Habte Tadesse LIKASSA | Data Science | Best Academic Researcher Award

Dr. Habte Tadesse LIKASSA | Data Science | Best Academic Researcher Award

Dr. Habte Tadesse Likassa, Arizona State University, United States

Dr. Habte Tadesse Likassa is a versatile and accomplished academic researcher whose work bridges critical areas of biostatistics, medical imaging, and econometrics. He has made notable contributions to methodological innovation and has demonstrated leadership in education and research policy. His career is marked by a commitment to excellence, interdisciplinary collaboration, and applied impact.

Profile

Scopus

Google Scholar

Summary:

Dr. Habte Tadesse Likassa is an accomplished statistician and researcher with strong credentials in applied and theoretical domains. His work is interdisciplinary, spanning healthcare, economics, and statistical methodologies, and is marked by real-world relevance and academic rigor. His leadership roles, technical skills, and international collaborations reinforce his profile as a high-potential researcher. However, strategic focus on publishing in higher-impact journals and increasing citation metrics would strengthen his global scholarly presence.

🎓 Education

Habte T. Likassa holds a PhD in Statistics from the National Taiwan University of Science and Technology, Taiwan, awarded in July 2019. His doctoral research focused on developing new robust methods for outlier and heavy sparse noise detection in high-dimensional images, earning him an A+ grade. He also holds an MSc in Statistics from Addis Ababa University, Ethiopia, where his thesis involved spatial and count regression models for analyzing tuberculosis incidence in North Shoa Zone. He earned his BSc in Statistics from the University of Gondar, Ethiopia, with a research focus on time series modeling for traffic data forecasting. Additionally, he obtained a Higher Diploma in Teaching at Higher Education from Debre Birhan University in 2013.

💼Experience

Dr. Likassa is currently serving as a Postdoctoral Research Scholar at the Department of Biostatistics, College of Health Solutions, Arizona State University, USA, since 2024. His work involves both methodological advancements in biostatistics and applied analysis using high-dimensional datasets. Previously, he held academic appointments across several Ethiopian universities including Addis Ababa University, Ambo University, and Debre Birhan University, serving in various capacities such as Assistant Professor, Lecturer, and Graduate Assistant between 2008 and 2023.

🔬Research Focus

Dr. Likassa’s research interests are diverse and interdisciplinary. His work primarily focuses on the development of robust statistical methods for medical imaging and anomaly detection in high-dimensional data. He is also engaged in survival analysis for heart failure, COVID-19, and cancer patients, as well as econometric modeling of inflation volatility using multivariate GARCH techniques. His research interests include machine learning, deep robust methods, low-rank sparse decomposition such as RPCA and Tensor RPCA, optimization techniques, artificial intelligence, and applied statistical modeling including logistic regression, multivariate analysis, spatial analysis, medical image analysis, and time series forecasting.

🛠️Skills

Dr. Likassa has extensive expertise in data management and advanced statistical modeling. His skills span big data analytics, management of economic and survey claim data, spatial exploratory data analysis, and high-dimensional health and image data analysis. He is proficient in various statistical software including LaTeX, SPSS, SAS, Stata, R, GIS, MATLAB, and Python. He has also delivered numerous training sessions to researchers, postgraduate students, and government professionals on research ethics, statistical methods, and data analysis techniques.

🏆Awards

Dr. Likassa has received several awards for his contributions to research and presentations. In 2024, he delivered a talk at the Arizona Alzheimer’s Consortium. He has received multiple Best Presenter Certificates at international conferences, including a Best Presenter Award in Taiwan, Republic of China.

📚 Publications

  • Title: A Multivariate GARCH Model with Time-Varying Correlations: What Do Inflation Data Show in Ethiopia
    Authors: Likassa, Habte Tadesse; Chen, Dinggeng; Nadarajah, Saralees; Temesgen, Shibru; Gotu, Butte
    Year: 2025
    Journal: Computational Economics

  • Title: Building a Sustainable Future: Investigating the Role and Contributions of Higher Education Institutions Instructors in Promoting Social Sustainability—Empirical Evidence from Ethiopia
    Authors: Tafese, Mestawot Beyene; Kopp, Erika; Likassa, Habte Tadesse
    Year: 2024
    Journal: Education Sciences

Conclusion:

Dr. Likassa is highly suitable for the Best Academic Researcher Award. His breadth of expertise, research innovation, and dedication to academic service make him a commendable choice. Addressing the noted areas for improvement could further enhance his candidacy, but his current achievements already position him as an impactful and deserving researcher on an international scale

Zhiyong Zhang | Data Science | Best Researcher Award

Dr. Zhiyong Zhang | Data Science | Best Researcher Award

Dr. Zhiyong Zhang, Tianjin university of traditional Chinese medicine, China

Dr. Zhiyong Zhang is a Ph.D. candidate at Tianjin University of Traditional Chinese Medicine, China. His research focuses on the integration of modern analytical techniques and artificial intelligence to enhance quality evaluation and control in Traditional Chinese Medicine (TCM). With expertise in LC/GC-MS, ICP-MS, NIR, and LIBS, he has contributed to over 20 peer-reviewed publications, including 12 SCI-indexed papers as first or co-first author. His work advances real-time, data-driven approaches for TCM manufacturing and herbal product authentication.

Profile

Scopus

Summary:

Dr. Zhiyong Zhang is a rising star in the field of Traditional Chinese Medicine research, demonstrating excellence in combining classical medical knowledge with state-of-the-art analytical and computational techniques. His research is not only scientifically rigorous but also highly relevant to real-world applications in medicine production, safety, and quality assurance. With a growing list of impactful publications and innovative methodologies, he exemplifies the type of interdisciplinary thinker the Research for Best Researcher Award aims to recognize.

🎓 Education

Zhiyong Zhang, born in September 1997 in Huaibei, Anhui, China, is currently a Ph.D. candidate in Traditional Chinese Medicine at the Tianjin University of Traditional Chinese Medicine, under the supervision of Researcher Wenlong Li. He began his doctoral studies in September 2022. Prior to this, he participated in a joint master’s training program at the First Institute of Oceanography, Ministry of Natural Resources, from September 2021 to June 2022, where he worked with Researcher Junhui Chen. Zhang completed his Master of Science in Traditional Chinese Medicine at the Tianjin University of Traditional Chinese Medicine from September 2020 to June 2021. His academic journey began with a Bachelor of Science in Traditional Chinese Medicine Pharmaceutical at the same university, completed between 2015 and 2019.

💼Experience

Dr. Zhiyong Zhang has extensive academic and research experience in the field of Traditional Chinese Medicine (TCM). He is currently pursuing his Ph.D. at Tianjin University of Traditional Chinese Medicine, where he focuses on quality assessment and control of TCM using advanced analytical technologies and artificial intelligence. He previously participated in a joint master’s training program at the First Institute of Oceanography, Ministry of Natural Resources, where he gained interdisciplinary experience in TCM analysis and data integration. He also completed both his Master’s and Bachelor’s degrees in Traditional Chinese Medicine and Pharmaceutical Sciences at Tianjin University of Traditional Chinese Medicine. Over the years, Dr. Zhang has developed strong expertise in applying chemometrics, metabolomics, and spectroscopy-based techniques to improve the reliability and efficiency of TCM research and manufacturing.

🔬Research Focus

Zhiyong Zhang’s research centers on advancing the quality evaluation and control of Traditional Chinese Medicine (TCM) through modern analytical and computational techniques. His interests include machine learning-based quality analysis of TCM using multimodal data, rapid on-site quality control of Chinese herbal materials and processed products, and the development of multidimensional quality evaluation systems integrating metabolomics, elementalomics, and chemometrics. He also focuses on the application of Process Analytical Technology (PAT) for real-time monitoring of critical quality attributes in TCM manufacturing.

🛠️Skills

He is proficient in a wide range of analytical techniques, including Liquid/Gas Chromatography-Mass Spectrometry (LC/GC-MS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Near-Infrared Spectroscopy (NIR), and Laser-Induced Breakdown Spectroscopy (LIBS). His expertise spans both laboratory-based and field-deployable technologies, enabling high-throughput and real-time analysis of complex herbal matrices.

🏆Awards

Zhiyong Zhang has made significant contributions to the field with over 20 peer-reviewed publications, including 12 SCI-indexed papers where he served as the first author or co-first author. He has also filed three patent applications related to his research innovations in TCM quality control and evaluation technologies.

📚 Publications

1. Journal of Food Composition and Analysis (2025)

Title: Investigating the impact of geographical origin and harvesting season on the quality of Hypericum perforatum L. using LC-MS, GC-MS, and ICP-MS technologies in conjunction with random forest model
Authors: Zhang Zhiyong, Qian Jiahe, Fang Guangpu, Chen Jingchao, Li Wenlong

2. Phytochemical Analysis (2025)

Title: A Machine Learning-Based Approach for the Prediction of Anticoagulant Activity of Hypericum perforatum L. and Evaluation of Compound Activity
Authors: Zhang Zhiyong, Nie Wennan, Zhang Yijing, Zhang Shule, Li Wenlong

Conclusion:

Dr. Zhiyong Zhang is highly suitable for the Research for Best Researcher Award. His achievements to date already place him among the most promising young researchers in the field of TCM. With continued support and opportunities to expand his global and practical influence, he is poised to make even greater contributions to science and society.