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Semhar Michael

A portrait of Dr. Semhar Michael smiling

Title

Associate Professor of Statistics

Office Building

Chicoine Architecture, Mathematics and Engineering Hall

Office

264

Mailing Address

Chicoine Architecture, Math & Engineering Building 264
Math & Statistics-Box 2225
University Station
Brookings, SD 57007

Biography

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 forms. I have addressed problems in clustering of time series, forensic 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 a 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 publicly available datasets.

Education

Ph.D. University of Alabama (2015), Applied Statistics
M.S. University of North Dakota (2011), Mathematics
B.S. University of Asmara, Eritrea (2006), Applied Mathematics

Academic Interests

Computational statistics, Mixture modeling, unsupervised learning, clustering, unstructured data analysis, forensic source identification problems

Academic Responsibilities

Spring 2023 Statistical Computation and Simulation
Spring 2021, 2022, 2023: STAT 685 Statistical Inference II
Fall 2021, 2022, 2023: STAT 715 Multivariate Statistics
Fall 2018, 2019, 2020: 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

Awards and Honors

National/regional/local
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

Grants

PI, "Developing Explainable Machine Learning and Computational Methods for Identifying Geographic and Racial Disparities in End Stage Renal Disease" (Award No. 1OT2OD032581-01, OTA-21-271). Co-PI's: Varilek, B., Moradi Rekabdarkolaee, H., Ngorsuraches, S., & Brooks, P. National Institute of Health Office of Data Science Strategy's AIM-AHEAD Consortium Development Grant. Amount awarded $1,091,316.00 (9/2023 - 9/2025).

Statistician, "Culturally responsive palliative care messaging for American Indians: An efficacy trial" (Award No. 1R21NR020383) Isaacson, M. (PI), and Anderson, J. (PI). National Institute of Nursing Research of the National Institutes of Health. Amount awarded: $368,794 (2022–2023).

Senior Personnel, “Testing a responsible innovation approach for integrating precision Agriculture (PA) technologies with future farm workers and work", Gardezi, M. (PI) Amount awarded: $2,996,759.00 National Science Foundation (Sept. 2020 – Aug. 2024).

Subaward Co-PI “Accounting for Covariates in Forensic Error Rate Assessment and Evidence Interpretation”, Saunders, C. (PI- SDSU), Tang, L (PI-UCF) Amount awarded: 108,104.00 National Institute of Justice (Sept. 2020 - Apr. 2022)

Co-PI “Anticipating Risks and Benefits of Precision Agriculture (PA) for the Future of Agricultural Work and Workforce: A Multi-Stakeholder Research Agenda." Gardezi, M. (PI) Amount awarded: $150,000 National Science Foundation. Funded. (Sept. 2019 - Aug. 2020)

Co-PI “MRI: Acquisition of a Microgrid Cyber-Physical Testbed for Advanced Energy Management Systems," National Science Foundation, Tonkoski, R. (PI) Amount awarded: $360,516 (Sept. 2017 - Aug. 2020)

PI "E-commerce analytics - finite mixture modeling for applications in E-commerce," Arnold K. Skeie - foundation, Amount awarded: $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, Amount awarded: $8253.21 (May - Aug. 2017).

PI “Combining structured and unstructured data for predictive modeling," SDSU faculty excellence grant, Amount awarded: $7,000 (Jan. 2018 - Jun. 2018).

PI "Natural language processing of text in the patient satisfaction survey," Sanford Data Collaborative, Amount awarded: $1,000 (Jan. 2018 - Jun. 2018).

PI "Breast cancer screening disparities in South Dakota," Women and giving, SDSU Foundation, Amount awarded: $1,000 (Jan. 2018 - May 2018).

CO-PI "Patient Engagement in the Management of Multiple Chronic Conditions," Sponsored by Sanford Health, Regional, Ngorsuraches, S. (PI) Amount awarded: $1,000.00. (Dec. 2016 – Jun. 2017).

Professional Memberships

American Statistical Association (ASA), Member, 2012–
Institute of Mathematical Statistics (IMS), Member, 2012–
International Institute for Analytics (IIA), Member, 2013–

Work Experience

Associate Professor at SDSU since 2021
Assistant Professor at SDSU 2015 - 2021
Graduate teaching Assistant 2009-2015 at UND, NDSU, UA

Creative Activities

JOURNAL PUBLICATIONS

Clustering large datasets by merging K-means solutions. Melnykov, V., & Michael, S. (2020). Journal of Classification, 37(1), 97-123.

Prioritizing climate‐smart agriculture: An organizational and temporal review. Gardezi, M., Michael, S., Stock, R., Vij, S., Ogunyiola, A., & Ishtiaque, A. (2022). Wiley Interdisciplinary Reviews: Climate Change, 13(2), e755.

Spatial analysis of breast cancer mortality rates in a rural state. Schulz, M., Spors, E., Bates, K., & Michael, S. (2022). Preventing Chronic Disease, 19, E65.

Mixture modeling of data with multiple partial right-censoring levels. Michael, S., Miljkovic, T., & Melnykov, V. (2020). Advances in Data Analysis and Classification, 14, 355-378.

Solar irradiance forecasting in remote microgrids using Markov switching model. Shakya, A., Michael, S., Saunders, C., Armstrong, D., Pandey, P., Chalise, S., & Tonkoski, R. (2016).IEEE Transactions on Sustainable Energy, 8(3), 895-905

See the full list of publications on Google scholar page here ----->

Area(s) of Research

Areas of research interest: Computational statistics, Mixture modeling, unsupervised learning, model-based clustering, unstructured data analysis, and forensic source identification problem.

Services
Associate Editor: Journal of Classification
Chair and member of the organizing committee: SDSU annual data science symposium
Reviewer: Computational Statistics and Data Analysis, Journal of Computational and Graphical Statistics, Journal of Applied Statistics, Journal of Computation and Simulation, Computational Economics, Law Probability, and Risk, etc...
Session Chair: Topic Contributed Session of Joint Statistical Meeting (2015,2017)
Session organizer and chair: Topic Contributed Session at Joint Statistical Meetings (2016)

Applications of Research

Health science, Forensic statistics, Engineering (Renewable energy), Precision Agriculture

Department(s)

Links

Research webpageGoogle Scholar pageORCIDLinkedIn