Eirini Eleni Tsiropoulou | Engineering | Best Researcher Award

Assoc. Prof. Dr. Eirini Eleni Tsiropoulou | Engineering | Best Researcher Award

Assoc. Prof. Dr. Eirini Eleni Tsiropoulou, Arizona State University, United States

Dr. Eirini Eleni Tsiropoulou is a tenured Associate Professor at the School of Electricahttps://academicexcellenceawards.com/eirini-eleni-tsiropoulou-engineering-best-researcher-award-2472/engil, Computer, and Energy Engineering at Arizona State University. Born in Athens, Greece, she is a U.S. lawful permanent resident fluent in Greek, English, and German. With expertise in game theory, reinforcement learning, distributed decision-making, and artificial intelligence-driven cyber-physical systems, Dr. Tsiropoulou has significantly contributed to optimizing dynamic systems under uncertainty. Her research focuses on resource orchestration in constrained environments and control of interdependent systems. Before joining Arizona State University, she held academic and research positions at the University of New Mexico, the University of Maryland, and the University of Texas at Dallas. She has been recognized globally for her contributions to engineering, including prestigious awards for research excellence, outstanding reviewing, and best paper distinctions. As a leader in her field, she serves on various IEEE committees and continues to shape the future of smart and adaptive systems.

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Suitability of Dr. Eirini Eleni Tsiropoulou for the Research for Best Researcher Award

Dr. Eirini Eleni Tsiropoulou is a distinguished researcher in Electrical, Computer, and Energy Engineering, currently serving as an Associate Professor with tenure at Arizona State University. Her research focuses on game theory, reinforcement learning, distributed decision-making, and optimization in dynamic systems, demonstrating a strong interdisciplinary approach to complex problem-solving. Her extensive professional experience across prestigious institutions—including the University of New Mexico, Sandia National Laboratories, and the University of Maryland—underscores her leadership in academia and applied research.

Her impressive record of accolades highlights her significant contributions to the field. She has received numerous awards for research excellence, including the IEEE Early Career Award, multiple Best Paper Awards, and the NSF CRII Award, which showcases her ability to secure competitive funding. Furthermore, her recognition as an IEEE Senior Member and her leadership in various IEEE conferences and technical committees reinforce her impact on the global research community.

🎓 Education

Dr. Eirini Eleni Tsiropoulou holds a Ph.D. in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), where she specialized in optimal resource allocation in next-generation wireless networks. She also earned an MBA in Project Management from NTUA, ranking in the top 1% of her class. Her MBA thesis focused on emissions analysis in power sectors through mathematical modeling. Additionally, she holds a five-year Diploma in Electrical and Computer Engineering from NTUA, again ranking among the top 1% of her class. Her diploma thesis explored game-theoretic approaches to power control in CDMA networks. Through her rigorous academic training, Dr. Tsiropoulou developed a strong foundation in systems optimization, distributed algorithms, and network management, setting the stage for her impactful research career. Her interdisciplinary education blends engineering excellence with strategic project management, equipping her to address complex challenges in modern technological systems.

💼 Professional Experience

Dr. Tsiropoulou is currently an Associate Professor with Tenure at Arizona State University. Previously, she held the same role at the University of New Mexico (UNM). She also served as a PO Contractor at Sandia National Laboratories, contributing to high-impact national security projects. Earlier, she worked as an Assistant Professor at UNM, a Postdoctoral Associate at the University of Maryland and the University of Texas at Dallas, and a Research Fellow at NTUA. Her career spans academia, research, and collaboration with industry and government agencies. She has led multiple NSF-funded projects and guided students in cutting-edge research. Her expertise in reinforcement learning, cyber-physical systems, and optimization has led to transformative advancements in wireless networks and intelligent systems. She actively contributes to IEEE conferences and editorial boards, shaping the future of network science and engineering through interdisciplinary innovation and leadership.

🏅 Awards & Recognition

Dr. Tsiropoulou has received numerous prestigious awards for her contributions to engineering. She was honored as an Excellent Reviewer by IEEE Transactions on Network Science and Engineering (2024) and the IEEE OJCOMS (2024). She won the Best Paper Runner-up Award from IEEE Transactions on Mobile Computing (2023) and received the Research and Creative Works Leader Award at UNM (2023). Recognized for excellence in education, she earned the IEEE Albuquerque Section’s Outstanding Engineering Educator Award (2021). Her research contributions were acknowledged with the IEEE Communications Society Early Career Award (2020) and multiple Best Paper Awards at top-tier conferences like INFOCOM and BRAINS. She was named an IEEE Senior Member (2021) and served on elite IEEE technical committees. Before joining UNM, she received the N2 Women Rising Stars in Networking and Communications Award (2017). Her accolades underscore her leadership and innovative contributions to engineering and academia.

🌍 Research Skills On Engineering

Dr. Tsiropoulou’s research expertise spans game theory, reinforcement learning, optimization of dynamic systems, and distributed decision-making. She specializes in designing adaptive cyber-physical systems for resource-constrained environments, ensuring efficiency in networked infrastructures. Her work integrates stochastic modeling and artificial intelligence to tackle real-world engineering problems. She has made significant contributions to network resource orchestration, security, and autonomous systems control. A key aspect of her research is the application of software-defined networking and AI-driven optimization in complex, uncertain environments. Her interdisciplinary approach enables the development of robust, intelligent frameworks for next-generation wireless networks and smart infrastructures. She has successfully led multiple NSF-funded research projects, collaborating with academia and industry. As an editorial board member for top IEEE journals, she advances knowledge in network science and engineering. Her pioneering research continues to drive innovation in computational intelligence, cybersecurity, and real-time system optimization.

📖 Publication Top Notes

  • Data offloading in UAV-assisted multi-access edge computing systems under resource uncertainty
    Authors: PA Apostolopoulos, G Fragkos, EE Tsiropoulou, S Papavassiliou
    Citation: 170
    Year: 2021
    Journal: IEEE Transactions on Mobile Computing 22 (1), 175-190

  • Game theory for wireless communications and networking
    Authors: Y Zhang, M Guizani
    Citation: 162
    Year: 2011
    Publisher: CRC Press

  • Risk-aware data offloading in multi-server multi-access edge computing environment
    Authors: PA Apostolopoulos, EE Tsiropoulou, S Papavassiliou
    Citation: 161
    Year: 2020
    Journal: IEEE/ACM Transactions on Networking 28 (3), 1405-1418

  • Machine learning and intelligent communications
    Authors: XL Huang, X Ma, F Hu
    Citation: 145
    Year: 2018
    Journal: Mobile Networks and Applications 23, 68-70

  • Interest, energy and physical-aware coalition formation and resource allocation in smart IoT applications
    Authors: EE Tsiropoulou, ST Paruchuri, JS Baras
    Citation: 141
    Year: 2017
    Conference: 51st Annual Conference on Information Sciences and Systems (CISS), 1-6

  • Wireless powered public safety IoT: A UAV-assisted adaptive-learning approach towards energy efficiency
    Authors: D Sikeridis, EE Tsiropoulou, M Devetsikiotis, S Papavassiliou
    Citation: 115
    Year: 2018
    Journal: Journal of Network and Computer Applications 123, 69-79

  • Resource Allocation in Next-Generation Broadband Wireless Access Networks
    Authors: C Singhal, S De
    Citation: 115
    Year: 2017
    Publisher: IGI Global

  • Interest-aware energy collection & resource management in machine to machine communications
    Authors: EE Tsiropoulou, G Mitsis, S Papavassiliou
    Citation: 111
    Year: 2018
    Journal: Ad Hoc Networks 68, 48-57

  • Big data in complex and social networks
    Authors: MT Thai, W Wu, H Xiong
    Citation: 110
    Year: 2016
    Publisher: CRC Press

  • Price and risk awareness for data offloading decision-making in edge computing systems
    Authors: G Mitsis, EE Tsiropoulou, S Papavassiliou
    Citation: 103
    Year: 2022
    Journal: IEEE Systems Journal 16 (4), 6546-6557

Siyuan Song | Engineering | Best Researcher Award

Assoc. Prof. Dr. Siyuan Song | Engineering | Best Researcher Award

👤 Assoc. Prof. Dr. Siyuan Song, Arizona State University, United States

Dr. Siyuan Song is an Associate Professor at Arizona State University’s Del E. Webb School of Construction, within the School of Sustainable Engineering and the Built Environment. He specializes in construction safety, AI in construction, and workforce development. Dr. Song earned his Ph.D. in Civil Engineering from the University of Alabama, where he focused on construction equipment productivity. He has a strong background in construction engineering and management, which he combines with cutting-edge research in construction automation and robotics. He is dedicated to advancing safety in the construction industry through innovative training programs and workforce development initiatives. Dr. Song has contributed extensively to the field with a focus on enhancing safety protocols in high-risk environments, such as construction sites and surface mining.

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🌟  Suitability For the Best Researcher Award

Siyuan Song, Ph.D., is an exceptional candidate for the Research for Best Researcher Award due to his extensive contributions to construction safety, workforce development, and AI in construction. As an Associate Professor at Arizona State University, Dr. Song has built a distinguished academic and professional portfolio. His research focuses on addressing critical issues in construction, such as workplace safety, health training, automation, and robotics. His work aligns with key global challenges, particularly in improving safety and health conditions for construction workers, an area in which he has secured significant research funding.

Dr. Song’s professional achievements include receiving multiple prestigious awards, such as the Best Division Paper Award from the American Society for Engineering Education (ASEE) in 2023, and the Outstanding Contribution to Workplace Industry Training Award at the Immersive Learning Research Network (iLRN) Annual Conference in 2023. His dedication to advancing construction safety is evident in his leadership of numerous research projects funded by organizations like the Department of Labor (OSHA and MSHA), focusing on heat-related illness prevention, hazard awareness, and worker safety.

🎓 Education

Dr. Song completed his Ph.D. in Civil Engineering from the University of Alabama in 2017, where his dissertation focused on “Construction Equipment Travel Path Visualization and Productivity Evaluation.” He also holds a Master of Science in Civil Engineering, with a thesis on “Location-Based Tracking of Construction Equipment for Automated Cycle-Time Analysis.” His undergraduate degree, a Bachelor of Science in Construction Engineering and Management, was awarded by Suzhou University of Science and Technology in 2014. His academic path has been defined by his commitment to developing innovative solutions to enhance safety and productivity in the construction industry.

💼  Professional Experience

Dr. Song has extensive teaching and research experience in the field of construction engineering. He currently serves as an Associate Professor at Arizona State University, where he focuses on AI-driven solutions in construction safety. Prior to this, Dr. Song was an Assistant Professor at the University of Alabama and the University of Southern Mississippi. His career has been marked by a strong focus on workforce safety, training, and the use of technology to address challenges in the construction sector. He has also contributed significantly to research grants related to occupational safety and health.

🏅 Awards and Recognition

Dr. Song has received numerous awards for his contributions to construction safety and engineering education. Notable honors include the 2023 Best Division Paper Award from the American Society for Engineering Education (ASEE) Annual Conference, and the 2023 University of Alabama 18 Under 31 Young Alumni Award. He also earned the 2022 ASCE ExCEEd Teaching Fellow Award for Excellence in Civil Engineering Education. Dr. Song’s early academic achievements were recognized through several awards at Suzhou University of Science and Technology, including the Outstanding Student Awards and Outstanding Student Leader awards, reinforcing his leadership and excellence in the field of engineering.

🌍 Research Skills On Engineering

Dr. Song’s research is focused on construction safety and the integration of AI and robotics into the industry. He has expertise in workforce development, workplace safety training, and the automation of construction processes. His research methods often combine traditional construction engineering approaches with emerging technologies like AI, data analytics, and robotics. Dr. Song is passionate about enhancing safety standards on construction sites and has developed training programs aimed at preventing heat-related illnesses and improving hazard awareness for workers in high-risk environments.

📖 Publication Top Notes

  • Improving tolerance control on modular construction project with 3D laser scanning and BIM: A case study of removable floodwall project
    • Authors: H Li, C Zhang, S Song, S Demirkesen, R Chang
    • Citation: Applied Sciences 10 (23), 8680
    • Year: 2020
  • Construction site path planning optimization through BIM
    • Authors: S Song, E Marks
    • Citation: ASCE International Conference on Computing in Civil Engineering 2019, 369-376
    • Year: 2019
  • Fuzzy Multicriteria Decision‐Making Model for Time‐Cost‐Risk Trade‐Off Optimization in Construction Projects
    • Authors: MA Alzarrad, GP Moynihan, MT Hatamleh, S Song
    • Citation: Advances in Civil Engineering 2019 (1), 7852301
    • Year: 2019
  • Impact variables of dump truck cycle time for heavy excavation construction projects
    • Authors: S Song, E Marks, N Pradhananga
    • Citation: Journal of Construction Engineering and Project Management 7 (2), 11-18
    • Year: 2017
  • A study on assessing the awareness of heat-related illnesses in the construction industry
    • Authors: S Song, F Zhang
    • Citation: Construction Research Congress 2022, 431-440
    • Year: 2022
  • Industrial safety management using innovative and proactive strategies
    • Authors: S Song, I Awolusi
    • Citation: Concepts, Applications and Emerging Opportunities in Industrial Engineering
    • Year: 2020
  • Work-related fatalities analysis through energy source recognition
    • Authors: S Song, I Awolusi, Z Jiang
    • Citation: Construction Research Congress 2020, 279-288
    • Year: 2020
  • A Software-Based Approach for Acoustical Modeling of Construction Job Sites with Multiple Operational Machines
    • Authors: B Sherafat, A Rashidi, S Song
    • Citation: Construction Research Congress 2020, 886-895
    • Year: 2020
  • Steel manufacturing incident analysis and prediction
    • Authors: S Song, Q Lyu, E Marks, A Hainen
    • Citation: Journal of Safety, Health and Environmental Research 14 (1), 331-336
    • Year: 2018
  • Impact of discretionary safety funding on construction safety
    • Authors: S Song, I Awolusi, E Marks
    • Citation: Journal of Safety Health and Environmental Research 13 (2), 378-384
    • Year: 2017

 

 

Tran Thi Bich Chau Vo | Industrial and Systems | Academic Excellence Award

Tran Thi Bich Chau Vo | Industrial and Systems | Academic Excellence Award

PhD Candidate at National Kaohsiung University of Science and Technology, Taiwan🎓

Tran Thi Bich Chau VO is an accomplished academic and professional with a strong background in industrial management and engineering. With extensive experience in both academia and the textile and garment industry, she has demonstrated a commitment to advancing knowledge and practical applications in her field. Currently, she is pursuing a Ph.D. in Industrial Engineering and Management, focusing on optimizing workflow processes and efficiency. Her dedication to education, research, and industry innovation positions her as a leading figure in her domain.

Professional Profile 

🎓Education

Tran Thi Bich Chau VO is pursuing a Ph.D. in Industrial Engineering and Management at the National Kaohsiung University of Science and Technology, Taiwan, with a research focus on improving processing efficiency through workflow process reengineering, simulation, and value stream mapping. She previously earned a Master of Engineering in Industrial and Systems Engineering from Ho Chi Minh City University of Technology, where her thesis explored the effects of lean manufacturing in the garment industry. She also holds a Bachelor of Engineering in Garment Technology and Fashion from Ho Chi Minh City University of Technology and Education, with a thesis focused on improving production patterns in the garment sector.

💼Work Experience

Tran Thi Bich Chau VO has been a lecturer at the Faculty of Industrial Management at Can Tho University since 2014, where she imparts her knowledge to the next generation of engineers and managers. Prior to her academic career, she held significant roles in the textile and garment industry, including Head of the Research & Development Department at Thanhcong Textile Garment Investment Trading Joint Stock Company and as a Work Study staff member at Garment Fashion Limited. These roles allowed her to gain valuable industry insights, which she now integrates into her teaching and research.

🔍Research Focus 

Tran Thi Bich Chau VO’s research primarily focuses on enhancing industrial processes through innovative approaches such as workflow process reengineering, simulation, and value stream mapping. Her ongoing Ph.D. research aims to improve processing efficiency, particularly in industrial settings, reflecting her commitment to both theoretical advancement and practical application in the field of Industrial Engineering and Management. Her previous research on lean manufacturing in the garment industry also underscores her interest in optimizing production processes and increasing efficiency.

🏆Awards and Honors

While specific awards and honors are not mentioned in her profile, Tran Thi Bich Chau VO’s continuous advancement in her academic and professional journey, including her pursuit of a Ph.D. and her leadership roles in the industry, suggest a career marked by dedication and recognition within her field.

Conclusion

Tran Thi Bich Chau VO is a promising candidate for the Academic Excellence Award, given her strong academic background, relevant industry experience, and current engagement in impactful research. While her publication record and international collaborations could be areas for development, her dedication to improving process efficiency and her contributions to education make her a strong contender for this award.

📖Publications : 

    1. A comprehensive review of aeration and wastewater treatment 🌊♻️
      • Year: 2024
      • Journal: Aquaculture
      • Author: Vo, T.T.B.C.
    2. Recent Trends of Bioanalytical Sensors with Smart Health Monitoring Systems: From Materials to Applications 🧬📱
      • Year: 2024
      • Journal: Advanced Healthcare Materials
      • Author: Vo, T.T.B.C.
    3. Advances in aeration and wastewater treatment in shrimp farming: emerging trends, current challenges, and future perspectives 🦐🌍
      • Year: 2024
      • Journal: Aqua Water Infrastructure, Ecosystems and Society
      • Author: Vo, T.T.B.C.
    4. Improving processing efficiency through workflow process reengineering, simulation and value stream mapping: a case study of business process reengineering 🔄🏭
      • Year: 2024
      • Journal: Business Process Management Journal
      • Author: Vo, T.T.B.C.
    5. Improvement of Manufacturing Process Based on Value Stream Mapping: A Case Study 🛠️📈
      • Year: 2024
      • Journal: EMJ – Engineering Management Journal
      • Author: Vo, T.T.B.C.
    6. Optimal microgrid design and operation for sustainable shrimp farming ⚡🦐
      • Year: 2023
      • Journal: AIP Conference Proceedings
      • Author: Chau, V.T.T.B.
    7. Risk priority and risk mitigation approach based on house of risk: A case study with aquaculture supply chain in Vietnam 🚨🇻🇳
      • Year: 2023
      • Journal: AIP Conference Proceedings
      • Author: Chau, V.T.T.B.
    8. Optimizing New Product Development through a Systematic Integration of Design for Six Sigma (DFSS) and Theory of Inventive Problem Solving (TRIZ) 🆕🔍
      • Year: 2023
      • Journal: Operations and Supply Chain Management
      • Author: Vo, T.T.B.C.
    9. Improvıng Inventory Tıme in Productıon Lıne through Value Stream Mappıng: A Case Study ⏳🔧
      • Year: 2023
      • Journal: Journal of Engineering Science and Technology Review
      • Author: Vo, T.T.B.C.
    10. Organic dye removal and recycling performances of graphene oxide-coated biopolymer sponge 🧽🔄
      • Year: 2022
      • Journal: Progress in Natural Science: Materials International
      • Author: Vo, T.T.B.C