Ivett-Greta Zsak | Data-Driven | Best Researcher Award

PhD Candidate, Technical University of Cluj-Napoca, Romania

Ms. Ivett-Greta Zsak, a Romanian architect, lecturer, and PhD candidate at the Technical University of Cluj-Napoca, is an influential figure in sustainable architecture and heritage preservation. She earned her Diploma in Architecture from the University of Oradea under the board of UAUIM Bucharest and has since established herself as a practicing architect and administrator of Zero Positive Architecture SRL. Currently serving as an expert at Living Lab 10 within the EU GREEN European University Alliance for Sustainability and as an associate lecturer at the University of Oradea, she combines academic engagement with professional innovation. Her doctoral research focuses on civil engineering and installation, contributing to frameworks such as the Building Identity Passport (BIP) for prefabricated housing rehabilitation, published in Sustainability in 2025. She is actively engaged in heritage protection as the coordinator of the Ambulance for Monuments – Bihor branch and has co-authored the national Architecture Guidelines for Rural Areas. Recognized with multiple awards, including two first prizes at the 2023 Transylvania Architecture Biennale, she continues to impact both theory and practice in architecture. With 11 citations across 2 documents and an h-index of 2, her scholarly work, though emerging, reflects her growing influence at the intersection of sustainable design, cultural heritage, and participatory architecture.

Featured Publications

Zsak, I.-G., Pescaru, A. H., & Manea, L.-D. (2025). Beyond energy efficiency: Integrating health, building pathology, and community through the building identity passport for prefabricated housing. Sustainability, 17(17), 8176.

Zsak, G. I., Pescaru, A. H., & Manea, L.-D. (2024). Analysis on using 3D scanning and BIM to reduce the physical and non-physical construction waste for sustainable fireproofing of steel trusses. Sustainability, 16(5), 1832.

Zsak, G. I. (2020). Ghiduri de arhitectură pentru încadrarea în specificul local din mediul rural. The Order of Architects of Romania.

Zsak, G. I. (2019, September 18). Regeneration of the industrial heritage in the central area of Oradea. In Materials Science and Engineering Conference Series (Vol. 603). IOP Publishing.

Prof. Sarah Marzen | Data Science | Best Researcher Award

Prof. Sarah Marzen – Professor | Claremont McKenna College | United States

Sarah E. Marzen is a highly accomplished physicist and interdisciplinary researcher based at the W. M. Keck Science Department, serving Pitzer, Scripps, and Claremont McKenna Colleges. Her work bridges physics, biology, and artificial intelligence, with a central focus on sensory prediction, information theory, and reinforcement learning. A frequent speaker at global conferences, Marzen is known for her analytical insight and leadership in computational neuroscience. She has held prestigious fellowships, organized influential workshops, and served on multiple editorial boards. Her dynamic academic contributions have garnered recognition across the scientific community, cementing her position as a leader in theoretical and applied information sciences.

Publication Profile

Scopus

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Education Background

Sarah Marzen earned her Ph.D. in Physics from the University of California, Berkeley, where her dissertation explored bio-inspired problems in rate-distortion theory under the mentorship of Professor Michael R. DeWeese. Prior to that, she completed her B.S. in Physics at the California Institute of Technology. Her early academic promise was recognized through numerous merit scholarships, including the Caltech Axline Award. She further enhanced her interdisciplinary understanding through participation in prominent summer schools, such as the Santa Fe Institute Complex Systems School and the Machine Learning Summer School, setting a strong foundation for her later research in theoretical and computational neuroscience.

Professional Experience

Currently an Associate Professor of Physics at the W. M. Keck Science Department, Sarah Marzen has held academic and research positions at some of the most prestigious institutions. Following her Ph.D., she was a postdoctoral fellow at MIT, collaborating with renowned scholars such as Nikta Fakhri and Jeremy England. She has also served as a facilitator and mentor at MIT and a research assistant at Caltech and the MITRE Corporation. Beyond academia, she advises a stealth startup focused on human cognition. Through her career, Marzen has balanced research, teaching, and mentorship while contributing significantly to interdisciplinary data science initiatives and diversity committees.

Awards and Honors

Sarah Marzen has been recognized with numerous accolades, including the Mary W. Johnson Faculty Scholarship Award and the prestigious National Science Foundation Graduate Research Fellowship. She was a finalist for the SIAM-MGB Early Career Fellowship and has received travel grants from OCNS, Entropy, and ILIAD. Her excellence in research and academic service is reflected in her appointments to editorial boards, guest editorships of top-tier journals, and organizing roles for workshops and symposia. Early in her academic journey, she was an Intel Science Talent Search Finalist and a U.S. Physics Team finalist, laying the groundwork for a distinguished scientific career.

Research Focus

Marzen’s research centers on the intersection of information theory, sensory prediction, reinforcement learning, and biological systems. She investigates how both natural and artificial systems use limited resources to make accurate predictions in dynamic environments. Her work incorporates resource-rationality, complexity theory, and dynamical systems to understand neural coding and learning processes. Marzen also explores the mathematical structures underlying neural computation and opinion dynamics, applying her expertise across machine learning, computational neuroscience, and cognitive science. Her contributions have led to breakthroughs in understanding neural memory, adaptive learning, and predictive representations in both biological and engineered systems.

Conclusion

Sarah E. Marzen exemplifies the ideal of a multidisciplinary scientist who blends deep theoretical insight with practical relevance. From her early accolades in physics to her leadership in computational neuroscience and information theory, she has contributed meaningfully to several scientific domains. Her commitment to teaching, diversity, and mentorship further enhances her role as a scholar and educator. With an impressive portfolio of publications, grants, and collaborations, Marzen continues to push the boundaries of how information and computation intersect in both biological and artificial systems, positioning her as a thought leader in contemporary science.

Top Publications

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

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

The evolution of lossy compression
Published Year: 2017
Citation: 65

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

Predictive rate-distortion for infinite-order Markov processes
Published Year: 2016
Citation: 45