Abel Sepulveda | Engineering | Best Researcher Award

Best Researcher Award

Abel Sepúlveda
Eidgenössische Technische Hochschule Zürich, Switzerland

Abel Sepúlveda
Affiliation Eidgenössische Technische Hochschule Zürich
Country Switzerland
Scopus ID 57217417207
Documents 27
Citations 332
h-index 9
Subject Area Engineering
Event International Popular Scientist Awards
ORCID 0000-0001-6493-1582

Abel Sepúlveda is an engineering researcher whose published work addresses the interaction between building design, daylight, solar radiation, thermal comfort, outdoor environmental quality, and energy performance. His research record includes collaborative studies published in journals and scholarly book chapters covering building performance and environmental design. The documented publications provide a basis for considering his work within the scope of a Best Researcher Award in Engineering. [1][2]

Abstract

This article presents an academic recognition profile for Abel Sepúlveda in connection with the Best Researcher Award. His research is situated in Engineering and encompasses building environmental performance, daylight availability, solar radiation, thermal comfort, urban heat mitigation, and optimization of building shading and environmental conditions. The supplied research record reports 27 indexed documents, 332 citations, and an h-index of 9. These indicators are accompanied by publications addressing both methodological development and applied evaluation of building and urban environmental performance. [1]

Keywords

Abel Sepúlveda; Engineering; Building Performance; Daylighting; Solar Radiation; Thermal Comfort; Urban Heat Island; Energy Performance; Environmental Design; Shading Optimization; Best Researcher Award.

Introduction

Research in building and environmental engineering increasingly requires simultaneous consideration of energy use, daylight, thermal conditions, occupant experience, and urban environmental effects. Sepúlveda’s supplied publication record reflects this multidisciplinary direction, with studies examining design-stage solar radiation assessment, daylight and thermal comfort, outdoor thermal comfort, urban heat island mitigation, and static shading systems. [3][4]

Research Profile

The supplied Scopus information identifies Abel Sepúlveda with Author ID 57217417207 and reports 27 indexed documents, 332 citations, and an h-index of 9. These metrics provide bibliometric context for the profile but should be interpreted as database-dependent indicators rather than complete measures of research quality or significance. [1]

Research Contributions

A significant theme in the supplied record is the development and evaluation of methods for balancing competing environmental and energy objectives. The 2023 study on solar radiation-based methods considers early design stages in relation to daylight and thermal comfort in office buildings, linking environmental simulation and design decision-making. [5]

Publications

The following selected publications were supplied as part of the research record. DOI links provide persistent identifiers for the corresponding scholarly works.

  1. Urban Shaderade. Building Space Analysis Method for Energy and Sunlight Consideration in Urban Environments. Book chapter, 2023. Contributors: Francesco De Luca; Abel Sepúlveda.
  2. Solar radiation-based method for early design stages to balance daylight and thermal comfort in office buildings. Frontiers of Architectural Research, 2023. Contributors: Abel Sepúlveda; Seyed Shahabaldin Seyed Salehi; Francesco De Luca; Martin Thalfeldt.
  3. Outdoor Thermal Comfort Optimization in a Cold Climate to Mitigate the Level of Urban Heat Island in an Urban Area. Energies, 2023. Contributors: Nasim Eslamirad; Abel Sepúlveda; Francesco De Luca; Kimmo Sakari Lylykangas; Sadok Ben Yahia.
  4. Assessing the applicability of the European standard EN 17037:2018 for office spaces in a cold climate. Building and Environment, 2022. Contributors: Abel Sepúlveda; Francesco De Luca; Toivo Varjas; Jarek Kurnitski.

Research Impact

The supplied bibliometric record reports 332 citations and an h-index of 9 across 27 documents. Such indicators suggest that the published work has received measurable scholarly attention, while the actual interpretation of impact should account for publication age, field-specific citation practices, co-authorship, and database coverage. [1]

Award Suitability

For the purposes of an academic recognition profile, the Best Researcher Award can be evaluated against evidence such as publication activity, documented research contributions, scholarly impact, methodological relevance, and alignment with the award’s Engineering category. The supplied record provides evidence across these dimensions without requiring claims beyond the documented publications and bibliometric information.

Conclusion

Abel Sepúlveda’s documented research profile reflects sustained activity in Engineering, particularly in the analysis and optimization of building and urban environmental performance. His selected publications address daylight, solar radiation, thermal comfort, shading, energy considerations, and urban environmental quality through interdisciplinary and applied research. The supplied bibliometric indicators and publication record provide a structured basis for consideration in the Best Researcher Award category.

References

  1. Elsevier. (n.d.). Scopus author details: Abel Sepúlveda, Author ID 57217417207. Scopus.
    https://www.scopus.com/pages/authors/57217417207
  2. Crossref. (n.d.). Metadata records for scholarly publications by Abel Sepúlveda and collaborators.
  3. Sepúlveda, A., Seyed Salehi, S. S., De Luca, F., & Thalfeldt, M. (2023). Solar radiation-based method for early design stages to balance daylight and thermal comfort in office buildings. Frontiers of Architectural Research.
  4. De Luca, F., Sepúlveda, A., & collaborators. (2022–2023). Selected research publications concerning building environmental performance, daylighting, thermal comfort, and energy considerations. Crossref-indexed records.
  5. Sepúlveda, A., Seyed Salehi, S. S., De Luca, F., & Thalfeldt, M. (2023). Solar radiation-based method for early design stages to balance daylight and thermal comfort in office buildings. Frontiers of Architectural Research.

Afşin Baran Bayezit | Engineering | Research Excellence Award

Mr. Afşin Baran Bayezit | Engineering | Research Excellence Award

Research Assistant at Istanbul Technical University | Turkey

Research engineer specializing in maritime artificial intelligence and control systems, with strong expertise in reinforcement learning, machine learning, and control theory for autonomous platforms. Demonstrates proficiency in developing and validating intelligent control algorithms using Python, embedded systems, and ROS, with hands-on implementation in real-world and model-scale environments. Contributed to advanced research in ship dynamics, autopilot systems, and safety modeling through data-driven approaches. Experienced in integrating sensors, actuators, and high-performance computing tools to optimize system performance. Professional experience reflects a consistent focus on innovative, experimentally validated solutions for autonomous maritime systems, delivering impactful contributions to intelligent navigation, system efficiency, and safety.

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Stergios Mavromatis | Engineering | Research Excellence Award

Dr. Stergios Mavromatis | Engineering | Research Excellence Award

Associate Professor | Technical University of Athens | Greece

Dr. Stergios Mavromatis is an academic researcher specializing in transportation engineering with a strong focus on road design safety, vehicle dynamics, and highway geometric design. His research explores vehicle–road interaction, stopping sight distance, and safety performance on complex road alignments to enhance traffic safety. He has contributed extensively through scholarly publications on traffic behavior, infrastructure risk factors, and data-driven safety evaluation methods. His research approach combines analytical modeling, simulation techniques, and empirical analysis to develop effective and practical engineering solutions. His work has had a meaningful impact on improving road safety practices, supporting infrastructure planning, and informing policy and safety assessment frameworks at broader levels.

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Young Won Kim | Engineering | Research Excellence Award

Dr. Young Won Kim | Engineering | Research Excellence Award

Senior Researcher | Korea Institute of Industrial Technology | South Korea

Dr. Young Won Kim is a researcher specializing in advanced manufacturing, smart materials, and energy harvesting technologies, with strong expertise in additive manufacturing, digital twin systems, and nano/micro-fabrication. His research focuses on triboelectric and piezoelectric nanogenerators, sensor development, and AI-driven predictive modeling for smart manufacturing applications. He has contributed extensively to high-impact international journals as both lead and corresponding author, particularly in nanomaterials, flexible electronics, and biomedical scaffolds. With 68 publications, 1,085 citations, and an h-index of 17, his work reflects strong academic impact. His professional experience spans academic and industrial research environments, integrating machine learning, materials science, and mechanical engineering to develop innovative systems for energy, healthcare, and intelligent industrial technologies.

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Genetic Insights into Avian Influenza Resistance in Jeju Island Chickens

– Journal of Animal Science and Technology, 2025

Getahun Mekuria | Engineering | Research Excellence Award

Mr. Getahun Mekuria | Engineering | Research Excellence Award

Lecturer | Debre Berhan University | Ethiopia

Mr. Getahun Mekuria is an industrial engineering researcher and lecturer with expertise spanning operations research and optimization, manufacturing systems and automation including additive manufacturing, human factors and ergonomics, supply chain and logistics, quality control, continuous improvement, and sustainability. His research approach integrates empirical investigations, digital twin simulations, lean manufacturing, and hybrid technologies such as IoT, big data, and blockchain to optimize productivity, quality, and environmental performance in manufacturing and industrial systems. He has contributed book chapters and numerous peer-reviewed journal articles, exploring topics from service quality and maintenance practices to air pollution assessment and wastewater treatment. Actively engaged in editorial and peer-review roles, he also mentors students in computational methods, system modeling, and industrial design. His work emphasizes practical and sustainable solutions, fostering innovation, operational excellence, and integration of human and technological factors in industrial and manufacturing environments.

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Isye Nurhasanah | Engineering | Research Excellence Award

Mrs. Isye Nurhasanah | Engineering | Research Excellence Award

Lecturer | Institut Teknologi Sumatera | Indonesia

Mrs. Isye Nurhasanah is an urban and regional planning scholar whose work explores spatial and aspatial planning, tourism development, governance, social innovation, participatory planning, and island studies. Her research integrates community-based approaches with sustainability perspectives to understand capacity building, local empowerment, and alternative governance arrangements in small island contexts. She has contributed to studies on ecotourism, landscape change, urban political ecology, and social resilience, producing interdisciplinary insights that bridge planning theory and real-world community needs. Her professional experience spans academic teaching, applied research, and collaborative development projects that support inclusive, knowledge-driven, and sustainable regional growth.

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Jinming Liang | Engineering | Best Researcher Award

Mr. Jinming Liang | Engineering | Best Researcher Award

Nanjing University of Aeronautics and Astronautics | China

Mr. Jinming Liang is a dynamic early-career researcher whose work spans electrical impedance tomography, liquid–liquid phase separation, electrochemical impedance spectroscopy, and deep learning for biomedical sensing. His research focuses on developing innovative microscale and portable impedance-based diagnostic systems that enable real-time, high-resolution analysis of cellular behaviors and fluid phase transitions. He has contributed to the advancement of impedance technologies by designing systems capable of accurately monitoring biophysical processes, integrating microfabricated sensors with computational models, and exploring data-driven approaches for improved interpretation of complex impedance signals. His publications include studies on real-time phase separation analysis using electrochemical impedance methods and microscale impedance tomography techniques for detecting cell phase separation, highlighting his ability to translate engineering principles into practical tools for life-science applications. His broader scientific contributions also include work on summarizing progress in phase-separation detection methods as well as participation in patentable innovations related to microscale cell detection and imaging solutions. Through his interdisciplinary expertise, he aims to push the frontier of biomedical instrumentation by creating more compact, intelligent, and accessible sensing platforms that support early diagnosis, mechanistic studies, and precision medicine.

Profile: Orcid

Featured Publications

Liang, J., Zhao, W., Liu, K., Sun, B., Zhu, C., & Yao, J. (2025). Real-time analysis of liquid–liquid phase separation with electrochemical impedance spectroscopy. Microchemical Journal, 116076.

Liang, J., Gao, B., Liu, K., Chai, X., Ji, J., Sun, B., & Yao, J. (2025). Microscale electrical impedance tomography method for cell phase separation detection. IEEE Nanotechnology Magazine.

Yue-Der Lin | Engineering | Best Researcher Award

Prof. Yue-Der Lin | Engineering | Best Researcher Award

Professor Feng Chia University/Department of Automatic Control Engineering Taiwan

🎓 Dr. Yue-Der Lin is a Professor at the Department of Automatic Control Engineering, Feng Chia University, Taiwan. With extensive experience in biomedical engineering, he specializes in biopotential amplifier design, adaptive signal processing, and EEG signal analysis. His research bridges biomedical and electronic engineering, contributing significantly to advancements in biopotential measurement and bioinformatics.

Profile

Scopus

Google Scholar

Education

📘 Ph.D. in Electrical Engineering (Biomedical Engineering Program)
National Taiwan University, Taiwan (1992–1998)
📘 Master’s in Electrical Engineering (Biomedical Engineering & Electronic Circuit Programs)
National Taiwan University, Taiwan (1987–1989)
📘 Bachelor’s in Electrical Engineering (Control Program)
Chung Yuan Christian University, Taiwan (1983–1987)

Professional Experience

💼 Professor, Department of Automatic Engineering, Feng Chia University (2019–Present)
💼 Director, Department of Automatic Engineering (2016–2017)
💼 Director, Master’s Program of Biomedical Informatics and Biomedical Engineering (2014–2017)
💼 Visiting Scholar, Department of Electrical and Computer Engineering (2007)

Research Interests

🔬 Dr. Lin’s research focuses on:

  • Biopotential amplifier design
  • Adaptive signal processing
  • Biomedical signal analysis (EEG, EMG)
  • Bioinformatics systems
  • Advanced imaging techniques in biomedical engineering

Honors and Awards

🏆 Excellent Research Award, Feng Chia University (2005, 2007–2009, 2011–2019, 2021–2024)
🏆 Distinguished Scholar Award, National Science and Technology Council, Taiwan (2014–2015, 2018–2020, 2022–2024)
🏆 Albert Nelson Marquis Lifetime Achievement Award (2017–2018, 2020)
🏆 Marquis Who’s Who in the World (2008–2010, 2012–2020)
🏆 IBC Leading Engineers of the World (2008, 2013, 2015)

Publications Top Notes:

📚 Below are Dr. Yue-Der Lin’s selected publications with publication year, journal, and citation details:

Lin, Y.-D., Chong, F.-C., Sung, S.-M., et al. “The calculation of complexity in normal and apoplectic EEG signals.” Journal of the Chinese Institute of Engineers, Vol. 21, No. 5, pp. 585-594, 1998. Cited by 56

Lin, Y.-D., Wu, C.-P., et al. “An active comb filter structure for harmonic interference removal.” Journal of the Chinese Institute of Engineers, Vol. 21, No. 5, pp. 605-610, 1998. Cited by 40

Lin, Y.-D., et al. “Preamplifier with a second-order high-pass filtering characteristic.” IEEE Transactions on Biomedical Engineering, Vol. 46, No. 5, pp. 609-612, 1999. Cited by 95

Lin, Y.-D., et al. “An adaptive power-line interference removal technique for biopotential measurement.” Biomedical Engineering—Applications, Basis and Communications, Vol. 12, No. 1, pp. 24-32, 2000. Cited by 23

Lin, Y.-D., et al. “Comments on ‘Line patterns in the mosaic electric properties of human skin—A cross-correlation study’.” IEEE Transactions on Biomedical Engineering, Vol. 49, No. 3, pp. 274, 2002. Cited by 15

Use of acupressure to improve gastrointestinal motility in women after trans-abdominal hysterectomy

Aminoguanidine prevents the impairment of cardiac pumping mechanics in rats with streptozotocin and nicotinamide‐induced type 2 diabetes

A novel approach for decomposition of biomedical signals in different applications based on data-adaptive Gaussian average filtering

Soroush Zare | Engineering | Best Researcher Award

Dr. Soroush Zare | Engineering | Best Researcher Award

Greadaute Research Assistant University of Virginia United States

📚 Soroush Zare is a dedicated Ph.D. Candidate in Mechanical and Aerospace Engineering at the University of Virginia. With expertise in robotics, soft exoskeletons, and Brain-Computer Interface (BCI) technologies, he specializes in designing advanced systems for rehabilitation and assistive applications. His research integrates AI-driven controls with cutting-edge mechanical design.

Profile

Google Scholar

Education

🎓 University of Virginia (2023–Present)

  • Ph.D. in Mechanical and Aerospace Engineering (GPA: 4.0/4.0)
  • Focus: EEG-based motor imagery for wearable textile robotics under an NSF-funded project.

🎓 University of Tehran (2018–2021)

  • M.S. in Mechanical Engineering (GPA: 3.9/4.0)
  • Thesis: Deep Reinforcement Learning Control of Suspended Cable-Driven Robots.

🎓 Shiraz University (2014–2018)

  • B.S. in Mechanical Engineering (GPA: 3.6/4.0)
  • Thesis: Modeling and analysis of bladeless wind turbines.

Experience

💼 Research Assistant, University of Virginia (2023–Present)

  • Developed wearable soft rehabilitation exoskeletons integrating EEG technologies.
  • Innovated reinforcement learning frameworks for intuitive robotic control.

💼 Research Assistant, York University (2022–2023)

  • Led projects on robotic grasping using deep reinforcement learning.

💼 Research Assistant, University of Tehran (2018–2022)

  • Advanced control techniques for Cable-Driven Parallel Robots (CDPRs).

Research Interests

🔬 Robotics, soft exoskeletons, Brain-Computer Interface (BCI) technologies, deep reinforcement learning, EEG-based motor imagery classification, and AI-driven assistive technologies.

Awards

🏆 Honors & Achievements

  • NSF Student Travel Award, IEEE/ACM CHASE (2024)
  • GRADESTAR Fellowship (2023, 2024)
  • Chairperson’s Fellowship (2023)
  • Ranked 2nd among solid design students at Shiraz University.

Publications Top Notes: 

📄 Recent Publications

NeuroMotion: EEG-Based Motor Imagery Control of Wearable Exoskeleton (In preparation).

Kinematic analysis of an under-constrained cable-driven robot using neural networks

Wearable upper limb robotics for pervasive health: A review

Experimental study on the control of a suspended cable-driven parallel robot for object tracking purpose

Reconstructing 3-D Graphical Model Using an Under-Constrained Cable-Driven Parallel Robot

Understanding Human Motion Intention from Motor Imagery Eeg Based on Convolutional Neural Network

A Low-Cost Wearable Exoskeleton for Sitting and Standing Assistance

EEG Motor Imagery Classification using Integrated Transformer-CNN for Assistive Technology Control

MIMO Dynamic Control of a Suspended Underactuated Cable Robot Using Genetic Algorithm

 

 

Jingyang Mao | Engineering | Best Researcher Award

Dr. Jingyang Mao | Engineering | Best Researcher Award

Lecturer Shanghai Institute of Technology China

🧑‍🏫 Dr. Jingyang Mao is a dedicated lecturer at the School of Electrical and Electronic Engineering, Faculty of Intelligence Technology, Shanghai Institute of Technology. With a Ph.D. in Control Science and Engineering from the University of Shanghai for Science and Technology (2022), he specializes in cutting-edge research on networked control systems and cyber-physical systems. His academic journey also includes a visiting scholar tenure at Louisiana State University, USA (2019–2021). Dr. Mao’s work bridges theoretical innovations with practical applications in modern engineering systems.

Profile

Orcid

Education

🎓 Ph.D. in Control Science and Engineering (2022)

  • University of Shanghai for Science and Technology, Shanghai, China

✈️ Visiting Scholar (2019–2021)

  • Department of Electrical and Computer Engineering, Louisiana State University, USA

Experience

👨‍💻 Lecturer (2022–Present)

  • School of Electrical and Electronic Engineering, Shanghai Institute of Technology
  • Focus: Cyber-physical systems, networked control, and adaptive filtering

Research Interests

🔍 Dr. Mao’s research interests lie in the fields of:

  • Cyber-physical systems 🌐
  • Multi-rate systems ⏱️
  • Joint recursive filtering 🔄
  • Unknown input estimation
  • Adaptive event-triggered mechanisms ⚙️

Awards

🏆 Award Nomination: Best Researcher Award
Recognized for groundbreaking contributions to the theory and application of cyber-physical systems.

Publications Top Notes:

📄 “Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms”

Event‐based reduced‐order H∞$H_{\infty }$ estimation for switched complex networks based on T‐S fuzzy model

Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms

Event-Based Distributed Adaptive Kalman Filtering With Unknown Covariance of Process Noises