Ziyang Jiao | Computer Science | Best Researcher Award

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Assist. Prof. Dr. Ziyang Jiao | Computer Science | Best Researcher Award

Huaibei Normal University | China

Dr. Ziyang Jiao is an Assistant Professor in the Department of Computer Science and Technology at Huaibei Normal University. He earned his Ph.D. in Computer & Information Science & Engineering from Syracuse University, USA. His research centers on file and storage systems, solid-state drives (SSDs), operating systems, and sustainable computing, contributing significantly to the advancement of efficient and eco-friendly data management technologies. Dr. Jiao has completed five major research projects and collaborated with leading institutions such as Syracuse University, Florida International University, Samsung Electronics, and Dankook University. His scholarly impact includes 28 citations, an h-index of 3, and 13 indexed research documents as per Scopus. He has published one peer-reviewed journal article and holds two patents under process. His pioneering work introduced the concept of asymmetric and heterogeneous RAID (paRAID) and explored capacity-variant systems for dynamic storage optimization. Recognized for his excellence, Dr. Jiao received the ACM Best Paper Award, the Best Presented Research Award, and the All-University Doctoral Award. A member of USENIX, ACM, IEEE, and ASEE, he continues to shape next-generation green computing and sustainable storage architectures.

Profile: Scopus 

Featured Publications 

Jiao, Z., & Kim, B. S. (2022). Asymmetric RAID: Rethinking RAID for SSD heterogeneity. In Proceedings of the ACM Symposium on Storage Systems

Riyadh Hossain | Data Science | Excellence in Research Award

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Mr. Riyadh Hossain | Data Science | Excellence in Research Award

Mr. Riyadh Hossain, Noakhali Science and Technology University, Bangladesh.

Mr. Riyadh Hossain is a dedicated researcher and data scientist specializing in public health statistics and epidemiological research. He holds a BSc and MSc in Statistics from Noakhali Science and Technology University, Bangladesh. His work focuses on child health, disease modeling, and machine learning applications in healthcare. He has published in reputed journals like BMC Public Health and Taylor & Francis and received the National Science & Technology Fellowship. He is also a reviewer for international journals and an active research instructor.

Profile

SCOPUS ID

Early Academic Pursuits

Mr. Riyadh Hossain demonstrated academic excellence from the outset of his educational journey. He completed his Secondary School Certificate (SSC) in 2014 from Chatkhil P.G Govt High School and his Higher Secondary Certificate (HSC) in 2016 from Govt Science College, Dhaka.. Continuing his education at Noakhali Science and Technology University (NSTU), he earned a Bachelor’s degree in Statistics in 2023.  His academic journey culminated with an ongoing Master’s in Statistics, where he currently holds a CGPA of 3.76, reflecting consistent academic dedication and performance.

Professional Endeavors

Mr. Hossain has steadily built a dynamic professional portfolio in both teaching and applied research. Since January 2024, he has served as a Data Scientist, working on time series modeling, coding in R and Python, and health insurance data prediction. Earlier, as an Instructor (2023–2024), he delivered live sessions on Research Methodology and Machine Learning. His experience includes serving as a Research Assistant (2021–2025) at NSTU, focusing on child health and cluster randomized trials. Additionally, in 2019–2020, he worked as a Statistician at Eusuf & Associates, refining his skills in data cleaning, documentation, and report writing.

Contributions and Research Focus On Data Science

Mr. Hossain’s research portfolio reflects a commitment to public health and statistical modeling. His Master’s thesis investigates the determinants of child physical health development in Bangladesh, employing non-parametric techniques to examine the influence of socioeconomic and demographic factors. His research extends to dengue fever spread in the USA, machine learning applications in cardiovascular disease prediction, and studies on malnutrition, mental health, and low birth weight. His commitment to statistical application in health sciences is evident in both published and under-review manuscripts.

Impact and Influence

Through his research and teaching, Mr. Hossain has made a meaningful impact on statistical education and public health research. His work, cited in prominent journals such as BMC Public Health and Taylor & Francis, addresses critical societal issues like environmental health and child development. He actively contributes to global health awareness as a technical volunteer at UNICEF Bangladesh and a member of Statistics without Borders, emphasizing social responsibility and scientific integrity.

Research Skills

Mr. Hossain possesses robust research skills in both theoretical and applied statistics. He is adept in Python, SPSS, R, and STATA, and well-versed in time series analysis, hypothesis testing, multivariate analysis, and machine learning. His training includes online certifications from Duke, Rice, and Imperial College London, reinforcing his capabilities in data analysis and public health statistics. His analytical strength is complemented by his ability to translate data into actionable insights, particularly in the health and development sectors.

Awards and Honors

In recognition of his academic and research excellence, Mr. Hossain received the National Science & Technology Fellowship (2023) from the Ministry of Science and Technology, Government of Bangladesh, and the NSTU Research Cell Project Award (2024) for joint research collaboration. These accolades underscore his dedication to research innovation and his potential for significant future contributions in statistical and health sciences.

Academic Citations

Mr. Hossain has authored and co-authored several peer-reviewed publications in international journals, including BMC Public Health, Discover Mental Health, BMC Cardiovascular Disorders, and more. His citations are steadily growing, particularly on studies addressing child health, environmental epidemiology, and machine learning in disease prediction. His work has attracted attention for its relevance, methodology, and real-world applications, positioning him as a rising academic in biostatistics and public health.

Legacy and Future Contributions

Mr. Hossain is poised to become a leading contributor in statistical health research, with ambitions to influence evidence-based policy and data-driven healthcare planning. His ongoing commitment to scientific integrity, social advocacy, and academic collaboration ensures that his work will continue to advance public health statistics in Bangladesh and globally. Through his academic mentorship, international collaborations, and innovative research, he is building a lasting legacy of knowledge, service, and impact.

Publications Top Notes

Determinants of Child Physical Health Development in Bangladesh: A Study of Key Socioeconomic and Cultural Influences

Authors: Riyadh Hossain, Mohammad Omar Faruk & Najma Begum
Journal: BMC Public Health (2025), Volume 25, Article 2447

Impact of Environmental Factors on the Spread of Dengue Fever in the United States of America (USA)

Authors: Riyadh Hossain, Tahmina Akter, Mohammad Omar Faruk, Sorif Hossain & Md Rasel Hossain
Journal: International Journal of Environmental Health Research (online ahead of print, July 2025)

Machine Learning Approach to Predict Cardiovascular Disease in Bangladesh: Evidence from a Cross‑Sectional Study in 2023

Authors: Sorif Hossain, Mohammad Kamrul Hasan, Mohammad Omar Faruk, Nelufa Aktar, Riyadh Hossain & Kabir Hossain
Journal: BMC Cardiovascular Disorders (2025)

Malnutrition and Its Associated Factors among Children under Five: A Case Study of the Chattogram Division

Authors: Riyadh Hossain, Shahinoor Jamal Muna & Nusrat Jahan Onu
Journal: Food and Nutrition Sciences (2025)

Impact of Socio‑economic, Demographic and Cultural Factors on the Development of Children’s Mental Health: A Cross‑Sectional Study in Bangladesh

Authors: Sarmin Akhter, Riyadh Hossain & Mohammad Omar Faruk
Journal: Discover Mental Health (2025)

Nikolay M. Sirakov | Data Science | Excellence in Research Award

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Prof. Nikolay M. Sirakov | Data Science | Excellence in Research Award

Prof. Nikolay M. Sirakov, East Texas A&M University, Dept. Mathematics, United States.

Nikolay Metodiev Sirakov is a Professor of Mathematics at East Texas A&M University 🏫, specializing in pattern recognition, machine learning, and mathematical modeling 🔬. With a Ph.D. from the Bulgarian Academy of Sciences 🎓, his research spans image processing, artificial intelligence, and biomedical applications 🧠. He has collaborated with leading global institutions 🌍 and supervised numerous Ph.D. and Master’s students 📚. His contributions to computer vision and AI-driven diagnostics 🤖 have earned him international recognition. ✨

🌟 Professional Profile

🎓 Early Academic Pursuits

Nikolay Metodiev Sirakov’s academic journey began with rigorous training at Bulgaria’s top institutions, including the Bulgarian National High School of Mathematics and CS. He pursued undergraduate studies at Sofia University, earning his B.S. in Mathematics and Computer Science. He went on to complete his Master’s in Coding Theory at Sofia University and later obtained his Ph.D. from the Bulgarian Academy of Sciences, specializing in Pattern Recognition.

💼 Professional Endeavors

Sirakov has held various prestigious academic positions, including professor and associate professor at Texas A&M University-Commerce since 2004. He also served as a senior researcher and invited professor at institutions like Instituto Superior Tecnico, Lisbon, and Northern Arizona University. His leadership includes chairing committees and collaborating with diverse institutions globally.

🔬 Contributions and Research Focus On Data Science 

Sirakov’s research spans machine learning, image processing, and biomedical applications, with significant contributions to skin cancer diagnosis, tracking objects in video, and automatic threat detection. He has led multiple international collaborations, publishing numerous peer-reviewed papers and advancing computational techniques, particularly in sparse representation and neural network

🌍 Impact and Influence

With his vast expertise, Sirakov has influenced fields such as medicine, security, and robotics, making a profound impact on medical imaging and biomechanics. His work in automated melanoma diagnosis has gained recognition in the medical community, while his contributions to video object tracking and image segmentation remain highly influential in computer vision.

🏆 Awards and Honors

  • Best Paper Award – Oluwaseyi Igbasanmi, Nikolay M. Sirakov, and Adam Bowden were recognized for their paper, CNN for Efficient Objects Classification with Embedded Vector Fields, presented at ICCIDA2023 and published in the Springer book series. 📚

  • 2nd Place Winner in Mathematics – Elisha Shachar received recognition for the project on An Artificial Intelligence-Based Driving Environment Descriptor: Voice Alerts to Drivers at the 15th TAMU System Pathway Students Symposium. 🚗

  • 1st Place Winner in Mathematics – Mengzhe Chen, supervised by Nikolay Sirakov, presented Singular Points of the Gradient Field of the Poisson Partial Differential Equation Solution on an Image at the TAMU System Pathway Students Symposium. 🔢

  • Lockheed Martin Best Paper Award – Awarded to a team for their paper, From Shape to Threat: Exploiting the Convergence Between Visual and Conceptual Organization for Weapon Identification and Threat Assessment. 🎖

🚀 Legacy and Future Contributions

Sirakov’s legacy is built on his innovative contributions to computational science and biomedical engineering. Looking ahead, his continued work in machine learning and medical applications promises to influence the next generation of scientific advancements in healthcare technologies and security systems.

📚Publications Top Notes

  • A system for reconstructing and visualizing three-dimensional objects
    Citations: 70 📊
    Year: 2001 🗓️

  • Lesion detection in dermoscopy images with novel density-based and active contour approaches
    Citations: 51 📈
    Year: 2010 🩺

  • A new active convex hull model for image regions
    Citations: 36 📐
    Year: 2006 🔍

  • Dermoscopic diagnosis of melanoma in a 4D space constructed by active contour extracted features
    Citations: 35 💡
    Year: 2012 🧑‍⚕️

  • Interpolation approach for 3D smooth reconstruction of subsurface objects
    Citations: 34 🌍
    Year: 2002 🖥️

  • Automatic boundary detection and symmetry calculation in dermoscopy images of skin lesions
    Citations: 30 🔬
    Year: 2011 🧠

  • Efficient segmentation with the convex local-global fuzzy Gaussian distribution active contour for medical applications
    Citations: 26 💉
    Year: 2015 📊

  • Intelligent shape feature extraction and indexing for efficient content-based medical image retrieval
    Citations: 26 🔍
    Year: 2004 🏥

  • Recognition of emotional states in natural human-computer interaction
    Citations: 23 😐
    Year: 2008 🤖

  • An integral active contour model for convex hull and boundary extraction
    Citations: 22 🏞️
    Year: 2009 🔧

  • Threat assessment using visual hierarchy and conceptual firearms ontology
    Citations: 19 🔫
    Year: 2015 🚨

  • Search space partitioning using convex hull and concavity features for fast medical image retrieval
    Citations: 19 🔎
    Year: 2004 🏥

  • Optimal set of features for accurate skin cancer diagnosis
    Citations: 18 🩺
    Year: 2014 🧬

  • Skin lesion feature vectors classification in models of a Riemannian manifold
    Citations: 17 🏥
    Year: 2015 🔬

  • Automatic feature extraction and recognition for digital access of books of the Renaissance
    Citations: 15 📚
    Year: 2000 🔍

  • Sparse representation wavelet-based classification
    Citations: 11 🖼️
    Year: 2018 💻

  • A novel classification system for dysplastic nevus and malignant melanoma
    Citations: 11 🩺
    Year: 2016 🌟

  • New accurate automated melanoma diagnosing systems
    Citations: 11 🧬
    Year: 2015 ⚕️

  • Weapon ontology annotation using boundary describing sequences
    Citations: 11 🔫
    Year: 2012 🛡️

  • Active contour directed by the Poisson gradient vector field and edge tracking
    Citations: 10 🖥️
    Year: 2021 📉

  • Comparing 2D borders using regular structures
    Citations: 10 🔍
    Year: 1994 🖼️

  • Support vector machine skin lesion classification in Clifford algebra subspaces
    Citations: 9 🩺
    Year: 2019 📈

  • Poisson equation solution and its gradient vector field to geometric features detection
    Citations: 9 🔬
    Year: 2018 🔧

  • Integration of low-level and ontology-derived features for automatic weapon recognition and identification
    Citations: 9 🛡️
    Year: 2011 💡

  • Monotonic vector forces and Green’s theorem for automatic area calculation
    Citations: 9 🔍
    Year: 2007 📐

  • A new automatic concavity extraction model
    Citations: 9 🔍
    Year: 2006 🧠

  • Classification with stochastic learning methods and convolutional neural networks
    Citations: 8 🤖
    Year: 2020 💻

  • From shape to threat: exploiting the convergence between visual and conceptual organization for weapon identification and threat assessment
    Citations: 8 🔫
    Year: 2013 🛡️

  • Skin lesion image classification using sparse representation
    Citations: 8 🩺
    Year: 2018 📊