Sarah Marzen | Data Science | Best Researcher Award

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Prof. Sarah Marzen | Data Science | Best Researcher Award

Associate Professor | Keck Graduate Institute, Claremont | United States

Professor Sarah Marzen is a prominent physicist and interdisciplinary researcher based at the W. M. Keck Science Department, representing Pitzer, Scripps, and Claremont McKenna Colleges in California. With a strong foundation in theoretical physics and complex systems, she is widely recognized for her research at the intersection of information theory, neuroscience, and machine learning. Her work explores how biological and artificial systems perceive, predict, and adapt to their environments. Through academic excellence and a commitment to scientific inquiry, she has established herself as a respected voice in computational neuroscience and resource-rational modeling

Professional Profile

Scopus | Google scholar

Education

Professor Marzen earned her Ph.D. in Physics from the University of California, Berkeley, where she conducted pioneering research on “Bio-inspired problems in rate-distortion theory” under the mentorship of Professor Michael R. DeWeese. Prior to her doctoral studies, she completed a Bachelor of Science degree in Physics at the California Institute of Technology (Caltech), reflecting an early and consistent commitment to scientific excellence. She has also participated in several prestigious summer schools and professional development programs, including the Santa Fe Institute’s Complex Systems School and the MIT Kauffman Teaching Certificate Program.

Experience

Dr. Marzen currently serves as Associate Professor of Physics at the W. M. Keck Science Department. Prior to this, she served as an Assistant Professor at the same institution . Her earlier career includes a postdoctoral fellowship at the Massachusetts Institute of Technology, where she collaborated with Professors Nikta Fakhri and Jeremy England. Her teaching experience is complemented by her role as a Seminar XL/LE Facilitator at MIT, underscoring her dedication to student engagement and mentorship.

Research Interests

Professor Marzen’s research focuses on sensory prediction, reinforcement learning, resource rationality, and the integration of information theory with biological systems. She investigates how both living and artificial neural systems process and respond to information in complex, dynamic environments. Her interdisciplinary approach spans computational modeling, machine learning theory, and theoretical neuroscience. She is currently involved in major research initiatives, including an Army Research Laboratory MURI project centered on hybrid biological-artificial neural networks and a series of workshops supported by the Sloan Foundation and Carnegie Institute

Honors

Dr. Marzen has received numerous recognitions for her academic contributions, including serving as Principal Investigator (PI) or Co-PI on several major research grants. Within her institution, she has held key service roles such as membership on the Executive Committee, DEI Committee, and Data Science Curriculum Coherence Committee, reflecting her leadership in fostering academic inclusivity and interdisciplinary learning.

Top Noted Publications

Title: Statistical mechanics of Monod–Wyman–Changeux (MWC) models
Citation: 128
Year of Publication: 2013

Title: On the role of theory and modeling in neuroscience
Citation: 100
Year of Publication: 2023

Title: The evolution of lossy compression
Citation: 65
Year of Publication: 2017

Title: Informational and causal architecture of discrete-time renewal processes
Citation: 46
Year of Publication: 2015

Title: Predictive rate-distortion for infinite-order Markov processes
Citation: 45
Year of Publication: 2016

Conclusion

Professor Sarah Marzen is a highly accomplished academic whose innovative research bridges physics, neuroscience, and artificial intelligence. Her work advances our understanding of how systems learn, adapt, and make decisions under constraints, with implications for both scientific theory and technological development. Through her leadership, mentorship, and scholarly impact, she continues to shape the future of interdisciplinary research and education. Her academic rigor, commitment to collaboration, and visionary research make her a key contributor to the global scientific community.

Prof. Dr Chih-Yung Tsai | Machine learning | Best Researcher Award |

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Prof. Dr Chih-Yung Tsai | Machine learning | Best Researcher Award

Professor, at University of Taipei, Taiwan.

Prof. Dr. Chih-Yung Tsai is a distinguished academic and researcher specializing in electrical engineering and nanotechnology. He is currently a professor at the Department of Electrical Engineering, National Taiwan University (NTU). Dr. Tsai’s work has significantly advanced the fields of nanolithography, integrated circuit design, and advanced manufacturing processes

Professional Profile

Scopus

ORCID

Google Scholar

🎓 Education 

Dr. Tsai earned his Bachelor of Science and Master of Science degrees from National Taiwan University. He then pursued his Ph.D. in Aeronautics and Astronautics, with a minor in Electrical Engineering, at Stanford University, completing it in 2002.

💼 Experience 

From 2002 to 2005, Dr. Tsai served as a Senior Process Engineer in lithography at Intel Corporation. During this time, he worked on performance monitoring and improvement of 193-nm microlithography scanners for Intel’s 90-nm process technology. In 2005, he joined the faculty of NTU’s Department of Electrical Engineering, where he established and directed several research laboratories, including the Nanoscale Design and Fabrication Systems Lab (NDFSL), Particle Beam Precision Patterning and Imaging Lab (PBPPIL), and High-Performance Servo Systems Lab (HPSSL).

🔬 Research Interests 

Dr. Tsai’s research centers on the design and application of advanced control, simulation, signal processing, optimization, and machine learning techniques to solve nanolithography and nanotechnology-related problems. His current focus includes the design and fabrication techniques of exploratory nanoscale integrated circuits at the IRDS 10 nm half-pitch node and beyond. He is also involved in aerospace-related research activities and has conducted research on control system design automation, automotive and aerospace electronics, consumer electronics, and biomedical equipment design.

🏆 Awards 

Dr. Tsai has been recognized for his contributions to the field with several honors. He has been invited by The Japan Society of Applied Physics to serve as Program Committee Section Sub Head in International Microprocesses and Nanotechnology since 2007. He has also been invited to present on innovative applications of helium ion beam nanofabrication and techniques for EUV mask defect detection technology research and development at various international workshops and seminars.

📚 Top Noted Publications 

Title: Applying the theory of planned behavior to explore the independent travelers’ behavior
Author(s): CY Tsai
Citations: 109
Index: African Journal of Business Management 4 (2), 221
Year of Publication: 2010

Title: Using the technology acceptance model to analyze ease of use of a mobile communication system
Author(s): CY Tsai, CC Wang, MT Lu
Citations: 79
Index: Social Behavior and Personality: an international journal 39 (1), 65-69
Year of Publication: 2011

Title: The impact of tour guides’ physical attractiveness, sense of humor, and seniority on guide attention and efficiency
Author(s): CY Tsai, MT Wang, HT Tseng
Citations: 55
Index: Journal of Travel & Tourism Marketing 33 (6), 824-836
Year of Publication: 2016

Title: An analysis of usage intentions for mobile travel guide systems
Author(s): CY Tsai
Citations: 48
Index: African Journal of Business Management 4 (14), 2962
Year of Publication: 2010

Title: Learning under time pressure: Learners who think positively achieve superior learning outcomes from creative teaching methods using picture books
Author(s): CY Tsai, YH Chang, CL Lo
Citations: 39
Index: Thinking Skills and Creativity 27, 55-63
Year of Publication: 2018

Conclusion

Prof. Dr. Chih-Yung Tsai’s illustrious career in electrical engineering and nanotechnology has significantly advanced the understanding and application of nanolithography and integrated circuit design. His dedication to research, education, and innovation continues to inspire and shape the future of technology.

Mr Fanyu Meng | Nonlinear Dependence | Best Researcher Award |

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Mr. Fanyu Meng | Nonlinear Dependence | Best Researcher Award

ShanDong University, China.

Mr. Fanyu Meng, born in May 1998 in Jinan, Shandong Province, is a dedicated and emerging scholar in the field of quantitative economics and econometrics. A member of the Chinese Communist Party, he demonstrates a strong foundation in mathematics, statistics, and economic theory, combined with a growing research profile in econometric modeling and data science. He is currently pursuing his Ph.D. at Shandong University and is recognized for his intellectual rigor, methodological expertise, and academic excellence.

Professional Profile

Scopus

Education 🎓

Mr. Meng is currently enrolled in a direct-track doctoral program (Ph.D.) in Quantitative Economics at Shandong University (2022.09–2025.06). He previously completed his Master’s degree in Financial Mathematics and Financial Engineering at the same university from 2020 to 2022. His undergraduate studies were undertaken at Ocean University of China, where he earned a Bachelor of Science in Mathematics and Applied Mathematics from 2016 to 2020. This strong academic journey laid a robust foundation for his work in economic modeling and statistical analysis.

Experience 💼

Mr. Meng has actively participated in several high-level research projects. These include a national-level project on statistical theory and applications in multi-arm robotic game learning (2022–2024), funded by the National Bureau of Statistics. He also contributed to a fintech project on modern agricultural risk management (2020–2022), supported by the Jinan Municipal Science and Technology Bureau. Additionally, he was involved in the “Qingniao Plan” internship program with the Jinan Survey Team of the National Bureau of Statistics in 2020. These experiences have enriched his practical understanding of statistical theory and economic applications.

Research Interests 🔬

Mr. Meng’s research centers on econometric theory and applied econometrics, with a particular interest in time series analysis, panel data models, and structural change detection. He focuses on quantile-based methods, unobserved factor models, semiparametric techniques, and sparse estimation approaches. His work aims to uncover complex, nonlinear relationships within economic systems, contributing to both theoretical advancements and real-world policy modeling.

Awards 🏆

Throughout his academic career, Mr. Meng has received multiple honors. These include a Graduate Second-Class Scholarship and an Excellent Student Source Award during his doctoral studies. As an undergraduate, he was named a Shandong Province Outstanding Graduate, and was awarded several university-level scholarships such as the Shengwu Scholarship, Li Xiaoyong Scholarship, and honors for academic excellence and student leadership. His competitive achievements include prizes in the Shandong Mathematical Modeling Contest and the China Mathematical Modeling Competition.

Top Noted Publications 📚

Mr. Meng has authored peer-reviewed papers published in respected international journals. His article,

“Uncovering Nonlinear Dependencies in the Treasury-Funds Rate Spread: A Quantile-Based Explanation,”

appeared in Finance Research Letters (SSCI, Q1, 2025). Another co-authored paper on adaptive change point detection is set to be published in Communications in Statistics – Simulation and Computation (SCI, Q3, 2025). He is the corresponding author of a paper currently under external review, which applies Bootstrap entropy-weighted TOPSIS in the assessment of China’s provincial digital economy. He also has several ongoing working papers exploring advanced panel models, binary regression, and break estimation techniques.

Conclusion

Mr. Fanyu Meng represents a new generation of quantitatively skilled economists with a deep understanding of statistical modeling and data-driven economic analysis. His strong academic background, ongoing scholarly contributions, technical skills, and recognized potential make him a highly promising researcher. With continued publication and international collaboration, he is well-positioned to make significant contributions to the field of econometrics and quantitative economics.

Assoc. Prof. Dr Sadullah Çelik | Quantitative Decision Methods | Best Academic Researcher Award |

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Assoc. Prof. Dr. Sadullah Çelik | Quantitative Decision Methods | Best Academic Researcher Award

Aydın Adnan Menders University,Turkey

Assoc. Prof. Dr. Sadullah Çelik is a dynamic academician specializing in international trade, finance, and quantitative decision-making. With a strong foundation in mathematics and econometrics, he brings a multidisciplinary perspective to business and economic sciences. He is currently serving as a faculty member at Aydın Adnan Menderes University, Faculty of Economics and Administrative Sciences, Department of International Trade and Finance. Known for his dedication to teaching, research, and academic leadership, Dr. Çelik has contributed significantly to the development of innovative curricula and the advancement of data-driven decision-making in international business contexts.

profile

Scopus

Orcid

Google scholar

Education

Dr. Çelik earned his Bachelor’s degree in Mathematics from Celal Bayar University (2007–2011), followed by a Master’s degree in Geometry from Ege University, Institute of Science (2011–2013). He later pursued a Ph.D. in Econometrics from Uludağ University, Institute of Social Sciences (2013–2018), solidifying his expertise in statistical and econometric analysis. Demonstrating intellectual versatility, he also completed an associate degree in Opticianry from Ege University’s Atatürk Vocational School of Health Services.

Experience

Dr. Çelik began his academic career as a Research Assistant in the Department of Econometrics at Adnan Menderes University (2014–2021). He later joined the Department of International Trade and Finance, where he was promoted to Doctor Lecturer (2022) and subsequently to Associate Professor (2023). He has also served as the Vice Chair of the Department, showcasing his leadership abilities in academic management and curriculum development. His extensive teaching portfolio includes undergraduate and graduate-level courses such as Econometrics, Research Methods, E-commerce, International Business, and Innovation Management.

Research interest

Dr. Çelik’s primary research interests lie in Quantitative Decision Methods, Data Analytics, Business Statistics, and International Trade and Finance. His work bridges the analytical rigor of mathematics and econometrics with practical applications in global business environments. He is especially interested in how data-driven strategies can enhance international business operations, risk analysis, and financial decision-making processes.

Awards

Dr. Çelik has achieved notable academic milestones, including his appointment as Associate Professor in 2023, marking a significant recognition of his scholarly contributions. His continuous academic promotions—from Research Assistant to Associate Professorship—reflect his commitment to excellence in research, teaching, and service. While specific national or international awards are not detailed, his academic progression itself is a testament to merit and recognition within the Turkish higher education system.

Publications

1. Big Data and Data Visualization by S. Çelik and E. Akdamar, published in Academic Perspective International Refereed Journal of Social Sciences, Issue 65, pages 253–264, in 2018, has received 32 citations.

2. Analyzing Shakespeare’s Corpus with Text Mining by S. Steel, published in MANAS Journal of Social Studies, Volume 9, Issue 3, pages 1343–1357, in 2020, has been cited 17 times.

3. The Importance of Big Data Technologies for Businesses by S. Steel, published in Social Sciences Studies Journal, Volume 3, Issue 6, pages 873–883, in 2017, has accumulated 14 citations.

4. Big Data by S. Steel, published by Night Library, publication number 25931, page 176, in 2018, has received 13 citations.

5. High-frequency Words Have Higher Frequencies in Turkish Social Sciences Articles by N. Gursakal, S. Çelik, and S. Özdemir, published in Quality & Quantity, Volume 57, pages 1865–1887, in 2023, has received 7 citations.

Conclusion

In summary, Assoc. Prof. Dr. Sadullah Çelik is a well-rounded academic with a robust educational background, a strong teaching record, and a research portfolio focused on the intersection of data analytics and international business. His career reflects both depth and breadth in the social sciences, with an emphasis on analytical precision and practical application. With further expansion into international publications and collaborative research, Dr. Çelik is poised to make even greater contributions to academia and the global business research community.

Dr M sangeetha | Operations research | Excellence in Research Award |

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Dr. M sangeetha | Operations research | Excellence in Research Award | 

Professor, at Dr.N.G.P.Arts and Science college , India.

Dr. M. Sangeetha is a Professor of Mathematics with over 22 years of teaching experience and 7 years of dedicated research in Fuzzy Operations Research. She has a strong academic foundation, with expertise in mathematical modeling, optimization techniques, and decision-making processes. Her research contributions, publications, and mentorship of Ph.D. scholars demonstrate her commitment to advancing mathematical sciences.

Professional Profile

Scopus

Education 🎓

Dr. Sangeetha holds a Ph.D. in Mathematics from Chikkanna Government Arts College, Tirupur (2018). She completed her M.Phil. (2009) and M.Sc. (2001) in Mathematics from Government Arts College, Coimbatore. Additionally, she earned a B.Ed. in Mathematics (2010) from St. Marks B.Ed. College and a Postgraduate Diploma in Operations Research (PGDOR, 2015) from Nirmala College for Women, Bharathiar University. She has also completed online certifications in Graph Theory (NPTEL, 2020) and Basics of Python (Infosys Springboard, 2022), showcasing her commitment to continuous learning.

Professional Experience 💼

With 22+ years of college teaching experience, Dr. Sangeetha has been instrumental in shaping the careers of numerous students. She has also mentored 6 Ph.D. scholars (2 submitted synopsis, 6 ongoing), 1 M.Phil. student, and multiple M.Sc. research projects. Her role as an educator extends beyond teaching, fostering a research-driven academic environment.

Research Interests 🌍

Dr. Sangeetha specializes in Fuzzy Operations Research, focusing on fuzzy transportation problems, multi-objective optimization, and intuitionistic fuzzy systems. Her work contributes to decision-making models, logistics, and applied mathematics, addressing real-world challenges through advanced computational techniques and mathematical frameworks.

Awards & Honors 🏆

Dr. Sangeetha has been recognized for her contributions to research and academics. Her work has been published in Scopus-indexed journals, reflecting her commitment to high-quality research. She has also played a significant role in mentoring Ph.D. scholars and guiding research projects, contributing to the academic growth of her institution.

Top Noted Publications 📚

Dr. Sangeetha has authored several research papers in Scopus-indexed journals, focusing on fuzzy logic, transportation problems, and optimization techniques. Some of her notable publications include:

Fuzzy Largest Cost Entry Method of Transportation Problem Using Heptagonal Fuzzy Numbers (Nonlinear Studies, Scopus-indexed)

Multi-Objective Fuzzy Fully Linear Programming Transportation Problem (Mathematical Sciences International Research Journal, Scopus-indexed)

Similarity Measure Model in Intuitionistic Fuzzy Transportation Problem (IJPAM, Scopus-indexed)

Conclusion

Dr. Sangeetha has a strong foundation in research, publications, and mentorship, making her a deserving candidate for the Excellence in Research Award. Strengthening international collaborations, increasing high-impact publications, and securing research grants will further enhance her profile.