|Title||Assistant Professor of Statistics|
|Office Building||Architecture, Mathematics & Engineering Building|
|Mailing Address||South Dakota State University
Mathematics & Statistics
SAME 264, Box 2225
Brookings, SD 57007
I am an applied statistician by training. My research focuses on computational statistics with an emphasis on developing novel methodologies for analyzing datasets in challenging form. I have addressed problems in clustering of time series and text data. My work has been published in peer-reviewed statistics journals and led to national paper competition awards. In the application side, I have developed forecasting algorithm jointly with colleagues in electrical engineering. With unstructured data, I worked on a building clustering, classification, and sentiment analysis models. In the health sciences, I have worked on mixture modeling, spatial clustering, and forecasting projects on datasets from Electronic Health Records and South Dakota Department of Health.
Applications of ResearchHealth science, Engineering (Renewable energy)
Professional MembershipsAmerican Statistical Association (ASA), Member, 2012–
Institute of Mathematical Statistics (IMS), Member, 2012–
International Institute for Analytics (IIA), Member, 2013–
Area(s) of Research Michael, S. and Melnykov, V. (2016) An effective strategy for initializing the EM algorithm in finite mixture models. Advances in Data Analysis and Classification.
 Shakya, A., Michael, S., Saunders, C., Armstrong, D., Pandey, P., Chalise, S., Tonkoski, R. (2016) Solar Irradiance Forecasting in Remote Microgrids using Markov Switching
Model, IEEE Transactions on Sustainable Energy pp. doi:10.1109/TSTE.2016.2629974
 Michael, S. and Melnykov, V. (2016) Finite mixture modeling of Gaussian regression time series with application to dendrochronology, accepted by Journal of Classification
 Shakya, A., Michael, S., Saunders, C., Armstrong, D., Pandey, P., Chalise, S., Tonkoski, R. (2016) Using Markov Switching Model for solar irradiance forecasting in remote
microgrids, IEEE Energy Conversion Congress and Exposition (ECCE) pp. 1–7 doi:10.1109/ECCE.2016.7855546
 Melnykov, V., Michael, S., and Melnykov, I. (2015) Recent Developments in Model-Based Clustering with Applications.In: M. E. Celebi (Ed.), Partitional Clustering Algorithms, ch. 1, pp. 1–39. doi:10.1007/978-3-319-09259-1
 Melnykov, V., Melnykov, I. and Michael, S. (2015) Semi-Supervised Model-Based Clustering with Positive and Negative Constraint. Advances in Data Analysis and classification, 10, 327–349. doi:10.1007/s11634-015-0200-3
 Michael, S. and Melnykov, V. (2016) Studying complexity of model-based clustering. Communications in Statistics - Simulation and Computation, 45, 2051–2069. doi:10.1080/03610918.2014.889156
Academic ResponsibilitiesFall 2018: STAT 684 & 685: Statistical Inference I & II
Fall 2017: STAT 784& 785: Statistical Inference I & II
Fall 2015-16: STAT 701: Modern Applied Statistics I
Spring 2017: STAT 702: Modern Applied Statistics II
Fall 2015- Spring 2017: Independent studies on Natural language processing, Finite mixture modeling and model-based clustering, advanced computational analysis
Work ExperienceAssistant Professor at SDSU since 2015
Former Positions HeldGraduate teaching assistantship at UA
Grants Co-PI “MRI: Acquisition of a Microgrid Cyber-Physical Testbed for Advanced Energy Management Systems," National Science Foundation, $360,516 (Sept, 2017 -Aug, 2020)
 PI "E-commerce analytics - finite mixture modeling for applications in E-commerce," Arnold K. Skeie - foundation, $158,590 (Dec 2016 - Dec 2019).
 PI "Topic Modeling for the Daschle Collection,” College of Arts and Science and SDSU Foundation, South Dakota State University, $8253.21 (May - Aug 2017).
 PI “Combining structured and unstructured data for predictive modeling," SDSU faculty excellence grant, $7,000 (Jan 2018 - Jun 2018).
 PI "Natural language processing of text in the patient satisfaction survey," Sanford Data Collaborative, $1,000 (Jan 2018 - Jun 2018).
 PI "Breast cancer screening disparities in South Dakota," Women and giving, SDSU Foundation, $1,000 (Jan 2018 - May 2018).
 CO-PI "Patient Engagement in the Management of Multiple Chronic Conditions," Sponsored by Sanford Health, Regional, $1,000.00. (Dec 2016 – Jun 2017).
Awards & HonorsNational
Certificate of appreciation (advising Damon Bayer and Eric Stratman), Van D. and Barabara B. Fishback Honors College, 2017
ASA Travel award for attending Women in Statistics and Data Science conference, 2016
R.L. Anderson student poster award Top 6 from 63 posters, 2014
Laha travel award, 2013
Annual national SAS Analytics and Data Mining Shootout competition Winner, 2013.
Boyd Harshbarger travel fund, SRCOS 2013 and 2014
Outstanding Ph.D. Student in Applied Statistics, ISM department at UA, 2014
Excellence in research and teaching, ISM department at UA, 2013-2015
Excellence in teaching at COMSAT, 2008 and 2009
University of Asmara Scholarship, 2001–2005
Research/Scholarship ResponsibilitiesReviewer: Computational Statistics and Data Analysis, Journal of Applied Statistics, Journal of Computation and Simulation, Computational Economics, Law Probability and Risk
Session Chair: Topic Contributed Session of Joint Statistical Meeting (2015,2017)
Session organizer and chair: Topic Contributed Session at Joint Statistical Meetings (2016)
- Computational statistics, unsupervised learning, clustering, unstructured data anlaysis
EducationPh.D. University of Alabama (2015), Applied Statistics
MS. University of North Dakota (2011), Mathematics
BS. University of Asmara, Eritrea (2006), Applied Mathematics