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.

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

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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.