Assessment Methods in CS Professors and Supervisors

Sevrine Sailleyمشاهده پروفایل

پژوهشگر

Leibniz Institute for Baltic Sea ResearchGermany

Dr. Sevrine Sailley serves as a Senior Scientist at Plymouth Marine Laboratory (PML) within the Marine System Modelling group, where she leads research on zooplankton, food-web, and higher trophic level dynamics. She additionally coordinates PML's Fisheries and Aquaculture Science to Impact Challenges and chairs the ICES Working Group on Integrative Physical-biological Ecosystem Modelling (WGIPEM), demonstrating significant leadership in marine science policy and international collaboration. Her research centers on marine ecosystem modelling with particular emphasis on: Climate change impacts on marine biodiversity and fisheries sustainability Zooplankton dynamics and food-web interactions across trophic levels Carbon and nutrient cycling processes in polar and temperate ecosystems Development of integrated methodologies bridging natural and social sciences Application of inverse modelling and plankton functional type frameworks Analysis of her publication record (2009-2021) reveals progressive focus from fundamental plankton dynamics to applied climate impact assessments, with recent work (2021) providing critical projections of fish biomass reductions in East Africa under climate change scenarios. Her research consistently employs advanced modelling techniques to address real-world marine conservation challenges while contributing to major assessments like the UK Climate Change Risk Assessment. Dr. Sailley actively participates in funded research projects including CS-NOW and the UK 4th Climate Change Risk Assessment, which support her work in ecosystem dynamics and climate impacts. While specific student mentoring details aren't documented, her senior scientist role at PML suggests involvement in training early-career researchers through collaborative projects and institutional supervision frameworks. Her leadership in ICES WGIPEM facilitates international research coordination and methodological standardization across marine ecosystem modelling communities. Within PML's Marine System Modelling group, Dr. Sailley drives research on higher trophic level processes, integrating her expertise in zooplankton dynamics with broader ecosystem analyses. Her work connects laboratory-based modelling with field observations to enhance predictive capabilities for marine ecosystem responses to environmental change, supporting PML's mission in advancing marine science for societal benefit.

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Axel Müllerمشاهده پروفایل

استاد

University of OsloNorway

Professor Axel Müller serves as Research Group Leader for the Norwegian Center for Mineralogy (NORMIN) at the Natural History Museum, University of Oslo. His academic career spans industry, government geological surveys, and academia, with current focus on mineralogy and petrology of granites and pegmatites. Müller maintains dual affiliations as External Researcher at the Natural History Museum of London since 2012. Professor of Mineralogy, University of Oslo (2015-present) Research Group Leader, NORMIN External Researcher, Natural History Museum London (2012-present) Associate Editor, Journal of Geochemical Exploration Scientific Associate, Natural History Museum London Professor Müller's research centers on genetic mineralogy, particularly quartz chemistry in pegmatite systems, with applications for solar cells and microchip production. His work bridges fundamental mineral science and industrial applications, focusing on rare-metal (Li, Sn, W, Nb, Ta, REE) and industrial mineral deposits. Current projects emphasize exploration for critical raw materials essential to the energy transition. His publication record demonstrates consistent output in top geoscience journals, with recent work (2023-2025) focusing on pegmatite exploration techniques, quartz chemistry, and machine learning applications in mineral deposit identification. Müller leads the significant EU-funded GREENPEG project developing tools for locating buried pegmatite deposits containing lithium and high-purity quartz. Society of Economic Geologists (SEG) Society for Geology Applied to Mineral Deposits (SGA) Mineralogical Society of UK and Ireland Leibniz-Sozietät der Wissenschaften zu Berlin Professor Müller actively supervises graduate students through the University of Oslo, with research opportunities connected to NORMIN's analytical facilities and international collaborations. His GREENPEG project provides substantial funding for PhD and postdoctoral positions focused on critical raw materials exploration. The research group maintains strong industry partnerships with mineral exploration companies and geological surveys across Europe. NORMIN serves as Norway's national hub for mineralogical research, housing advanced analytical equipment and the Mars Sample Return Analogue Sample Library (MSR ASL). Müller's group conducts fieldwork across Norwegian pegmatite provinces and European lithium deposits, with recent work in Austria's Wolfsberg deposit and Norway's Tysfjord region.

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Kate Howlandمشاهده پروفایل

استاد

University of SussexUnited Kingdom

Professor Kate Howland is a Professor of Interaction Design in the Department of Informatics at the University of Sussex's School of Engineering and Informatics. Appointed as a Lecturer in 2013 after completing her PhD and MSc at Sussex, she has established herself as a leading researcher in end-user programming and child-computer interaction. As a member of the Creative Technology Group, she leads the Human-Centred Technology lab and has secured substantial research funding from EPSRC, UKRI, and other major funding bodies. Her research focuses on enabling non-experts, particularly children and older adults, to participate meaningfully in technology design and programming. Key research areas include: End-user programming for smart environments Child-computer interaction and educational technology Participatory design methodologies Interactive storytelling systems Technology for autistic children and older adults Professor Howland has supervised seven PhD students to completion between 2020-2025, with research spanning conversational programming interfaces, gesture-based learning, and motion-based sonic systems for autism support. Her recent publications (2023-2025) show increasing focus on embodied programming concepts, concreteness fading in computing education, and innovative approaches to supporting non-verbal communication through full-body interaction systems. Professor Howland currently teaches Technology Enhanced Learning Environments and Applications and Implications of Artificial Intelligence, and serves as Course Convenor for the Computer Science (Conversion) MSc. Her active grants include British Academy funding for climate transition research and UKRI support for dementia-focused storytelling projects. She maintains an active research agenda with strong community engagement components, working directly with user groups often excluded from technology design processes. Her laboratory work emphasizes real-world application and meaningful user involvement throughout the design lifecycle.

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Philipp Bruneمشاهده پروفایل

استاد

Neu-Ulm University of Applied SciencesGermany

Professor Dr. Philipp Brune serves as a prominent academic leader at Neu-Ulm University of Applied Sciences (HNU), holding multiple key positions including Academic Head of TTZ Günzburg, Head of the Master of Artificial Intelligence and Data Analytics program, Head of the Centre for Secure IT Applications and Infrastructures, and Head of the Institute of Agile Product and System Development within the Faculty of Information Management. His career demonstrates a notable transition from physics research (evident in his early 2000-2004 publications) to his current focus on cutting-edge information systems and artificial intelligence. Dr. Brune's research program spans several interconnected domains with particular emphasis on facial emotion recognition systems, legacy system modernization, and secure IT infrastructure development. His work investigates fundamental challenges in AI interpretability, data quality for emotion recognition, and practical approaches to modernizing legacy applications. He has made substantial contributions to understanding the limitations of current facial expression recognition technologies and developing more robust, trustworthy alternatives. Analysis of his recent publications reveals a clear research trajectory toward explainable and trustworthy AI systems, with increasing sophistication in addressing data quality issues and model interpretability challenges. His work bridges theoretical computer science with practical applications across healthcare, marketing, and smart city technologies, demonstrating strong translational research capabilities. As an educator, Dr. Brune has developed innovative pedagogical approaches specifically tailored for non-computer science majors, with research examining student motivation in programming courses and effective methods for teaching cybersecurity concepts. His leadership in the Master of Artificial Intelligence and Data Analytics program shapes curriculum development for next-generation AI professionals. Dr. Brune directs multiple research initiatives including the Centre for Secure IT Applications and Infrastructures, which addresses critical cybersecurity challenges in modern IT environments, and the Institute of Agile Product and System Development, which explores innovative software development methodologies. His collaborative research approach is evident through extensive co-authorship networks spanning multiple institutions and disciplines.

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William Tarimoمشاهده پروفایل

استادیار

Connecticut CollegeUnited States

William Tarimo is the Jean C. Tempel '65 Assistant Professor of Computer Science at Connecticut College, where he has been teaching since 2017. His work focuses on educational technology and computer-supported pedagogy, with particular interest in agile teaching methodologies and affective computing. He develops technologies like the Discovery Teaching platform to enhance interactive learning in both physical and virtual classroom environments. Education: Ph.D., Brandeis University M.A., Brandeis University B.A., Connecticut College Tarimo's research centers on Technology-Supported Agile Pedagogy, exploring how continuous transparency, inspection, and adaptation can improve teaching and learning outcomes. His two main research thrusts include developing and evaluating technology-supported pedagogies using the Discovery Teaching platform, and investigating how data from wearable devices (such as EEG headbands and Oura rings) can provide insights into cognitive and affective states during learning. His work integrates artificial intelligence, machine learning, and educational theory to create responsive learning environments. His recent publications (2024-2025) demonstrate a growing emphasis on equity in education, student mental health, and the application of neuroscience to educational technology. Earlier works focused on practical classroom applications including peer grading systems, flipped classrooms, and remote student integration. Across all publications, Tarimo consistently bridges computer science and education, developing innovative solutions to persistent challenges in teaching and learning. Tarimo teaches core computer science courses including Introduction to Computer Science and Problem Solving (COM110), Data Structures (COM212), Mobile App Development (COM350), and Web Technologies & Development (COM214). As part of Connecticut College's requirement that computer science majors complete two semesters of research, he mentors undergraduate students in projects related to educational technology, wearable computing, and machine learning applications in education. His research involves collaboration with colleagues like Thomas Hickey and utilizes the Discovery Teaching platform (discoveryteaching.com), which provides tools for interactive teaching in remote, hybrid, or in-person settings.

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Keng-Chi Changمشاهده پروفایل

استادیار

Dartmouth CollegeUnited States

Keng-Chi Chang is an Assistant Professor in the Department of Quantitative Social Science at Dartmouth College. His research employs computational tools including AI and Large Language Models to investigate how technology and media shape political processes. Specific interests include censorship circumvention, online image-sharing behavior, and algorithmic recommendation systems for short-form video content. Education: • Ph.D. Political Science (Computational Social Science), University of California San Diego • M.S. Computer Science, University of California San Diego • B.A. Economics, National Taiwan University Research Focus: Chang explores the intersection of digital technology and political behavior, with emphasis on visual media analysis, censorship dynamics, and social media algorithms. His work examines how crises like COVID-19 trigger information-seeking behaviors and how platform features like live-stream chats influence political perceptions. Publications: Recent works demonstrate a strong focus on computational methods applied to political communication, including neural network interpretability, meme propagation patterns, and image-based credibility assessment. Publications span PNAS, Journal of Communication, and premier CS conferences. Funding & Awards: • NSF/APSA Dissertation Grant • Rapoport Family Foundation Research Grant

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