Davide Guido – Biostatistics/Bioinformatics – Best Researcher Award

Davide Guido - Biostatistics/Bioinformatics - Best Researcher Award

National Institute of Gastroenterology - Italy

AUTHOR PROFILE

SCOPUS

DR. DAVIDE GUIDO 🎓

Dr. Davide Guido is an esteemed researcher and expert in the field of Experimental Studies, focusing on various study designs such as randomized clinical trials, cross-over trials, and adaptive designs. His contributions to the scientific community include determining relative sample sizes for different research methodologies, enabling more effective and reliable outcomes in clinical research. His work is vital for understanding complex interventions and ensuring that studies yield meaningful results.

OBSERVATIONAL STUDIES 📊

In the realm of Observational Studies, Dr. Guido conducts comprehensive analyses of cross-sectional, case-control, and cohort designs. His expertise extends to propensity score matching and sample size determination, which are critical for reducing bias and improving the validity of observational research findings. His dedication to these methodologies enhances our understanding of health trends and outcomes in various populations.

REGRESSION ANALYSIS 📈

Dr. Guido's work in Regression Analysis encompasses a wide array of techniques, including generalized linear models and time series regression. He employs sophisticated methods such as quantile regression and spline regression to uncover relationships in complex datasets. His findings contribute significantly to the fields of epidemiology and public health, providing insights that inform policy and practice.

PREDICTIVE ANALYSIS 🔍

Through his expertise in Predictive Analysis, Dr. Guido utilizes supervised and unsupervised methods, including random forests and penalized regression modeling. His work in classification and clustering enables researchers to make informed predictions based on data patterns. By integrating these techniques, he enhances the ability to forecast outcomes in health-related research and beyond.

BAYESIAN ANALYSIS 🔮

Dr. Guido applies Bayesian Analysis to tackle challenges in statistical modeling, particularly in spatial-temporal contexts. His innovative approaches facilitate understanding complex phenomena, allowing for more accurate predictions and inferences. This area of research plays a pivotal role in enhancing the robustness of scientific conclusions drawn from data.

SPATIAL STATISTICS 🗺️

In Spatial Statistics, Dr. Guido explores geostatistical modeling and geographically weighted regression. His investigations into lattice data modeling contribute to the understanding of spatial patterns and relationships within data. This research is essential for addressing public health concerns and environmental challenges that exhibit spatial characteristics.

COLLABORATIVE RESEARCH 🤝

Dr. Guido has actively collaborated on several influential studies, including investigations into the effects of dietary interventions in children with refractory epilepsy and the impact of COVID-19 on oncological care. His contributions to these studies reflect his commitment to advancing medical knowledge and improving patient outcomes. By working with multidisciplinary teams, he helps bridge gaps in research and practice, promoting innovative solutions in healthcare.

NOTABLE PUBLICATION

Title: Glycemic Index and Amylose Content of 25 Japonica Rice Italian Cultivar
Authors: M. Rondanelli, F. Haxhari, C. Gasparri, S. Feccia, S. Perna
Year: 2023
Journal: Starch/Staerke, 75(9-10), 2300031
Cited by: 1

Title: The Glycemic Index of Indica and Japonica Subspecies Parboiled Rice Grown in Italy and the Effect on Glycemic Index of Different Parboiling Processes
Authors: M. Rondanelli, R.A. Ferrario, G.C. Barrile, A. Tartara, S. Perna
Year: 2023
Journal: Journal of Medicinal Food, 26(6), pp. 422–427
Cited by: 0

Title: Discovering the Physio-Pathological Mechanisms of Interaction between Bone Mineral Density, Muscle Mass, and Visceral Adipose Tissue in Female Older Adults through Structural Equation Modeling
Authors: S. Perna, C. Gasparri, S. Allehdan, T.A. Alalwan, M. Rondanelli
Year: 2023
Journal: Journal of Clinical Medicine, 12(6), 2269
Cited by: 3

Title: Endosperm structure and Glycemic Index of Japonica Italian rice varieties
Authors: F. Haxhari, F. Savorani, M. Rondanelli, S. Perna, R. Magnaghi
Year: 2023
Journal: Frontiers in Plant Science, 14, 1303771
Cited by: 0

Title: Time-Trends in Air Pollution Impact on Health in Italy, 1990–2019: An Analysis From the Global Burden of Disease Study 2019
Authors: S. Conti, C. Fornari, P. Ferrara, L. Monasta, L.G. Mantovani
Year: 2023
Journal: International Journal of Public Health, 68, 1605959
Cited by: 5

Aminul Hoque – Computers in Biology – Best Researcher Award

Aminul Hoque - Computers in Biology - Best Researcher Award

University of Rajshahi - Bangladesh

CURRENT RESEARCH

Md. Aminul Hoque is a distinguished academic with a robust research portfolio spanning several domains. His current research interests encompass Bioinformatics, Medical Informatics, Telemedicine, Systems Biology, and Metabolomics. He delves into Biochemical Engineering and Bioprocess, focusing on Multivariate Analysis, Inferential Statistics, and Machine Learning. His expertise extends to Biostatistics, Bayesian Network Analysis, and Gene Clustering, with a special emphasis on Statistics related to Genetic Data Analysis, Gene Expression Data Analysis, Robust Regression Analysis, Time Series Analysis, and Forecasting. His work also includes Outlier Detection and Dynamic Simulation, contributing significantly to these fields.

EMPLOYMENT RECORDS

Md. Aminul Hoque has an impressive academic career, currently serving as a Professor in the Department of Statistics at the University of Rajshahi, Bangladesh, since August 2011. His previous roles include Adjunct Professor at Pundra University of Science and Technology, JSPS Post Doctoral Research Fellow at Niigata University Medical & Dental Hospital, and Visiting Professor at Tokyo University of Science. His postdoctoral research experience includes a tenure at the Institute of Biological Sciences, University of Malaya. His career began at the University of Rajshahi, where he progressed from Lecturer to Associate Professor.

PROFESSIONAL EXPERIENCE

With over 27 years of teaching and research experience, Md. Aminul Hoque has profoundly impacted undergraduate and graduate education in Statistics and Bioinformatics. His extensive professional background is highlighted by his roles in various prestigious institutions and his contributions to advancing the fields of bioinformatics and statistical sciences.

LANGUAGE SKILLS

Md. Aminul Hoque is proficient in Bangla, his mother tongue, and English, which he speaks, reads, writes, and understands excellently. He has average proficiency in Japanese and basic knowledge of Bahasa, showcasing his ability to engage in diverse academic and professional environments.

MEMBERSHIPS

He is an active member of several professional societies, including the Editorial Board of the Journal of Integrative Computational Biosciences and the International Society for Computational Biology. His leadership roles include serving as Vice President of the Bangladesh Bioinformatics and Computational Biology Association and the Bioinformatics Research Group in Rajshahi University. He is also a Joint Secretary of the Bangladesh Statistical Association and holds life memberships in various statistical and alumni associations.

FUNDS OBTAINED

Md. Aminul Hoque has successfully secured various research grants, including the Ministry of Science and Technology grant for studying the impact of Telemedicine in Bangladesh, and multiple grants from Rajshahi University and international scholarships. His notable funding includes the JSPS Post Doc Research Fellowship, University of Malaya Post Doctoral Research Fellowship, and several scholarships and grants from Japan, demonstrating his ability to attract and manage research resources.

ACHIEVEMENTS

His career is marked by significant achievements, including prestigious fellowships and scholarships from leading institutions. His research contributions and academic roles reflect his dedication to advancing knowledge in bioinformatics, medical informatics, and statistical sciences, reinforcing his reputation as a leading figure in his field.

NOTABLE PUBLICATIONS

scHD4E: Novel Ensemble Learning-Based Differential Expression Analysis Method for Single-Cell RNA-Sequencing Data.

Authors: Biswas, B., Kumar, N., Sugimoto, M., Hoque, M.A.
Year: 2024
Journal: Computers in Biology and Medicine


Socioeconomic Inequality and Urban-Rural Disparity of Antenatal Care Visits in Bangladesh: A Trend and Decomposition Analysis.

Authors: Biswas, B., Kumar, N., Rahaman, M.M., Das, S., Hoque, M.A.
Year: 2024
Journal: PLoS ONE


Title: Securing Vehicle-to-Drone (V2D) Communications: Challenges and Solutions.

Authors: Islam, S.M.R., Hoque, M.A., Hossain, M.
Year: 2024
Book Title: Wireless Networks


Title: Weighted Scaling Approach for Metabolomics Data Analysis.

Authors: Biswas, B., Kumar, N., Hoque, M.A., Alam, M.A.
Year: 2023
Journal: Japanese Journal of Statistics and Data Science


Title: Someone to Watch Over You: Using Bluetooth Beacons for Alerting Distracted Pedestrians.

Authors: Hasan, R., Hoque, M.A., Karim, Y., Schwebel, D.C.
Year: 2022
Journal: IEEE Internet of Things Journal

Leyli Mohammad Khanli – Studying the three-dimensional structure of proteins – Best Researcher Award

Leyli Mohammad Khanli - Studying the three-dimensional structure of proteins - Best Researcher Award

University of Tabriz - Iran

AUTHOR PROFILE

SCOPUS
ORCID
GOOGLE SCHOLAR

PROFESSIONAL EMPLOYMENT

Leyli Mohammad Khanli is a highly esteemed Professor in the Department of Computer Engineering at the University of Tabriz, where she has been serving since 2020. She previously held positions as an Associate Professor from 2012 to 2020 and as an Assistant Professor in the Department of Computer Science from 2007 to 2012 at the same institution. Her academic journey at the University of Tabriz has been marked by significant contributions to the fields of computer science and engineering.

RESEARCH INTERESTS

Prof. Khanli's research interests are broad and include Cloud Computing, Network Security, Artificial Intelligence, Intrusion Detection, Computer Networks, and Information Systems. Her work has contributed to advancements in these areas, addressing both theoretical and practical challenges in modern computing and security.

UNDER-REVIEW ARTICLES

Prof. Khanli has several under-review articles, showcasing her ongoing research endeavors. These include "A Fast Multi-network k-Dependency Bayesian Classifier for Continuous Features" and "ACQC-LJP: Apollonius Circle-based Quantum Clustering using Lennard-Jones Potential," both submitted to the Pattern Recognition Journal. Additionally, she has work under review in the International Journal of Intelligent Engineering and Systems and Knowledge-based Systems, demonstrating her active engagement in cutting-edge research.

ARTICLES IN PROGRESS

Her current articles in progress include "Fuzzy Modeling of the Individual Behaviors Tendency based on the Cloninger’s Personality Theory," "Increasing Chatbot’s Context-Dependent Grasping, through Cloninger's Planes of Being Theory," and "Investigating the Relationship between the Dissemination of Neuronal Signals and Modeling the Spread of Memes in Social Networks." These projects highlight her innovative approach to integrating psychological theories and computational models.

MASTER AND DOCTORATE THESIS SUPERVISION

Prof. Khanli has supervised numerous master's and doctorate theses, guiding students through complex research projects. Notable theses include "Nonparametric Bayesian Network for Classifying Non-Stationary Data Streams" by Imaneh Khodayari, "A Novel Facial Expression Recognition Algorithm using Geometry B-Skeleton in Fusion based on Deep CNN" by Abbas Issa Jabbooree, and "Adaptive Neighborhood Bandwidth Detection of Gaussian Kernel in Quantum Clustering using the Apollonius Circle" by Nasim Abdolmaleki. Her mentorship has been instrumental in shaping the careers of many researchers.

CONFERENCE PRESENTATIONS

Prof. Khanli has presented her research at various international conferences. Recent presentations include "Automatic Clustering by Geometric Method of Tangent Lines with Points" and "Increasing Artificial Intelligence’s Context-Dependent Grasping, through Cloninger's Planes of Being Theory" at the 7th International Symposium on Innovative Approaches in Smart Technologies. She has also presented at the International Conference on Communication and Signal Processing in Montreal, Canada, and the International Conference on Computer Science, Communication, and Information Technology in Tbilisi, Georgia, among others.

NOTABLE PUBLICATION

Survey on prediction models of applications for resources provisioning in cloud 2017 (235)

EE-CTA: Energy efficient, concurrent and topology-aware virtual network embedding as a multi-objective optimization problem 2019 (34)

A survey of neighborhood construction algorithms for clustering and classifying data points 2020 (29)

An edge computing matching framework with guaranteed quality of service 2020 (26)