Chengyuan Zhang | Computer Science | Best Research Article Award

Published on by Citation Awards

Chengyuan Zhang | Computer Science | Best Research Article Award

Chengyuan Zhang, Hunan University, China

Dr. Chengyuan Zhang, born in October 1985 in Suining County, Hunan, is an Associate Professor and Ph.D. Supervisor at the College of Computer Science and Electronic Engineering, Hunan University. He also serves as a Guest Professor at the College of Information and Intelligence, Hunan Agricultural University. Dr. Zhang earned his Ph.D. in Computer Science from the University of New South Wales, where he also completed his master’s studies under the guidance of Professors Xuemin Lin and Wenjie Zhang. His professional experience includes academic roles in both China and Australia, notably as a postdoctoral researcher. With nearly 40 SCI-indexed publications and over 1,300 citations, he is widely recognized in the domains of multimedia computing, spatio-temporal data analysis, and machine learning. Dr. Zhang is a frequent reviewer for top-tier journals and has contributed to numerous national and provincial-level research projects. He holds editorial and committee roles in several internationally recognized journals and conferences.

Publication Profile

scopus

Education

Dr. Chengyuan Zhang began his academic journey in Software Engineering at Sun Yat-sen University, earning his bachelor’s degree in 2008. He then advanced to the University of New South Wales (UNSW), one of Australia’s leading research institutions, where he obtained a master’s degree in Computer Science in 2011. His academic excellence led him to pursue a Ph.D. in Computer Science at UNSW from July 2011 to December 2015. During his doctoral studies, he worked under the mentorship of esteemed professors Xuemin Lin and Wenjie Zhang. His research during this period laid the groundwork for his future academic contributions in data mining, multimedia computing, and spatio-temporal data processing. The international education experience at UNSW not only honed his technical expertise but also equipped him with a global research perspective and collaborative mindset, helping him transition smoothly into high-impact academic roles upon returning to China.

Experience

Dr. Chengyuan Zhang currently holds the position of Associate Professor and Deputy Director in the Department of Computer Science at Hunan University. He joined the university in December 2019 and assumed his deputy directorship in November 2023. Previously, he served as a Lecturer at the College of Information Science and Engineering at Central South University from 2016 to 2019. His international experience includes a one-year postdoctoral research position at the University of New South Wales from 2015 to 2016, where he continued his research on large-scale data processing. Over the years, Dr. Zhang has participated in and led various nationally funded projects, especially in multimedia, graph data analysis, and AI-driven spatio-temporal applications. He also contributes significantly to the academic community as an editor and reviewer for top journals such as IEEE TKDE, ACM TOIS, and IEEE TNNLS. His career reflects a balanced combination of research innovation, teaching, and academic leadership.

Awards and Honors

Dr. Chengyuan Zhang has received several recognitions for his scholarly contributions, including the Outstanding Reviewer Award from Pattern Recognition Letters, which highlights his dedication to academic quality and peer review. He serves as Academic Editor for Advances in Multimedia and as a Guest Editor for prestigious journals such as Multimedia Tools and Applications and Mathematics. Dr. Zhang has also contributed as a Reviewer for top-tier academic journals including IEEE TPAMI, IEEE TNNLS, IEEE TKDE, ACM TOIS, and ACM TOMM. In addition, he has served as a Program Committee Member for leading international conferences such as ACM Multimedia and IJCAI-PRICAI. These roles are a testament to his academic credibility and recognition within the global research community. His grant-winning research and participation in national foundations reflect his active role in shaping future advancements in multimedia, data mining, and artificial intelligence.

Research Focus

Dr. Chengyuan Zhang’s research centers on multimedia computing, spatio-temporal multi-modal data analysis, image processing, graph data analysis, and machine learning. His work aims to address complex challenges related to information retrieval, representation learning, and knowledge discovery from large-scale, heterogeneous datasets. Specifically, he focuses on designing efficient algorithms for spatio-temporal queries, cross-modal hashing retrieval, and dynamic image enhancement techniques. His research often integrates deep learning, graph theory, and semantic correlation mining, contributing to both theoretical advancements and real-world applications—especially in areas like intelligent agriculture, social recommendation systems, and wireless sensor networks. With support from multiple National Natural Science Foundation of China (NSFC) grants and Hunan provincial research programs, his work is recognized as both innovative and impactful. He has published nearly 40 papers in top journals and conferences such as IEEE TKDE, ACM TOIS, and ACM TOMM, earning over 1,300 citations and an H-index of 18.

Publication Top Notes

  1. 📖 MvHAAN: Multi-view hierarchical attention adversarial network for person re-identification – World Wide Web, 2024

  2. 📖 Bi-Direction Label-Guided Semantic Enhancement for Cross-Modal Hashing – IEEE TCSVT, 2024

  3. 🖼 Using CNN with Multi-Level Information Fusion for Image Denoising – Electronics, 2023

  4. 🖼 Adaptive Dynamic Shuffle Convolutional Parallel Network for Image Super-Resolution – Electronics, 2024

  5. 📷 Efficient Feature Redundancy Reduction for Image Denoising – World Wide Web, 2024

  6. 🔍 Efficient Maximal Biclique Enumeration on Large Uncertain Bipartite Graphs – IEEE TKDE, 2023

  7. 🔍 Efficient Maximum Edge-Weighted Biclique Search on Large Bipartite Graphs – IEEE TKDE, 2022

  8. 🤖 Robust Sparse Weighted Classification for Crowdsourcing – IEEE TKDE, 2022

  9. 🌐 Multi-Graph Heterogeneous Interaction Fusion for Social Recommendation – ACM TOIS, 2022

  10. 🌐 Scaling High-Quality Pairwise Link-Based Similarity Retrieval on Billion-Edge Graphs – ACM TOIS, 2022

 

Emmanouil Zoulias | Computer Science | Best Researcher Award

Published on by Citation Awards

Emmanouil Zoulias | Computer Science | Best Researcher Award

Dr Emmanouil Zoulias, Department of Nursing, National and Kapodistrian University of Athens, NKUA, Greece

Emmanouil A. Zoulias is a highly experienced electrical and computer engineer with specialization in health informatics and biomedical technology. Born on May 25, 1973, he currently serves as a Laboratory Teaching Staff member at the Faculty of Nursing, School of Health Sciences, National and Kapodistrian University of Athens 🇬🇷. His academic journey and professional career reflect a unique blend of technical expertise and medical application, with a strong foundation in medical informatics. A PhD holder with research experience in advanced data mining methods for medical diagnostics, Dr. Zoulias is known for his contributions to digital health systems, telemedicine, and biomedical engineering. He is an active member of notable professional bodies such as the IEEE, the Greek Biomedical Informatics Association, and the National Technical Chamber of Greece. Emmanouil is a team player, lifelong learner, and passionate educator with a vision to advance healthcare technologies for better patient outcomes. 🧠💻📊

Publication Profile

google scholar

Education

Emmanouil Zoulias holds a PhD in Biomedical Informatics (2012) from the National Technical University of Athens and the Medical School of the University of Patras. His doctoral thesis focused on developing a decision-support system for diagnosing thyroid smears using advanced data mining techniques 🔬📈. He also earned an MSc in Biomedical Instrumentation Engineering (1997) from the University of Dundee, UK, where he studied medical equipment, signal measurements, and imaging systems, completing a dissertation on telemetry systems in anesthesia monitoring 🏥📡. He began his academic journey with a Diploma in Electrical & Computer Engineering (1996) from the National Technical University of Athens, with a specialization in electronics, telecommunications, and computing systems ⚙️💡. His diploma project involved designing data management tools for telemedicine databases. Emmanouil’s academic path demonstrates a consistent commitment to integrating engineering with healthcare innovation. 📚🔧🩺

Experience

Emmanouil Zoulias has over two decades of diverse experience in health informatics, biomedical systems, and IT engineering. Since January 2020, he has been part of the Laboratory Teaching Staff at the National and Kapodistrian University of Athens, teaching Biomedical and Health Informatics 🧑‍🏫💡. Previously, he served as a Computer Engineer (2008–2018) at the National Centre of Public Administration and Local Governance. His earlier roles include IT Engineer at the 1st Regional Health Care System (2004–2008), Electronic Engineer at ISAP S.A. for urban railway signaling (2003–2004), and Project Manager at ANKO S.A. (2002–2003). He also worked as Research Manager at the National Centre for Scientific Research “Demokritos” (2000–2002), contributing to EU-funded projects 🌍📊. Emmanouil’s multidisciplinary expertise spans public health, telemedicine, traffic systems, and biomedical research. His career showcases a dynamic integration of technical problem-solving and public service impact. 🧪🖥️🔌

Awards and Honors

While no individual honors or awards were specifically listed in the CV, Emmanouil Zoulias’ recognition can be seen through his active membership in prestigious professional associations and his long-standing contributions to both academia and public service. He became a member of the National Technical Chamber of Greece in 1997 🏛️, reflecting his early professional credibility. In 2017, he joined the Hellenic Unit of Biomedical Instrumentation, followed by membership in the IEEE in 2018, acknowledging his alignment with global standards in engineering excellence 🌐🔧. Most recently, in 2020, he joined the Greek Biomedical Informatics and Health Informatics Association, recognizing his growing influence in medical data systems and informatics innovation 💻🔍. His consistent engagement with interdisciplinary fields and national organizations is a testament to his respected status in the Greek engineering and health informatics community.

Research Focus

Dr. Emmanouil Zoulias’ research centers on the integration of health informatics, biomedical instrumentation, and advanced computational methods in medical diagnostics 🧠💾. His PhD research pioneered the use of data mining techniques for supporting diagnostic decisions in thyroid FNA smears, demonstrating his vision for intelligent, automated healthcare solutions. His broader interests encompass telemedicine systems, signal processing, biomedical device development, and clinical information management systems 📊🩺. Through his academic and professional roles, he continues to explore how technology can improve patient monitoring, diagnostic accuracy, and healthcare delivery. As a university instructor, Emmanouil promotes interdisciplinary knowledge that merges medical science with informatics, aiming to equip future healthcare professionals with the tools to navigate a tech-driven clinical environment. His work stands at the intersection of engineering, computer science, and medicine, targeting innovations that enhance both individual care and public health infrastructures ⚙️💡🌍.

Publication Top Notes

  • Forecasting transmission and distribution system flexibility needs for severe weather condition resilience and outage management. 🌩️📉🔌📊

  • Active System Management Approach for Flexibility Services to the Greek transmission and distribution system. 🇬🇷⚙️🔋📡

  • Introducing maker movement in educational robotics: beyond prefabricated robots and “black boxes”. 🤖🎓🔧📚

  • Computer-aided diagnosis of thyroid malignancy using an artificial immune system classification algorithm. 🧠💻🧬🔍

  • A flexibility platform for managing outages and ensuring the power system’s resilience during extreme weather conditions. 🌪️🔌🛠️📈

  • Development and implementation of a flexibility platform for active system management at both transmission and distribution level in Greece. 🏗️📊🇬🇷🔋

  • Impacts of robotic assisted surgery on hospital’s strategic plan. 🏥🤖📈📋

  • The route to patient safety in robotic surgery. 🛡️🧑‍⚕️🤖❤️

  • A review of techniques to counter spam and spit. 📧🚫🕵️‍♂️🔐

  • Organization Style and Its Effect on Employee Satisfaction and Personal Performance. 🏢😊📈👥

 

 

 

Pedro Stalyn Aguilar Encarnacion | Computer Science | Best Research Article Award

Published on by Citation Awards

Pedro Stalyn Aguilar Encarnacion | Computer Science | Best Research Article Award

Prof Pedro Stalyn Aguilar Encarnacion, Escuela Superior Politécnica de Chimborazo, Ecuador

Pedro Stalyn Aguilar Encarnación 🇪🇨 is an experienced software engineer, researcher, and educator currently serving as a professor at the Escuela Superior Politécnica de Chimborazo (ESPOCH). With a strong foundation in programming and systems development, he integrates technical expertise with business acumen, holding an MBA alongside advanced degrees in Software Engineering. His academic journey reflects a commitment to innovation and excellence, culminating in his ongoing PhD in Computer Science. Pedro has contributed significantly to the academic community through impactful research in artificial intelligence, software engineering, and web technologies. Passionate about empowering future IT professionals, he actively participates in research projects and international conferences. He is known for developing intelligent platforms for environmental monitoring and sustainable agriculture. His diverse experiences in academia and industry, paired with leadership in research, make him a dynamic figure in Ecuador’s tech-education landscape.

Publication Profile

google scholar

Education

Pedro Aguilar holds multiple degrees in Information Technology and Business. He earned his Bachelor’s Degree in Computer Systems Engineering from the Escuela Superior Politécnica de Chimborazo in 2018. He later pursued a Master’s in Software from the Universidad Técnica de Machala, graduating in 2023. To complement his technical skills with business strategy, he obtained a Master in Business Administration (MBA) from the Universidad Internacional de La Rioja, Spain, in 2024. Continuing his academic excellence, he is currently a PhD candidate in Computer Science at the Escuela Politécnica Nacional as of 2024. His formal education is further enhanced by certifications in English proficiency (B1), leadership, talent management, and organizational culture from institutions such as MIU City University Miami, Universidad Nacional de Chimborazo, SETEC, and IECAP. This diverse educational background reflects his dual focus on technical innovation and strategic management in the digital age.

Experience

Pedro Aguilar’s professional journey spans both the private sector and academia. He began his career as a Hardware and Software Technician at TEINCORP (2009–2011) and then served as a Full Stack Developer at CYMOGSYS in 2017. His work in academia began in 2018 at ESPOCH, where he held various roles such as IT Support Analyst, Registration Analyst, and currently serves as a Professor and Researcher since April 2023. His teaching covers programming, mobile computing, and web technologies, shaping the next generation of software engineers. Pedro’s experience is also deeply rooted in research and innovation, leading projects that use smart technologies like IoT and Progressive Web Apps. His interdisciplinary approach—blending IT systems with real-world applications like agriculture and water monitoring—demonstrates his commitment to socially impactful solutions. With over 5 years in academia and multiple years in industry, Pedro has developed a well-rounded, hands-on approach to technology and education.

Awards and Honors

Pedro Aguilar has earned multiple recognitions for his academic involvement and leadership. He was acknowledged by ESPOCH as a Reviewer at the II International Congress on Innovation, Science, and Technology (May–Nov 2023), reflecting his contributions to scientific quality and peer evaluation. He also received certifications in Leadership and Training from SETEC and MIU City University Miami, recognizing his ability to lead and inspire teams in technological and educational settings. His English language proficiency (B1) was certified by the Universidad Nacional de Chimborazo, supporting his active participation in international collaborations. In addition, he completed over 180 hours of certified training in areas like diversity, inclusion, human resources, organizational well-being, and corporate image—enhancing his ability to lead educational and research projects with a human-centered focus. While his academic and research achievements shine, his consistent pursuit of self-improvement stands as a testament to his professional excellence.

Research Focus

Pedro Aguilar’s research focus lies at the intersection of Software Engineering, Artificial Intelligence, and Information Systems for societal applications. His projects are strongly rooted in smart agriculture, environmental monitoring, and IoT systems, addressing real-world challenges through data-driven platforms. Notably, he contributed to the creation of a Predictive Platform for Cocoa Moniliasis Detection using sensors and AI, benefiting Ecuadorian agricultural zones. Currently, he is involved in developing an Intelligent Geoportal to monitor potable water quality using IoT technologies. Pedro is particularly interested in Progressive Web Applications (PWAs) and machine learning models to improve decision-making in critical sectors. His work integrates semantic web technologies, mobile computing, and vehicular networks (VANETs) to create scalable, sustainable digital solutions. With publications in international high-impact journals and conference proceedings, his research continues to evolve with emerging technologies while staying aligned with sustainable development and technological equity in Latin America.

Publication Top Notes

  • 🧠 Desarrollo de un modelo predictivo utilizando técnicas de aprendizaje supervisado para detectar la moniliasis en plantas de cacao de la Provincia de Orellana

  • 🌱 Fighting moniliasis in Orellana with sensors and PWA for sustainable agriculture

  • 🌾 Prevention of cocoa moniliasis using Progressive Web Applications and sensor data in the province of Francisco de Orellana

  • 📊 Predictive Model in Production through Progressive Web Applications to Forecast Moniliasis in Cacao

  • 🚗 Vehicular Ad-Hoc Network (VANET)

Ahmad Yahya Dawod | Computer Science | Academic Excellence Citation Award

Published on by Citation Awards

Assist. Prof. Dr. Ahmad Yahya Dawod | Computer Science | Academic Excellence Citation Award

Assist. Prof. Dr. Ahmad Yahya Dawod, Chiang mai University, Thailand

Assist. Prof. Dr. Ahmad Yahya Dawod is a lecturer at the International College of Digital Innovation (ICDI) at Chiang Mai University (CMU), Thailand. He holds a bachelor’s degree in Computer Science from Al-Mustansiriya University, Iraq (2006), a master’s degree in Computing and Informatics from Multimedia University (MMU), Malaysia (2012), and a Ph.D. from the Faculty of Information Science and Technology at the National University of Malaysia (UKM) (2018). His research focuses on Artificial Intelligence, Machine Learning, Pattern Recognition, Computer Vision, Medical Image Analysis, Image Processing, Robotics, Sign Language Recognition, and Natural

Education

Assistant Professor Dr. Ahmad Yahya Dawod has a rich academic background with a strong focus on computer science and technology. He earned his Doctor of Philosophy (Ph.D.) degree from the National University of Malaysia (UKM), Faculty of Information Science and Technology, in May 2018. His doctoral research, titled “Hand Gesture Recognition Based on Isolated and Continuous Sign Language,” was supervised by Assoc. Prof. Dr. Md. Jan Nordin. Prior to this, he completed his Master’s degree (M.Sc.) at Multimedia University (MMU) in Malaysia in May 2013. His thesis, “Hand and Fingertip Detection Based on Free-Form Color Model,” was supervised by Dr. Junaidi Abdullah at the Faculty of Computing and Informatics. Dr. Dawod began his academic journey by obtaining a Bachelor’s degree (B.Sc.) in Computer Science from The University of Mustansirya in Iraq in July 2006, graduating with a commendable GPA of 3.18.

Professional Profiles

ORCID Profile

Google Scholar

Scopus Profile

Teaching Experience

Assistant Professor Dr. Ahmad Yahya Dawod is a distinguished academic and lecturer at Chiang Mai University International College of Digital Innovation in Thailand, where he has been teaching since February 15, 2019. With extensive experience in higher education, Dr. Dawod has taught a variety of courses to both undergraduate and master’s students. For master’s students, he delivers advanced courses such as Artificial Intelligence and Machine Learning for Digital Business and Research Methodology, teaching 6 hours weekly for each course to groups of 20–25 students. At the undergraduate level, he engages in teaching a wide range of subjects, including Communication, Digital Platforms, Networking in Online Society, Internet of Things (IoT), Internet Databases Systems, Internet Programming Language, Big Data, and Information Management Systems, often handling class sizes ranging from 50 to 150 students and dedicating 8–12 hours weekly per course.

Before joining Chiang Mai University, Dr. Dawod taught at Al-Maaref University College from 2013 to 2015, covering subjects such as Artificial Intelligence, Digital Images, Video Processing, Human-Computer Interaction, and Image Processing for classes of 30–40 students. His teaching career began at the University of Mosul, where, as a tutor in the College of Computer Science and Mathematics (2006–2009), he specialized in image processing, computer graphics, and artificial intelligence programs, providing hands-on training in lab environments.

Professional Experience

Dr. Dawod’s expertise spans a broad range of subjects in computer science and programming. His professional background includes:

Programming and Software Training:

MATLAB Trainer (2010–2016):

Conducted courses on MATLAB basics, mathematics, and working with variables in the MATLAB environment.

C++ Trainer (2010–2014):

Delivered training on fundamental programming concepts and variable management.

C# Trainer (2012–2016):

Provided training on C# fundamentals, applications, and Visual Studio.NET.

Dr. Dawod’s extensive experience in teaching and professional training reflects his strong proficiency in computer science, digital innovation, and programming.

Research Interests

His research focuses on Image processing, Machine Learning, Machine vision, Artificial Intelligence, Robotic Control, Video Processing, Computer Graphical programming, Augmented Reality, Virtual Reality, Computer Vision, Human-computer interaction, Sign Language Recognition, and Sign Language Interpretation.

Achievements

Medical Image Processing Projects

Segmenting and classifying brain hemorrhage injuries using CT scan images.

Detecting and classifying lesions related to diabetic retinopathy (NPDR).

Studying skin cancer (melanoma) using advanced techniques.

Utilized Spyder (IDE) Python and deep learning algorithms for the projects, with research and datasets from Chiang Mai Hospital.

Mangrove Forest Study

Conducting research on mangrove forests and their various ecological features.

Security and Cybersecurity Projects

Developing a face recognition security system (data collection phase).

Identifying car plate numbers, models, and vehicle brands through cybersecurity measures.

Markerless Tracking Augmented Reality Project

Contributing to a project focused on treating insect phobias using augmented reality.

Funded by Multimedia University from 2010 to 2012.

Real-Time 3D Virtual Object Overlay

Overlaying 3D virtual objects onto real environments using optical tracking for accurate registration.

Insect Movement Simulation in Virtual Reality

Created and organized insect simulations using VRML, OpenGL, and Maya.

Ensured insects accurately track and follow hand movements on screen.

Virtual Reality for Surgical Training

Developed a VRML program to create high-quality virtual hearts for training students in surgery, aiming to help overcome fear of surgery.

Sign Language Recognition for Deaf Communication

Devised a new technique using American Sign Language to improve communication for deaf individuals.

Developed four classification approaches with a focus on accuracy in recognition.

Continuous Sign Language Gesture Recognition

Conducted research on detecting and recognizing hand gestures in continuous sign language.

Focused on static and dynamic gesture categories.

Kinect-Based Sign Language Recognition

Developed a novel approach to automatically recognize and interpret sign language using Kinect for Windows V2.

Algorithm capable of recognizing both continuous and isolated sign language.

Real-Time Recognition of Continuous Sign Language

Contributed to advancements in real-time recognition of continuous sign language using Kinect sensors.

Hand Gesture Recognition in Sign Language

Developed methods to recognize one-handed and two-handed signs in sign language.

Tested the method on standard and negative sentence datasets.

Top Notable Publications

“Hotspots and trends of environmental, social and governance (ESG) research: A bibliometric analysis”

Co-authors: G Wan, AY Dawod, S Chanaim, RS Shankar

Published in Data Science and Management, 6(2), 65-75

Citations: 68 (2023)

“An optimal deep learning framework for multi-type hemorrhagic lesions detection and quantification in head CT images for traumatic brain injury”

Co-authors: A Phaphuangwittayakul, Y Guo, F Ying, AY Dawod, S Angkurawaranon

Published in Applied Intelligence

Citations: 52 (2022)

“Adaptive skin color model for hand segmentation”

Co-authors: AY Dawod, J Abdullah, MJ Alam

Published in 2010 International Conference on Computer Applications and Industrial Engineering

Citations: 49 (2010)

“A new method for hand segmentation using free-form skin color model”

Co-authors: AY Dawod, J Abdullah, MJ Alam

Published in 2010 3rd International Conference on Advanced Computer Theory and Engineering

Citations: 29 (2010)

“ESG Rating and Northbound Capital Shareholding Preferences: Evidence from China”

Co-authors: G Wan, AY Dawod

Published in Sustainability Journal, 14(15), 19

Citations: 27 (2022)

“Twitter sentiment analysis and expert ratings of initial coin offering fundraising: evidence from Australia and Singapore markets”

Co-authors: A Chursook, AY Dawod, S Chanaim, N Naktnasukanjn, N Chakpitak

Published in TEM Journal, 11(1), 44

Citations: 26 (2022)

“Fingertips detection from color image with complex background”

Co-authors: AY Dawod, J Abdullah, MJ Alam

Published in The 3rd International Conference on Machine Vision (ICMV), 88-96

Citations: 12 (2010)

“Novel Technique for Isolated Sign Language Based on Fingerspelling Recognition”

Co-authors: AY Dawod, N Chakpitak

Published in 2019 13th International Conference on Software, Knowledge, Information, …

Citations: 11 (2019)

“A Bibliometric and Visual Analysis in the Field of Environment, Social and Governance (ESG) Between 2004 and 2021”

Co-authors: G Wan, AY Dawod, C Nopasit

Published in International Journal of Information Science and Management (IJISM), 21(2)

Citations: 10 (2023)

“Assessing mangrove deforestation using pixel-based image: a machine learning approach”

Co-authors: AY Dawod, MA Sharafuddin

Published in Bulletin of Electrical Engineering and Informatics, 10(6), 3178-3190

Citations: 8 (2021)

“Gesture Segmentation: Automatic Continuous Sign Language Technique Based on Adaptive Contrast Stretching Approach”

Co-authors: AY Dawod, M.J. Nordin, J. Abdullah

Published in Middle-East Journal of Scientific Research, 24, 347-352

Citations: 8 (2016)

“Legal Informatics of HS Code Automatic Compliance Translation Based on Cross-border Trade Digitization”

Co-authors: J Mao, AY Dawod

Published in International Electrical Engineering Congress (iEECON). IEEE, 1-4

Citations: 6 (2022)

“Static Hand Gestures: Fingertips Detection Based on Segmented Images”

Co-authors: AY Dawod, MJ Nordin, J Abdullah

Published in J. Comput. Sci., 11(12), 1090-1098

Citations: 6 (2015)

“Microseismic Monitoring Signal Waveform Recognition and Classification: Review of Contemporary Techniques”

Co-authors: H Shu, AY Dawod

Published in Applied Sciences, 13(23), 12739

Citations: 5 (2023)

“Post-covid teaching of physics experiments through flipped classroom & blended teaching practice at college”

Co-authors: X Wen, AY Dawod

Published in 2022 International Conference on Engineering and Emerging Technologies

Citations: 5 (2022)

“Adaptive Slices in Brain Haemorrhage Segmentation Based on the SLIC Algorithm”

Co-authors: AY Dawod, A Phaphuangwittayaku, F Ying, S Angkurawaranon

Published in Engineering Letters, 29(2)

Citations: 5 (2021)

“Correlation between capital markets and cryptocurrency: impact of the coronavirus”

Co-authors: K Ariya, S Chanaim, AY Dawod

Published in International Journal of Electrical & Computer Engineering, 13(6)

Citations: 4 (2023)

“Hand Feature Detection from Skin Color Model with Complex Background”

Co-authors: AY Dawod, J Abdullah, MJ Alam

Published in Annual International Conference on Advances in Distributed and Parallel Computing

Citations: 4 (2010)

“From traditional to digital: The impact of drones and virtual reality technologies on educational models in the post-epidemic era”

Co-authors: J Lu, AY Dawod, F Ying

Published in Sustainable Engineering and Innovation, 5(2), 261-280

Citations: 3 (2023)

Conclusion

Assist. Prof. Dr. Ahmad Yahya Dawod is highly deserving of the Research for Academic Excellence Citation Award based on his impressive body of work, significant citation impact, and the breadth of research topics he has addressed. His contributions to both academic and applied research, particularly in AI, image processing, and ESG, are commendable. While there are opportunities for enhancing the interdisciplinary nature of his work and boosting his international and public visibility, his current contributions reflect excellence in academic research. Dr. Dawod’s continuous pursuit of innovation and collaboration makes him a valuable candidate for this prestigious recognition.

 

 

 

 

 

Iustina Ivanova | Computer Science | Best Researcher Award

Published on by Citation Awards

Mrs. Iustina Ivanova | Computer Science | Best Researcher Award

Mrs. Iustina Ivanova, Fondazione Bruno Kessler, Italy

Mrs. Iustina Ivanova is a researcher at Fondazione Bruno Kessler in Italy, specializing in the application of Artificial Intelligence (AI) in real-world contexts. Her early foundation in software engineering, coupled with her fascination for computer vision, has fueled her pursuit of impactful solutions in diverse fields such as sports and smart agriculture. Notably, her distinction-earning Master’s in AI, focusing on neural networks for object detection, highlights her dedication to advancing cutting-edge technology.

Education:

Her academic journey began with a Specialist degree in Software Engineering from Bauman Moscow State Technical University, Russia (2007-2013), followed by a Master of Science in Artificial Intelligence from the University of Southampton, United Kingdom, which she completed with distinction in 2018. Although she pursued a PhD in Computer Science at the Free University of Bolzano, Italy, from 2019 to 2022, she opted to discontinue her doctoral studies to focus on professional endeavors.

Professional Profiles:

ORCID Profile

Scopus Profile

Professional Experience:

Researcher
Foundazione Bruno Kessler (Italy)
October 2023 – Present
Engaged in advancing Artificial Intelligence in smart agriculture, with a focus on step-ahead forecasting using sensor data. Conducted experiments with machine learning models to enhance prediction accuracy and decision-making in agricultural systems.

Data Science Moderator
Netology Company (Russia)
May 2019 – October 2020
Developed and delivered lectures on Statistics and Mathematics for Data Science as part of the “Data Science” course. Designed accessible educational materials hosted online for wider learning opportunities (Netology Statistics Repository).

Computer Vision Data Scientist
OCRV Company (Russia)
April 2019 – November 2019
Worked on a video-based tracking system for railway operations. Focused on detecting objects and people in video data, measuring working hours, and deploying advanced computer vision algorithms to improve workplace efficiency.

Teacher of Informatics and Mathematics
Repetitor.ru (Russia)
August 2013 – November 2017
Organized and facilitated engaging study sessions to prepare high school students for final exams in informatics and mathematics. Successfully guided approximately 30 students to pass exams and gain university admissions.

Research Interests:

Mrs. Ivanova’s research interests center on computer vision, machine learning, and the integration of AI technologies into diverse domains such as smart agriculture and sports analytics. She has made notable contributions through her research project “Sensors and Data for the Analysis of Sports Activities (SALSA).” This project, focusing on computer vision solutions and recommender systems for sport climbers, resulted in several well-received publications. Her work bridges technology and user experience, demonstrating innovation and practical value in AI-driven applications.

Publications:

Climbing Crags Repetitive Choices and Recommendations
2023-09-14 | Conference paper | DOI: 10.1145/3604915.3610652 | Contributors: Iustina Ivanova

Recommender Systems for Outdoor Adventure Tourism Sports: Hiking, Running and Climbing
2023-07-18 | Journal article | DOI: 10.1007/s44230-023-00033-3 | Contributors: Iustina Ivanova; Mike Wald

How Can We Model Climbers’ Future Visits from Their Past Records?
2023-06-16 | Conference paper | DOI: 10.1145/3563359.3597408 | Contributors: Iustina Ivanova; Mike Wald

Introducing Context in Climbing Crags Recommender System in Arco, Italy
2023-03-27 | Conference paper | DOI: 10.1145/3581754.3584120 | Contributors: Iustina Alekseevna Ivanova; Mike Wald

Map and Content-Based Climbing Recommender System
2022 | Conference paper | DOI: 10.1145/3511047.3536416 | Contributors: Ivanova, I.A.; Buriro, A.; Ricci, F.

Climber Behavior Modeling and Recommendation
2021 | Conference paper | DOI: 10.1145/3450613.3459658 | Contributors: Ivanova, I.

Climbing Route Difficulty Grade Prediction and Explanation
2021 | Conference paper | DOI: 10.1145/3486622.3493932 | Contributors: Andric, M.; Ivanova, I.; Ricci, F.

Knowledge-Based Recommendations for Climbers
2021 | Conference paper | EID: 2-s2.0-85116934926 | Contributors: Ivanova, I.; Andrić, M.; Ricci, F.

Climbing Activity Recognition and Measurement with Sensor Data Analysis
2020 | Conference paper | DOI: 10.1145/3395035.3425303 | Contributors: Ivanova, I.; Andric, M.; Janes, A.; Ricci, F.; Zini, F.

Video and Sensor-Based Rope Pulling Detection in Sport Climbing
2020 | Conference paper | DOI: 10.1145/3422844.3423058 | Contributors: Ivanova, I.; Andric, M.; Moaveninejad, S.; Janes, A.; Ricci, F.

Conclusion:

Mrs. Iustina Ivanova is a strong candidate for the Research for Best Researcher Award, given her impressive contributions to recommender systems and outdoor adventure tourism. Her work is not only academically robust but also highly relevant in practical contexts, addressing modern challenges in personalization and activity recognition.