Changhyoun Park | Machine Learning | Best Researcher Award

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Dr. Changhyoun Park | Machine Learning | Best Researcher Award

Research Scientist | Pusan National University | South Korea

Changhyoun Park is a South Korean atmospheric scientist and research scholar currently serving as a Research Scientist at the Institute of Environmental Studies and a Lecturer in the Department of Atmospheric Environmental Sciences at Pusan National University (PNU), South Korea. With extensive international academic and research experience, including postdoctoral positions in the USA, Dr. Park has focused on the intersection of atmospheric modeling, greenhouse gas fluxes, and artificial intelligence. His work bridges theoretical research and practical applications, contributing to the advancement of climate and environmental science through teaching, mentorship, and high-impact scholarly publications.

Publication Profile

Scopus

ORCID

Google Scholar

Education Background

Dr. Changhyoun Park holds a Ph.D. in Atmospheric Sciences from Texas A&M University in the United States, where he conducted advanced research in greenhouse gas fluxes and atmospheric modeling. Prior to this, he earned both his Master’s and Bachelor’s degrees in Atmospheric Sciences from Pusan National University (PNU), South Korea. His academic path reflects a strong commitment to environmental and climate research, enhanced by international collaborations and exposure to multidisciplinary approaches in atmospheric science, machine learning, and mesoscale modeling.

Professional Experience

Dr. Park currently holds dual positions as a Research Scientist at the Institute of Environmental Studies and a Lecturer in the Department of Atmospheric Environmental Sciences at PNU. His prior appointments include postdoctoral research roles at Texas A&M University, the University of California, Los Angeles (JIFRESSE), and PNU. He also has industry experience as a Project Manager at YhKim Co. Ltd. His work includes developing AI-based prediction models, conducting mesoscale simulations, managing national-level carbon modeling projects, and mentoring gifted science students through national science education programs in Korea.

Awards and Honors

Throughout his academic and professional journey, Dr. Changhyoun Park has received multiple awards recognizing his contributions to research and science education. These include the Best Researcher of the Year Award from the Institute of Environmental Studies at PNU, an Outstanding Presentation Award by the Korean Society for Atmospheric Environment, and a Regent’s Graduate Fellowship at Texas A&M University. He was also a session winner at Texas A&M’s Student Research Week and received an Encouragement Award from Korea’s Director’s Council of Gifted Science Education.

Research Focus

Dr. Park’s research centers on micrometeorology, atmospheric carbon modeling, greenhouse gas (GHG) dynamics, and the application of artificial intelligence to environmental prediction systems. His expertise includes mesoscale numerical modeling of GHGs, machine learning-based fog and flux prediction, and eddy covariance data analysis. He has led significant projects on CO₂ radiative forcing, VOC fluxes, and vegetation uptake across East Asia and Korea. His interdisciplinary approach integrates atmospheric science with cutting-edge computational techniques to address pressing climate and environmental challenges.

Publications

Significance of Time-Series Consistency in Evaluating Machine Learning Models for Gap-Filling Multi-Level Very Tall Tower Data
Published Year: 2025
Cited by: 5

Environmental factors contributing to variations in CO2 flux over a barley–rice double‑cropping paddy field in the Korean Peninsula
Published Year: 2022
Cited by: 12

Numerical simulation of atmospheric CO2 concentration and flux over the Korean Peninsula using WRF-VPRM model during Korus-AQ 2016 campaign
Published Year: 2020
Cited by: 20

CO2 transport, variability, and budget over the southern California air basin using the high-resolution WRF-VPRM model during the CalNex 2010 campaign
Published Year: 2018
Cited by: 30

Anthropogenic and biogenic features of long-term measured CO2 flux in north downtown Houston, Texas
Published Year: 2016
Cited by: 24

Conclusion

Dr. Changhyoun Park’s academic and research journey reflects a robust commitment to advancing atmospheric and environmental sciences. His diverse roles across academia, research, and education have positioned him as a leader in micrometeorological modeling and AI applications in climate science. With numerous peer-reviewed publications and funded research projects, he continues to contribute significantly to understanding biosphere-atmosphere interactions, offering scientific insights that support sustainable environmental policy and technological innovation in atmospheric monitoring.

Farzaneh Zareian | Machine Learning | Best Researcher Award

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Ms. Farzaneh Zareian | Machine Learning | Best Researcher Award

Ms. Farzaneh Zareian – Graduate Student, Amirkabir University of Technology, Iran.

Farzaneh Zareian is a dynamic civil engineering researcher with a specialization in earthquake engineering and machine learning applications in structural analysis. Holding a master’s degree from the prestigious Amirkabir University of Technology and a bachelor’s from the University of Tehran, she has consistently demonstrated academic excellence and innovation. Farzaneh has contributed significantly through teaching, research, and scholarly publications in seismic assessment and structural resilience. With experience in AI-powered modeling, fragility curve generation, and passive control systems, she stands at the intersection of engineering and intelligent computation, contributing to safer, more resilient infrastructure in seismic-prone regions.

Publication Profile

Google Scholar

🎓 Education Background

Farzaneh Zareian earned her M.Sc. in Civil Engineering (Earthquake Engineering) from Amirkabir University of Technology, Tehran (2020–2023) with an excellent-rated thesis supervised by Dr. Mehdi Banazadeh. Her research focused on nonlinear dynamic response estimation using machine learning. Prior to that, she completed her B.Sc. in Civil Engineering at the University of Tehran (2016–2020), with coursework emphasizing earthquake engineering, bridge design, and hydraulic structures. Her academic journey highlights a deep commitment to blending structural theory with advanced computational methods, maintaining strong GPAs and securing top ranks in national entrance exams at both undergraduate and postgraduate levels.

💼 Professional Experience

Farzaneh Zareian has accumulated valuable academic experience through teaching and research roles. She worked as a sessional instructor for the “Soft Computing” course at Shahab Danesh University during 2023–2024 and currently serves as a Teaching Assistant in “Theory of Structural Analysis” at Amirkabir University of Technology. Her practical engagements also include academic projects involving seismic hazard analysis, vulnerability assessment, and AI-driven structural modeling. These roles reflect her dual strength as both an educator and practitioner in earthquake-resistant design and computational engineering, making her a well-rounded and impactful civil engineering professional.

🏅 Awards and Honors

Farzaneh’s academic excellence has been widely recognized through several honors. In 2024, she was selected as a distinguished Ph.D. candidate by Amirkabir University’s Committee of Exceptional Talents. She ranked 1st among her peers in the Earthquake Engineering master’s program in 2022 and was among the top 0.2% in both bachelor’s and master’s national entrance exams in 2016 and 2020, respectively. Additionally, she was the top high school student at NODET. These accolades reflect her exceptional dedication, intelligence, and potential as a future leader in structural and earthquake engineering research.

🔬 Research Focus

Farzaneh’s research focuses on AI-enabled structural design and optimization, particularly in seismic contexts. She specializes in applying machine learning and physics-informed models to estimate structural responses, assess risk and reliability, and enhance infrastructure resilience. Her projects include probabilistic seismic hazard analysis, fragility curve generation, and the use of deep learning for crack detection in masonry. She is deeply committed to integrating data-driven approaches with classical civil engineering practices to improve safety, sustainability, and performance of critical infrastructure under seismic hazards.

🧾 Conclusion

Farzaneh Zareian exemplifies the emerging generation of civil engineers who are leveraging artificial intelligence to redefine structural safety and resilience. Her academic accomplishments, hands-on project experiences, teaching engagements, and scholarly contributions highlight a well-rounded professional profile. As she progresses toward doctoral research, her innovative mindset and strong foundation in both theory and practice make her a prime candidate for research excellence in AI-integrated earthquake engineering. With her interdisciplinary approach, she is poised to make impactful contributions to the global civil and seismic engineering community.

📚 Publication Top Notes

 Prediction of nonlinear dynamic responses and generation of seismic fragility curves for steel moment frames using boosting machine learning techniques
📅 Year: 2024 (Nov.)
📘 Journal: Computers & Structures
🔢 Cited by: 1

 Machine learning-based seismic risk assessment of steel moment structures: a reliability analysis framework
📅 Year: In Preparation (Expected 2025)
📘 Journal: Engineering Structures
🔢 Cited by: –

Mr. Ahmad Faraz Hussain | Machine learning | Best Scholar Award

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Mr. Ahmad Faraz Hussain | Machine learning | Best Scholar Award

PhD student, Zhejiang university, China

Ahmad Faraz Hussain is an accomplished researcher and engineer specializing in audio signal processing, speaker recognition, and wireless sensor networks. With a strong academic background and extensive technical experience, he has contributed significantly to the field of electronics and information engineering. His work spans research, teaching, and industry, reflecting his passion for innovation and education.

Publication Profile

Scopus

🎓 Education:

Ahmad Faraz Hussain earned his Master of Science in Electronics & Information Engineering from the South China University of Technology, China (2017–2019), achieving an impressive 90%. His thesis focused on “Speaker Recognition with Emotional Speech,” showcasing his expertise in audio processing. He completed his Bachelor of Science in Electrical Engineering from the University of Engineering and Technology, Peshawar, Pakistan (2009–2014), with a thesis on “ZigBee-Based Wireless Sensor Network for Building Safety Monitoring.”

💼 Professional Experience:

Ahmad has a diverse professional journey, beginning as a Research Assistant at the South China University of Technology (2017–2019), where he worked on cutting-edge projects in speech recognition. Before that, he served as a Lecturer at Polytechnical College Kohat (2016–2017), imparting knowledge to aspiring engineers. His technical expertise was further honed during his two-year tenure as a Technical Engineer at PTCL, Pakistan, where he worked on telecommunications and networking solutions.

🏆 Awards and Honors:

Ahmad was a recipient of the prestigious CSC Scholarship, which enabled him to pursue his master’s degree in China. His academic excellence and dedication to research have earned him recognition in both academic and professional circles.

🔬 Research Focus:

Ahmad’s research interests lie in audio signal processing, speaker recognition, speech recognition, and wireless sensor networks. His work focuses on developing advanced methodologies for improving speech-based systems and enhancing security through smart sensor networks. His contributions to these fields are evident in his multiple publications and research projects.

🔚 Conclusion:

Ahmad Faraz Hussain is a dedicated researcher and engineer with a strong foundation in speech and wireless sensor technologies. His academic achievements, professional experience, and research contributions highlight his commitment to innovation and education. With a passion for higher learning and community service, he continues to make impactful contributions to the field of electronics and information engineering. 🚀

📚 Publications:

Three-Dimensional Dynamic Positioning Using a Novel Lyapunov-Based Model Predictive Control for Small Autonomous Surface/Underwater Vehicles

Fish Detection and Classification Based on Improved ViT

ZigBee-Based Wireless Sensor Network for Building Safety Monitoring – Published in the Journal of TWASP. Read here.

Speaker Recognition with Emotional Speech – Published in GSJ. Read here.

Speech Emotion Recognition – Under review.

ZigBee and GSM-Based Security System for Business Places– Accepted for publication.

Internet of Things-Based Information System for Smart Wireless Sensor Healthcare Applications – Submitted for review.

Carolina Magalhães | Machine Learning | Best Researcher Award

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Dr. Carolina Magalhães | Machine Learning | Best Researcher Award

Investigadora, INEGI – Instituto de Ciência e Inovação em Engenharia Mecânica e Industrial, Portugal

👩‍🔬 Carolina Magalhães is a dedicated biomedical engineer and PhD candidate with expertise in applying AI and imaging technologies to healthcare challenges. Based in Porto, Portugal, she combines her passion for modern technology with a problem-solving mindset to develop innovative solutions in skin cancer diagnostics. Carolina has worked collaboratively with clinical experts to bridge research and practical applications, contributing significantly to advancing imaging-based decision support systems.

Publication Profile

ORCID

Education

🎓 Carolina holds a PhD in Biomedical Engineering from the Faculdade de Engenharia da Universidade do Porto (2020–2024). She also completed her MSc in Biomedical Engineering at the same institution (2016–2018) and earned her Bachelor’s in Bioengineering – Biomedical Engineering from Universidade Católica Portuguesa (2013–2016).

Experience

💼 Carolina has a rich research background, currently serving as a Graduate Research Fellow at INEGI, focusing on skin lesion diagnosis using multispectral imaging. Her work spans from leveraging machine learning models for skin cancer classification to thermal and UV imaging techniques. Previously, she contributed to projects on hyperhidrosis diagnosis, prosthetic device design, and thermal image analysis for musculoskeletal disorders, collaborating with leading hospitals and research centers in Portugal.

Research Interests

🔬 Carolina is passionate about exploring artificial intelligence, machine learning, and advanced imaging technologies for healthcare applications. Her interests include developing multispectral imaging systems, improving diagnostic tools for skin cancer, and advancing infrared thermography for clinical support systems.

Awards

🏆 Carolina’s innovative work has been recognized with prestigious research grants from the Foundation for Science and Technology (SFRH/BD/144906/2019) and other funding organizations. These awards have supported her impactful contributions to biomedical engineering and healthcare innovation.

Publications

“Systematic Review of Deep Learning Techniques in Skin Cancer Detection”
BioMedInformatics, 11/2024
Read here

“Skin Cancer Image Classification with Artificial Intelligence Strategies: A Systematic Review”
Journal of Imaging, 10/2024
Read here

“Use of Infrared Thermography for Abdominoplasty Procedures in Patients with Extensive Subcostal Scars: A Preliminary Analysis”
Plast Reconstr Surg Glob Open, 06/2023
Read here

“Classic Versus Scarpa-Sparing Abdominoplasty: An Infrared Thermographic Comparative Analysis”
J Plast Reconstr Aesthet Surg, 06/2023
Read here

“Towards an Effective Imaging-Based Decision Support System for Skin Cancer”
Handbook of Research on Applied Intelligence for Health and Clinical Informatics, 10/2022
Read here