About Me

I am currently a Postdoctoral Research Fellow in the Department of Biostatistics, College of Health Solutions, Arizona State University (ASU), United States of America under the supervision of Prof. Ding-Geng Chen (https://search.asu.edu/profile/4022508). We are working on developing robust methods for medical imaging, including retinal and cancer-related imaging, to support medical experts in early screening and diagnosis.

Before joining ASU, I served as an Assistant Professor in the Department of Statistics at both Addis Ababa and Ambo Universities in Ethiopia. I also taught statistical courses as a guest lecturer at several public universities, including Haramaya, Jimma, Bule Hora, and Wollega Universities. Additionally, I chaired the Department of Statistics at Addis Ababa University and served as Chair of the Department of Statistics and Vice Dean of the College of Natural and Computational Sciences at Ambo University, where I focused on research, community-based services, and technology transfer. I also conducted multiple training sessions on statistical software for faculty and postgraduate students at various higher public universities in Ethiopia. Furthermore, I served on the executive committee of the Ethiopian Statistical Association, where I led the training wing.

Currently, as a guest board member for the International Journal of Statistics in Medical Research, I encourage scholars to submit their methodological papers to the journal. Additionally, I have presented my research at prominent national and international conferences. In 2024, I presented part of our work at the 2024 Alzheimer's Consortium in Arizona, as well as orally at the Department of Statistics at Addis Ababa University. Additionally, I gave an online presentation to the University of Manchester in the UK. Now, I am a member of the American Statistical Association, the Ethiopian Statistical Association, the Ethiopian Biometry Society, and the Ethiopian Computational Society.

My research interests include:

• Tensor RPCA for multi-array neuroimaging data.
• RPCA for medical image analysis: Enhancing image quality and accuracy for applications such as cataract, diabetes and cancer detection.
• Developing novel and innovative AI-driven research, supported by modern robust statistical methods, to analyze health and health-related data
• Predictive modeling to manage diseases such as diabetes, Alzheimer’s disease, and cancer through neuroimaging.
• Spatio-temporal analysis of infectious diseases, statistical analysis in mental health and time to event analysis.

I earned my Ph.D. from the National Taiwan University of Science and Technology, Republic of China, in 2019, where my dissertation focused on developing robust PCA methods to address noise and outliers in high-dimensional images. I also recieved my M.Sc. and B.Sc. from Addis Ababa University and the University of Gondar, completed in 2011 and 2008, respectively all in Statistics.

Education

• Postdoctoral Research Scholar in Biostatistics, College of Health Solutions, Arizona State University (since 2024)
• Ph.D. in Statistics (specializing in signal processing), National Taiwan University of Science and Technology (NTUST), Taiwan (2019)
• M.Sc. in Statistics, Addis Ababa University (2011)
• B.Sc. in Statistics, University of Gondar (2008)

Publication

1) Selected methodological papers (More to come)

• Likassa, Habte Tadesse and Chen, Ding-Geng (2024): Robust Principal Component Analysis for Retinal Image Enhancement: Biostatistics Modeling and Public Health Applications, 157—190, 2024 . See full paper
• Habte Tadesse LIKASSA,Ding Geng Chen, and Dayu Sun (2024): A Novel RPCA Method Using Log-Weighted Nuclear and L_(2,1) Norms Combined with Contrast-Limited Adaptive Histogram Equalization (CLAHE) for High Dimensional Natural and Medical Image Data: International Journal of Statistics in Medical Research, 13, 2024. See full paper
• Likassa, Habte Tadesse and Fang, Wen-Hsien and Leu, Jenq-Shiou (2019): Robust image recovery via affine transformation and L_(2,1) Norm, 7, 125011—125021, IEEE. See full paper
• Likassa, Habte Tadesse and Chen, Ding-Geng and Chen, Kewei and Wang, Yalin and Zhu, Wenhui (2024): Robust PCA with L_{w,*} and L_{2, 1} Norms: A Novel Method for Low-Quality Retinal Image Enhancement: Journal of Imaging, 10(7), 151, 2024. See full paper

2) Selected Applied Papers (Only spatial based articles)

• Tadesse, Habte (2023): Modelling Conflict Dynamics: Evidence from Africa: What do the data show via spatiotemporal global ACLED dataset? Journal of Applied Spatial Analysis and Policy, 16(4), 1541—1559, 2023, Springer. See full paper
• Mulgeta, Daniel, Gotu, Butte, Temesgen, Shibru, Belina, Merga, Likassa, Habte Tadesse and Tsegaye, Dejene (2024): Statistical Analysis of Spatial Distribution of Ambient Air Pollution in Addis Ababa, Ethiopia, Journal Stochastic Environmental Research and Risk Assessment, 1—19, 2024, Springer. See full paper

Teaching

• Fundamental of biostatistics
• Bayesian biostatistics
• Multivariate techniques
• Design experiment analysis
• Advanced statistical theory of distributions and
• Probability and statistics

Skills

• R
• Matlab
• Stata
• GIS
• SAS