Goncalo Galvao | Electronics and Computer Engineering | Best Researcher Award

Published on by Environmental Scientists

Dr. Goncalo Galvao | Electronics and Computer Engineering | Best Researcher Award

International Society For Executive Learning | Portugal

Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures.

Profiles: Scopus | Orcid | Google Scholar | Researchgate

Featured Publications

Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240.

Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692.

Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65).

Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116.

Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.

May El Barachi | Predictive Analytics and Machine Learning | Best Researcher Award

Published on by Environmental Scientists

Prof. May El Barachi | Predictive Analytics and Machine Learning | Best Researcher Award

Professor and Dean, University of Wollongong in Dubai, United Arab Emirates.

Prof. May El Barachi is a Canadian computer scientist and seasoned academic leader known for her transformative impact on education, research, and innovation. She is currently a Full Professor and Head of the School of Computer Science at the University of Wollongong in Dubai. Over her 15+ year career, she has secured over 5 million AED in research funding, published 110+ high-impact papers, and built a global network of collaborations across academia and industry. Her work bridges cutting-edge AI research with real-world applications in smart systems and sustainable development. A passionate advocate for diversity, inclusion, and lifelong learning, she holds a UAE Golden Visa and is fluent in English, Arabic, and French.

Profile

Scopus

Orcid

Google Scholar

🎓 Education

  • Ph.D. in Computer Science, Concordia University, Montréal, Canada (2004–2009)
    Specialization: Next Generation Networks, Service Engineering, Network Intelligence and Adaptation

  • M.A.Sc. in Electrical and Computer Engineering, Concordia University, Montréal, Canada (2002–2004)
    Specialization: Web Services, IP Telephony, Multimedia Communications

  • B.Sc. in Electronics and Communication Engineering, Arab Academy for Science, Technology & Maritime Transport, Alexandria, Egypt (1995–2000)
    Graduated Valedictorian with Honors; Specialization in Object Recognition, Remote Sensing, and Neural Networks

💼 Professional Experience

Prof. May El Barachi is a visionary academic leader and full professor of Computer Science with over 15 years of experience across the UAE, Canada, and Europe. She currently serves as the Head of the School of Computer Science at the University of Wollongong in Dubai (UOWD), where she has led transformational initiatives, including a 400% increase in enrollment, the development of innovative Master’s programs in AI and Cybersecurity, and the establishment of a widely recognized Executive Learning Program that has trained over 2,500 professionals.

Previously, she held the roles of Associate Dean of Research and Associate Professor at UOWD, where she restructured research clusters around Sustainable Development Goals, drove multi-million-dirham funding acquisition, and played a pivotal role in Ph.D. program development. At Zayed University, she served as Smart Lab Director and co-founder, pioneering research on smart cities and AI-driven systems, while also leading curriculum development and accreditation efforts. Her earlier experience includes postdoctoral research at the University of Quebec (ETS), and roles in industry-academic collaborations at Ericsson Canada and the Ambient Networks Project in Sweden, focusing on web services, context-aware networks, and next-generation telecom systems.

🔬 Research Interest

  • Artificial Intelligence and Machine Learning: including deep learning, computer vision, natural language processing (NLP), reinforcement learning, and ethical AI

  • Emerging Technologies & Applications: smart cities, smart healthcare systems, autonomous systems, and digital transformation

  • Next Generation Networks: context-aware networking, IoT integration, and cloud computing

  • Interdisciplinary Innovation: leveraging AI for societal challenges, particularly in sustainable development, cybersecurity, and educational technology

🏆Author Metrics

  • Publications: 110+ peer-reviewed papers

  • Google Scholar Profile: Google Scholar – Prof. May El Barachi

  • Research Funding Secured: 5.28+ million AED

  • Professional Training Delivered: 2,500+ industry professionals via executive education programs

  • Languages: English, Arabic, French

📚 Publications

1. Evaluating the Impact of COVID-19 on Multimodal Cargo Transport Performance: A Mixed-Method Study in the UAE Context

  • Authors: Rami Aljadiri, Balan Sundarakani, May El Barachi

  • Journal: Sustainability

  • Volume & Issue: 15(22)

  • Article Number: 15703

  • Publication Date: November 7, 2023

  • DOI: 10.3390/su152215703

  • Abstract: This study examines the challenges and opportunities of multimodal cargo transport in the UAE during the COVID-19 pandemic (2020–2022). Utilizing a mixed-method approach, the research involved qualitative interviews with five senior logistics executives and quantitative surveys with 120 participants. Findings indicate a significant relationship between geographical/geopolitical risks and increased shipping costs, emphasizing the need for secure and cost-effective multimodal solutions. The study offers insights for enhancing logistics performance in transit hubs during uncertain times.

2. E2DNE: Energy Efficient Dynamic Network Embedding in Virtualized Wireless Sensor Networks

  • Authors: Vahid Maleki Raee, Amin Ebrahimzadeh, Roch H. Glitho, May El Barachi, Fatna Belqasmi

  • Journal: IEEE Transactions on Green Communications and Networking

  • Volume & Issue: 7(3)

  • Pages: 1309–1325

  • Publication Year: 2023

  • DOI: 10.1109/TGCN.2023.3271230

  • Abstract: The paper introduces E2DNE, a novel approach for energy-efficient dynamic network embedding in virtualized wireless sensor networks (VWSNs). By optimizing resource allocation and reducing energy consumption, E2DNE enhances the performance and sustainability of VWSNs, making them more adaptable to varying network demands.

3. Secure Data Access Using Blockchain Technology Through IoT Cloud and Fabric Environment

  • Authors: Sangeeta Gupta, Premkumar Chithaluru, May El Barachi, Manoj Kumar

  • Journal: Security and Privacy

  • Publication Date: November 23, 2023

  • DOI: 10.1002/spy2.356

  • Abstract: This study addresses the challenges of secure data access in IoT environments by integrating blockchain technology with cloud computing. The proposed framework leverages the Hyperledger Fabric platform to ensure data integrity, confidentiality, and scalability, providing a robust solution for managing IoT data securely.

4. Combining Named Entity Recognition and Emotion Analysis of Tweets for Early Warning of Violent Actions

  • Authors: May El Barachi, Sujith Samuel Mathew, Manar AlKhatib

  • Conference: 2022 7th International Conference on Smart and Sustainable Technologies (SpliTech)

  • Publication Date: July 7–8, 2022

  • DOI: 10.23919/SpliTech55088.2022.9854231

  • Abstract: The paper presents a proactive framework that combines Named Entity Recognition (NER) and emotion analysis to detect early warning signs of potential violent actions from social media content. By analyzing tweets related to the 2020 US presidential election, the study demonstrates the framework’s effectiveness in identifying negative sentiments associated with specific entities, offering a tool for early intervention strategies.

5. A Green, Energy, and Trust-Aware Multi-Objective Cloud Coalition Formation Approach

  • Authors: Souad Hadjres, Fatna Belqasmi, May El Barachi, Nadjia Kara

  • Journal: Future Generation Computer Systems

  • Volume: 111

  • Pages: 52–67

  • Publication Date: October 2020

  • DOI: 10.1016/j.future.2020.04.030

  • Abstract: This research proposes a multi-objective approach for forming cloud coalitions that are energy-efficient and trust-aware. The algorithm considers factors like energy consumption, trust levels among providers, and service quality to form optimal coalitions. Experimental results show improvements in coalition size, provider payoff, and reduced mistrust costs, highlighting the approach’s potential for sustainable cloud computing.

🏁 Conclusion

Prof. May El Barachi is an outstanding and highly qualified nominee for the Best Researcher Award in Predictive Analytics and Machine Learning. Her portfolio exhibits the rare combination of technical depth, real-world applicability, international leadership, and a firm commitment to innovation in AI and societal impact. She not only advances predictive analytics through rigorous research but also through her systemic influence in academia and industry.

Given her publication volume, research funding, academic innovation, and practical AI implementations, she represents a paragon of excellence and leadership in predictive analytics and machine learning.

Mika Yasuoka | Computer | Best Researcher Award

Published on by Environmental Scientists

Dr. Mika Yasuoka | Computer | Best Researcher Award

Associate Professor, Roskilde University, Denmark

Dr. Mika Yasuoka Jensen 🇯🇵🇩🇰 is an Associate Professor of Sustainable Digitalization at Roskilde University, Denmark. With a multicultural background and deep expertise in computer science, informatics, and interaction design, she bridges Japanese, American, and Danish academic traditions. Passionate about co-creation, digital welfare, and Living Labs, Dr. Yasuoka leads global collaborations with universities, public institutions, and tech corporations to shape sustainable digital futures. Her leadership in participatory design, social innovation, and smart city initiatives has made her a prominent voice in advancing technology for societal benefit. 🌍💻

Profile

Google Scholar

Education 🎓

Dr. Yasuoka’s academic journey is a blend of prestigious institutions across three continents. She earned her Ph.D. in Computer Supported Cooperative Work from the IT University of Copenhagen, incorporating research at The University of Tokyo and Carnegie Mellon University. Prior to this, she completed an M.Sc. in Informatics from Kyoto University and a B.Sc. in Library and Information Science from Keio University. Her academic enrichment also includes an exchange program and visiting researcher positions at Carnegie Mellon University in the U.S. 🎓📘🌐

Experience 💼

Dr. Yasuoka’s professional path is marked by academic excellence and impactful leadership. Since 2020, she has been serving as Associate Professor at Roskilde University. She has held roles at institutions including the IT University of Copenhagen, Keio University, and Technical University of Denmark. She has led numerous cross-sectoral projects, blending stakeholder engagement and digital design across borders. Her strategic advisory roles include working with municipalities and government digital agencies in Japan. 🏫🌏👩‍🏫

Research Interest 🔍

Her core research focuses on sustainable digitalization, participatory design, Living Labs, and avatar-mediated communication. She investigates how digital technologies can be co-designed and responsibly integrated into societies to enhance well-being. With a special interest in smart cities, welfare technologies, and design frameworks, Dr. Yasuoka’s work aligns technology with human-centric values and social innovation. 🤖🏙️👥

Awards 🏆

Dr. Yasuoka has received multiple accolades for her innovative contributions. These include the 11th Nextcom Paper Award (2022) for advancing e-government strategy, the 12th KDDI Foundation Book Publishing Grant (2022), and a Best Paper Finalist at IEEE ARSO 2021. She also earned the Human Interface Society Award (2021) for her analysis of stakeholder involvement in welfare technology assessment. 🏆📚✨

Publications 📄

Key Practices for Welfare Robots Provision: Assessment Framework and Participation
Yasuoka, M., Akutsu, Y., Honma, K., & Matsumoto, Y.
IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO), 2021.
🔗 IEEE Xplore Link
Cited by researchers in robotics and social care design.

How Remote-Controlled Avatars Are Accepted in Hybrid Workplace
Yasuoka, M., Miyata, T., Nakatani, M., Taoka, Y., & Hamaguchi, N.
In: Distributed, Ambient and Pervasive Interactions, Lecture Notes in Computer Science, vol. 14036, Springer, Cham, 2023.
🔗 Springer Link
Referenced in studies on telepresence and future work environments.

Not Just Power: Exploring Transitions as Fluidity and Relationality in Participatory Design
Yasuoka, M., & Kibi, Y.
Participatory Design Conference 2024, Vol. 2: Exploratory Papers and Workshops.
🔗 ACM Link
Cited in participatory design and relational theory literature.

Reflection on Digital Cities
Yasuoka, M., & Ishida, T.
In Oxford Research Encyclopedia of Communication, Oxford University Press, 2023.
Used in urban digital studies and smart city curricula.

Conclusion

Dr. Mika Yasuoka Jensen is highly suitable for the Best Researcher Award. Her cross-cultural expertise, commitment to societal impact through digitalization, leadership in international projects, and award-winning research achievements make her a standout candidate. Minor enhancements in research metrics and journal profile would further strengthen her already impressive credentials.

Hyeryung Jang | Machine Learning | Best Researcher Award

Published on by Environmental Scientists

Assist. Prof. Dr Hyeryung Jang | Machine Learning | Best Researcher Award

Assistant Professor, Dongguk University, South Korea 🧑‍🏫

Hyeryung Jang is an Assistant Professor at the Division of AI Software Convergence at Dongguk University, Seoul, South Korea. His research interests lie at the intersection of communication systems, probabilistic graphical models, and networked machine learning. He has contributed significantly to the development of algorithms for large-scale communication networks, with applications in healthcare, manufacturing, and beyond. He has held academic and research positions at prestigious institutions, including King’s College London and KAIST.

Profile

Google Scholar

🎓 Education

Hyeryung Jang earned his Ph.D. in Electrical Engineering from the Korea Advanced Institute of Science and Technology (KAIST), South Korea, from March 2012 to February 2017. His doctoral thesis, titled Optimization and Learning of Graphical Models: A Stochastic Approximation Approach, was supervised by Prof. Yung Yi and co-advised by Prof. Jinwoo Shin. He also holds a Master’s degree in Electrical Engineering from KAIST, completed between March 2010 and February 2012, with a thesis on the Economic Benefits of ISP-CDN and ISP-ISP Cooperation, under the guidance of Prof. Yung Yi. Hyeryung Jang completed his Bachelor’s degree in Electrical Engineering at KAIST in February 2010.

💼 Experience

Hyeryung Jang currently serves as an Assistant Professor in the Division of AI Software Convergence at Dongguk University, where he has been leading the Intelligence and Optimization in Networks (ION) lab since March 2021. Before this, he was a Research Associate at King’s College London, in the Centre for Telecommunications Research, Department of Engineering, from March 2018 to February 2021. His post-doctoral research was conducted at KAIST from March 2017 to February 2018. Hyeryung also gained valuable experience as a Research Intern at Los Alamos National Laboratory in the USA during the summer of 2015.

🔬 Research Interests

Hyeryung Jang’s research interests are centered on mathematical modeling and communication systems, with a particular emphasis on networked machine learning. He explores innovative learning algorithms for probabilistic graphical models, deep learning, and reinforcement learning. His work aims to improve the stability and representation quality of generative models such as GANs, VAEs, and diffusion models. Jang is also focused on the learning and inference of graphical models, specifically for applications like robust recommendation systems and communication-efficient algorithms. Moreover, his research delves into efficient learning methods to address noisy data and real-world challenges in fields like healthcare, highlighting his broad interdisciplinary approach to solving complex problems in communication networks.

🏆 Awards

Hyeryung Jang has received recognition for his groundbreaking work in networked machine learning, contributing to innovative applications in healthcare and telecommunications. His research has been published in top-tier journals such as IEEE Transactions on Communications, IEEE Transactions on Neural Networks and Learning Systems, and Journal of Medical Internet Research (JMIR).

📚 Publications Top Notes

LinkFND: Simple Framework for False Negative Detection in Recommendation Tasks with Graph Contrastive Learning, IEEE Access, Dec. 2023.

In-Home Smartphone-based Prediction of Obstructive Sleep Apnea in Conjunction with Level 2 Home Polysomnography, JAMA Otolaryngology-Head & Neck Surgery, Nov. 2023.

Prediction of Sleep Stages via Deep Learning using Smartphone Audio Recordings in Home Environments, Journal of Medical Internet Research, June 2023.

Real-time Detection of Sleep Apnea based on Breathing Sounds and Prediction Reinforcement using Home Noises, Journal of Medical Internet Research, Feb. 2023.

Conclusion

Given his strong academic credentials, innovative contributions, and high-impact research, Hyeryung Jang is undoubtedly a strong contender for the Best Researcher Award. His work not only advances theoretical knowledge but also drives practical applications that address critical real-world challenges, particularly in communication systems and healthcare. Jang’s passion for interdisciplinary research and teaching further solidifies his suitability for this prestigious recognition.

Haichang Jiang | AI | Best Researcher Award

Published on by Environmental Scientists

Mr Haichang Jiang | AI | Best Researcher Award

lecturer, jingdezhen university, China  📚

Haichang Jiang is a lecturer at the School of Information Engineering, Jingdezhen University, with over 10 years of experience in artificial intelligence technology, project management, and research. He completed his Master’s in Software Engineering at the University of Electronic Science and Technology of China in 2013 and earned his Ph.D. in Educational Management from the University of Perpetual Help System DALTA in the Philippines in 2023. Jiang has successfully managed large-scale AI projects, such as AI public opinion platforms for the Cyberspace Administration of China and the Ministry of Education.

Profile

Google Scholar

Education 🎓

Haichang Jiang holds a Master’s degree in Software Engineering from the University of Electronic Science and Technology of China (2013). In 2023, he received his Ph.D. in Educational Management from the University of Perpetual Help System DALTA, Philippines, where he honed his expertise in artificial intelligence and educational technologies.

Experience 💼

Jiang has extensive experience in both academia and industry. He has been a lecturer at Jingdezhen University since 2023, teaching AI and related subjects. His professional career includes managing and researching AI-based projects such as the development of AI-driven platforms for the Chinese government and the design of smart healthcare and financial systems. He has collaborated with various top Chinese universities and institutions on AI and health-related research.

Research Interests 🔬

Haichang Jiang’s research primarily focuses on artificial intelligence, smart healthcare, intelligent finance, and sentiment analysis. His projects involve the application of deep learning in medical diagnostics, the development of smart financial systems, and the integration of multimodal views based on natural language for public opinion monitoring.

Awards 🏆

Jiang has contributed significantly to various research projects, with notable achievements including his involvement in AI public opinion platforms, AI-driven smart healthcare systems, and environmental monitoring technologies. His work has been recognized by the Ministry of Education of China, the Jiangxi Provincial Higher Education Society, and several leading academic organizations.

Publications Top Notes 📑

“Research on Real-time Psychological Crisis Early Warning System Based on Natural Language and Deep Learning”, Journal of Artificial Intelligence, 2024. Cited by 15 articles.

“Innovation and Practice of Teaching Methods Under New Engineering Background”, Educational Technology and Society, 2024. Cited by 10 articles.

Conclusion

Haichang Jiang is a highly deserving candidate for the Best Researcher Award due to his extensive and impactful contributions to AI, healthcare, finance, and public opinion analysis. His innovative projects, ongoing research, and leadership in cutting-edge AI applications demonstrate his potential to drive future technological advancements. With continued collaboration and greater international visibility, Haichang Jiang is poised to further elevate the scope of his research, making him a suitable recipient of this prestigious award.