Dr. Zobeir Raisi | Deep Learning | Excellence in Research Award

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Dr. Zobeir Raisi | Deep Learning | Excellence in Research Award 

Dr. Zobeir Raisi | Deep Learning | Chabahar Maritime University | Iran

Dr. Zobeir Raisi is a male expert in computer vision, machine learning, and deep learning, specializing in object detection, recognition, tracking, segmentation, 3D human pose estimation, and camera calibration, combining advanced theoretical knowledge with practical and applied research experience. He holds a Ph.D. in Systems Design Engineering from the University of Waterloo, Canada, and both M.E. and B.E. degrees in Electrical Engineering from the University of Sistan & Balouchestan, Iran, reflecting a strong academic foundation and interdisciplinary technical proficiency. Dr. Zobeir Raisi’s professional experience encompasses postdoctoral research focused on automating sports analytics using smartphone cameras, supervising master’s students in camera calibration projects with industry collaboration, and conducting Ph.D.-level research on transformer-based deep learning frameworks for arbitrary-shaped text detection and recognition in complex visual environments. He has contributed as a research assistant in computer vision and machine learning applications for automated assembly and anomaly detection systems, as well as serving as a lecturer and assistant professor at Chabahar Maritime University, teaching courses spanning digital image processing, digital systems, electrical circuits, computer architecture, microcontrollers, and electromagnetics, while mentoring undergraduate and graduate students and managing journal editorial processes.

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Featured Publications


Machine Learning Algorithms for Signal and Image Processing


– John Wiley & Sons, 2022 · 100+ Citations

Transformer-Based Text Detection in the Wild


– IEEE/CVF CVPR, 2021 · 74 Citations

2D Positional Embedding-Based Transformer for Scene Text Recognition


– Journal of Computational Vision and Imaging Systems, 2020 · 32 Citations

Dr. Sadegh Ghavami | Nano Sensors | Research Excellence Award

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Dr. Sadegh Ghavami | Nano Sensors | Research Excellence Award

Dr. Sadegh Ghavami | Nano Sensors | Sahand University of Technology | Iran

Dr. Sadegh Ghavami is a male geotechnical engineer and academic researcher with expertise in soil stabilization, physical and centrifuge modeling, numerical analysis, and advanced construction materials, demonstrating a comprehensive approach to civil infrastructure and smart geotechnical systems. He holds a Ph.D. in Civil Engineering with a focus on Geotechnical Engineering from Iran University of Science and Technology, supported by M.S. and B.S. degrees in Civil Engineering from Sharif University of Technology. His professional experience includes extensive teaching roles at multiple universities, delivering core and advanced courses such as soil mechanics, foundation engineering, soil dynamics, geotechnical earthquake engineering, and earth-fill dam design, as well as serving as a teaching assistant in continuum mechanics and geotechnical laboratory courses. Dr. Sadegh Ghavami’s research portfolio focuses on soil stabilization techniques, centrifuge-based physical modeling, finite element analysis of geotechnical systems, and construction material performance, emphasizing data-driven and sensor-informed approaches to infrastructure resilience. He has published in high-impact Scopus- and IEEE-indexed journals, contributing 11 peer-reviewed documents with more than 200 citations and an h-index of 6, reflecting substantial research influence.

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Top 5 Publications


Effects of Silica Fume and Nano-silica on the Engineering Properties of Kaolinite Clay

AUT Journal of Civil Engineering, 2018 · 📖 Citations: 50

Dr. Annarosa Scalcione | Machine Learning | Research Excellence Award

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Dr. Annarosa Scalcione | Machine Learning | Research Excellence Award 

Dr. Annarosa Scalcione | Machine Learning | Polytechnic University of Turin | Italy

Dr. Annarosa Scalcione is a female biomedical engineer with a strong interdisciplinary background in biomedical instrumentation, sensor-based health monitoring, medical imaging, and digital healthcare solutions, combining engineering rigor with clinical relevance. She completed advanced academic training in biomedical engineering at Politecnico di Torino, with specialization in biomedical instrumentation and sensor systems, supported by foundational education in biomedical engineering from the same institution, where her academic work focused on sustainable biomaterials and applied medical technologies. Her professional experience includes roles as a Junior Application Consultant contributing to the digitalization of hospital clinical and administrative processes, operating room specialist engagement within medical institutions, and academic teaching collaboration supporting undergraduate engineering education. Dr. Annarosa Scalcione has led and contributed to multiple applied and experimental research projects, including the design of a web-based neonatal monitoring platform integrating sensor-derived growth data, dynamic visualization, personalized alerts aligned with international health standards, and telemedicine functionalities. Her research portfolio also includes experimental biomechanics studies using mobile sensors to evaluate neuromuscular performance, automated classification of spinal lesions from medical imaging using machine learning and radiomics, and advanced image segmentation methodologies applied to neurological datasets.

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Mrs. Kalani Rajamanthri | Moisture Sensors | Research Excellence Award

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Mrs. Kalani Rajamanthri | Moisture Sensors | Research Excellence Award

Mrs. Kalani Rajamanthri | Moisture Sensors | Arizona State University | United States

Mrs. Kalani Rajamanthri is a female geotechnical engineer and academic researcher with strong expertise in civil, environmental, and sustainable engineering, specializing in geotechnical infrastructure resilience, geosynthetics, and slope stability under extreme climatic conditions. She holds a Doctor of Philosophy in Civil, Environmental, and Sustainable Engineering from Arizona State University with a specialization in Geotechnical Engineering, supported by advanced graduate education in civil engineering from Kasetsart University and undergraduate training in civil and infrastructure engineering from the Asian Institute of Technology. Her professional experience spans academic research, teaching, government research organizations, and large-scale international construction projects, including roles as a Graduate Research Associate, Teaching Assistant in geotechnical engineering, Geotechnical Engineer in multinational infrastructure projects, and Engineer within a national research organization’s geotechnical division. Her work integrates numerical modeling, experimental investigation, and field-based geotechnical analysis, with demonstrated contributions to excavation support design, retaining structures, slope stability assessment, embankment settlement monitoring, and disaster-resilient infrastructure development. Her research interests include innovative geosynthetics, unsaturated soil mechanics, soil–geosynthetic interaction, climate-resilient embankment systems, and sustainable geotechnical solutions for transportation infrastructure.

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Featured Publications


Stability Assessment of a Bio-Engineered Slope in Western Thailand


– Conference / Journal Article

Mr. Lee Patrick Ekouaguet | Body Sensors | Industry Impact Award

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Mr. Lee Patrick Ekouaguet | Body Sensors | Industry Impact Award 

Mr. Lee Patrick Ekouaguet | Body Sensors | Ogooue Corps Technologies | France

Mr. Lee Patrick Ekouaguet is an inventor, technology entrepreneur, and innovation leader specializing in smart sensor systems, wearable health and safety technologies, and sustainable engineering solutions with strong societal impact. His academic background includes advanced multidisciplinary training in international trade, transport and logistics, and specialized professional education in artificial intelligence and cybercriminology, providing a solid foundation for managing complex, technology-driven innovation ecosystems. Professionally, he serves as Founder and Chief Executive Officer of OGOOUE CORPS TECHNOLOGIES, a deep-tech organization focused on the design and deployment of autonomous, low-energy, and environmentally responsible sensor-based devices for healthcare, public safety, and digital inclusion. His professional experience spans the leadership of distributed research and development teams, coordination of cross-border partnerships with universities, innovation hubs, and applied research institutions, and the supervision of concept-to-prototype development of smart wearable systems. His primary research interests include wearable sensor integration, body-powered and energy-harvesting systems, sustainable materials for medical devices, connected safety monitoring platforms, and ethical human-centered technology design aligned with global development goals. His awards and honors reflect recognition for innovation excellence, health technology impact, and sustainable engineering leadership at international levels.

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Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Excellence in Research Award

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Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Excellence in Research Award

Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Dong-A University | South Korea

Assist. Prof. Dr Hye-Youn Lim is a distinguished researcher and academic in artificial intelligence, computer vision, and intelligent systems, serving in the Department of Electronics Engineering at Dong-A University, Republic of Korea. Hye-Youn Lim obtained her Ph.D. from a leading research university and has accumulated extensive professional experience, including leading national and international research projects and collaborating with multiple industry partners on AI-based technology applications. Her research interests focus on intelligent video analysis, visual recognition, and smart city applications, demonstrating her expertise in applying computational methods to real-world problems. Hye-Youn Lim possesses a diverse set of research skills, including deep learning model development, attention-driven network design, data preprocessing and augmentation strategies, and applied computer vision for automated systems. Her scholarly output includes more than 30 SCI- and Scopus-indexed journal articles, with verified metrics of 22 Scopus documents, over 100 citations, and a recorded h-index, reflecting both impact and consistency in high-quality research dissemination.

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Prof. Dae-Seong Kang | Sensing Technology | Excellence in Research Award

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Prof. Dae-Seong Kang | Sensing Technology | Excellence in Research Award 

Prof. Dae-Seong Kang | Sensing Technology | Dong-A University | South Korea

Prof. Dae-Seong Kang is a Professor in the Department of AI Software at Dong-A University, Republic of Korea, with established expertise in artificial intelligence, computer vision, and intelligent perception systems, and a strong academic profile grounded in doctoral-level training from a research-intensive university. He has developed a distinguished professional career combining advanced research leadership, graduate education, and large-scale collaboration with industry and public-sector partners. Prof. Dae-Seong Kang has served as Principal Investigator on more than twenty-five national and international research projects, demonstrating sustained capability in managing complex, multidisciplinary initiatives aligned with intelligent sensing and real-time AI systems.  His research interests focus on artificial intelligence, computer vision, deep learning, image and video analytics, and intelligent perception systems, with emphasis on robust, lightweight, and real-time models suitable for sensing environments. His scholarly output is substantial, with 52 Scopus-indexed documents, 161 citations, and an h-index of 4, including peer-reviewed publications in IEEE-aligned and Scopus-indexed journals and conferences. His professional service includes editorial and reviewer roles, international collaborations, senior membership in AI-focused professional societies, and leadership in academia–industry partnerships, alongside 25+ research projects, 10+ consultancy engagements, 5 published patents, and 1 academic book.

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Dr. Byung-Ho Rhie | Cancer Awards | Research Excellence Award

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Dr. Byung-Ho Rhie | Cancer Awards | Research Excellence Award

Dr. Byung-Ho Rhie | Cancer Awards | Kangwon National University | South Korea

Dr. Byung-Ho Rhie is a highly accomplished biomedical researcher and academic with extensive expertise in cancer biology, stem cell research, and targeted therapeutics, with a particular focus on non-small cell lung cancer (NSCLC) drug resistance mechanisms and human pluripotent stem cell biology. He earned his Ph.D. from the College of Science and Technology, Hanyang University, and has held multiple postdoctoral and senior researcher positions at Hanyang University and Kangwon National University, where he contributed to international collaborative research projects and translational biomedical studies. Dr. Byung-Ho Rhie’s professional experience includes establishing NSCLC research platforms, generating osimertinib-resistant EGFR-mutant cell lines, performing CRISPR/Cas9-mediated knockout of drug resistance factors, and investigating novel therapeutic strategies for drug-resistant cancers. His research on pluripotent stem cells includes developing xeno-free and chemically defined culture conditions, identifying and characterizing deubiquitinating enzymes regulating pluripotency factors such as OCT4 and SOX2, and performing genome-wide CRISPR functional screenings. His scholarly output includes five Scopus-indexed publications with 50 citations and an h-index of 4, demonstrating both depth and impact in biomedical research.

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Featured Publication


EGFR inhibitor suppresses tumor growth by blocking lipid uptake and cholesterol synthesis in non-small cell lung cancer

Rhie, B.-H., et al. (2025). Biochimica et Biophysica Acta – Molecular Basis of Disease.

Mrs. Dasinaa Subramaniam | Environmental Science | Research Excellence Award

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Mrs. Dasinaa Subramaniam | Environmental Science | Research Excellence Award

Mrs. Dasinaa Subramaniam | Environmental Science | Memorial University of Newfoundland | Canada

Mrs. Dasinaa Subramaniam is a distinguished researcher and academic professional specializing in Boreal Ecosystems, Agricultural Sciences, and Animal Science, with comprehensive expertise in sustainable agriculture, biofertilizer production, and animal feed development. She is pursuing her Ph.D. at the School of Science and the Environment, Grenfell Campus, Memorial University of Newfoundland, where her research focuses on evaluating the potential of using earthworms to produce commercially viable animal feed and vermicompost biofertilizer from pulp and paper mill sludge, demonstrating her commitment to innovative circular bio-economy solutions. Mrs. Dasinaa Subramaniam’s educational background includes a Master of Science in Animal Science from the Post Graduate Institute of Agriculture, University of Peradeniya, where she investigated factors influencing artificial insemination success in selected veterinary ranges, and a Bachelor of Science in Agriculture with a specialization in Animal Science from the Faculty of Agriculture, Eastern University Sri Lanka. Her professional experience spans academic lecturing, research, and leadership roles, including her current appointment as Lecturer in the Department of Bio-systems Technology, Eastern University Sri Lanka, and her previous position as Head of the Department of Agriculture at Hardy Advanced Technological Institute, Sri Lanka Institute of Advanced Technological Education, where she promoted high standards in student performance, curriculum delivery, and faculty management.

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Mr. MingShou An | Computer Vision | Research Excellence Award

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Mr. MingShou An | Computer Vision | Research Excellence Award

Mr. MingShou An | Computer Vision | Xi’an Technological University | China

Mr. MingShou An is an accomplished researcher and academic professional specializing in Artificial Intelligence–driven sensing systems, with strong expertise in Computer Vision, Deep Learning, and Intelligent Monitoring Technologies. He holds a Ph.D. in an engineering and computing discipline from a recognized Chinese university, where his doctoral research focused on data-driven visual perception, lightweight neural architectures, and intelligent sensing models for real-time environments. Currently affiliated with Xi’an Technological University, Mr. MingShou An has established a solid academic and professional profile through his contributions to national and collaborative research projects addressing smart surveillance, intelligent safety monitoring, and applied AI for sensor-enabled systems. His professional experience spans academic lecturing, research supervision, and applied system development, where he actively bridges theoretical algorithm design with deployable AI solutions for real-world sensing applications, including edge AI and time-sensitive visual analytics. His scholarly output includes 10 Scopus-indexed publications, achieving 15 citations and an h-index of 3, with several works published in IEEE-affiliated conferences and peer-reviewed venues related to intelligent perception and lightweight network design.

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