for Network Data Clustering. In the proceeding of16thIEEEInternational Conference on Machine Learning andApplication(ICMLA’17). (Best Paper Award Top 3 Finalist, *CorrespondingAutor)
[9] Nezhad, MZ, Zhu, D*, Yang, K andLevy, P. (2017)A SupervisedBi-Clustering Approach for Precision Medicine. In the proceeding of16thIEEEInternational Conference on Machine Learning andApplication(ICMLA’17). (Best Poster Award Top 3 Finalist,*Corresponding Autor)
[10] Li, X, Zhu, D and Levy, P(2017)PredictiveDeep Network with Leveraging Clinical Measure as Auxiliary Task. Inthe proceedings of 2017 IEEEInternational Conference on Bioinformaticsand Biomedicine(BIBM’17)
[11] Wang, L, Li, Y, Zhou, J, Zhu, Dand Ye, J (2017)Multi-taskSurvival Analysis. In the proceedings of 2017IEEEInternational Conference on Data Mining(ICDM’17)
[12] Li, X, Zhu, D, Dong, M, Nezhad,MZ and Levy, P (2017)SDT: A Tree Method for DetectingPatient Subgroups with Personalized Risk Factors. In the proceedingsof 2017 American Medical Information Association (AMIA)Summit on ClinicalResearch Informatics, San Francisco, March 2017.
[13] Nezhad, MZ, Zhu, D, Li, X,Yang, C and Levy, P (2016)SAFS: A Deep Feature SelectionApproach for Precision Medicine. In the proceedings of 2016 IEEEInernational Conference on Bioinformatics and Biomedicine (IEEE BIBM2016).
[14] Xu, H, Dong, M, Zhu, D, et al.(2016)Text Classification with Topic-basedWord Embedding and Convolutional Neural Networks. In the proceedingsof 2016 ACM Conference on Bioinformatics, Computational Biology and HealthInformatics (ACM BCB 2016).
[15] Wang, L, Zhu, D, Li, Y andDong, M. (2016)Poisson-Markov Mixture Model andParallel Algorithm for Binning Massive and Heterogeneous DNA Sequencing Reads.In the Series ofLecture Notes in Computer Science(ISBRA 2016).
[16] Almomani, R, Dong, M and Zhu,D. (2016)Bayesian Hierarchical AppearanceModel for Robust Object Tracking. In the Proceeding of InternationalConference on Multimedia and Expo (ICME 2016).
[17] Almomani, R, Dong, M and Zhu,D. (2016)Object Tracking via DirichletProcess-based Appearance Models.Neural Computing andApplications, in press. DOI: 10.1007/s00521-016-2280-1.
科研项目：
1.NSF/CCF:S&CC:Promoting a Healthier Urban Community: Prioritization of Risk Factors for thePrevention and Treatment of Pediatric Obesity.09/01/2016-08/31/2019.(co-Principal Investigator)
2.NSF/IIS:S&AS: INT: Autonomous Battery Operating System (ABOS): AnAdaptive and Comprehensive Approach to Efficient, Safe, and Secure BatterySystem Management.09/01/2017-08/31/2021. (Senior Personnel)
3. NSF/CCF: EAGER: A novel algorithmic framework for discovering subnetworksfrom big biological data. 08/15/2014-08/14/2017. (Principal Investigator)
4. NIH/NLM: R21.A new informatics paradigm for reconstructing signalingpathways in human disease. 09/2009 – 08/2012. (Principal Investigator)
5. NIH/NCI: R01. Analysis of Epstain-Barr virus type III latency on cellular miRNAgene expression. (co-Investigator)
6. NSF/CCF: CPATH: A verification based learningmodel that enriches CS and related undergraduate programs.(co-PrincipalInvestigator)
教学情况：
ClassroomTeaching(Computer Science Department at Wayne State University):
1. CSC 8860 Seminar Topics in Computer Vision and Pattern Recognition. Fall 2017
2. CSC 7825 Machine Learning. Fall 2014, Fall 2015, Fall 2016
3. CSC 6580 Design and Analysis of Algorithms. Winter 2015, Winter 2016, Winter2017
4. CSC 5825 Intro. to Machine Learning and Applications. Winter 2017, Fall 2017,Fall 2018
5. CSC 5991 Special Topics in Comp. Sci. Fall 2012, Fall 2013, Winter 2014 ,Winter 2015, Winter 2016
6. CSC 2110 Comp. Sci. I (C++ Programming). Fall 2011, Winter 2012, Winter 2013,Fall 2013