Prof. Laura Busse is a Professor at Ludwig Maximilian University of Munich (LMU), leading the Research Group in the Department of Biology II, Division Neurobiology. She holds roles as a Regular Member of MCN, Full Member of GSN, and Deputy Head of the GSN Examination Board. Her research focuses on cellular and systems neuroscience, particularly investigating how contextual information influences visual perception through neural circuits in mice. Key areas include feedback mechanisms, behavioral state effects, and thalamocortical interactions. Her work employs advanced techniques like high-density extracellular recordings and optogenetics to study active behavior in rodents. Current students include Simon Renner, Gregory Born, and others. Recent research highlights include studies on corticothalamic feedback effects, thalamic spatial integration, and the role of pupil dynamics in neural activity. She leads the Vision Circuits Lab (https://visioncircuitslab.org), exploring how sensory inputs and brain states shape visual processing. Her articles reveal trends in understanding thalamocortical communication, adaptive sensory systems, and the biological basis of neural network models. She coordinates the SPP2411 project on cortico-subcortical loops, emphasizing interdisciplinary neuroscience.
Lukas Engelmann is a Senior Lecturer at the University of Edinburgh , specifically within the Science, Technology and Innovation Studies department under the School of Social and Political Science . His research focuses on the history and sociology of biomedicine , with particular interest in epidemiological reasoning , visual cultures of disease , digital epidemiology , and decolonial approaches to medical history . The Epidemy Lab , which he founded, explores the historical development of epidemiology and its contemporary influence on data-driven public health and pandemic policy-making . Engelmann's work has been funded by prestigious grants including an ERC Starting Grant (2021-2025) for his research on the history of epidemiological reasoning, and support from the Wellcome Trust for projects examining the social dimensions of digital health . His book 'Mapping AIDS' (2018) established him as a leading scholar in medical visualization , while 'Sulphuric Utopias' (2020) with Christos Lynteris explores the technological history of maritime sanitation and its political implications. Recent publications emphasize the visual and data practices that have shaped epidemiology, including works on epidemic modeling during the COVID-19 pandemic , the history of plague mapping , and the ethical implications of digital phenotyping . He has also contributed to interdisciplinary discussions on syndemics , co-infection epistemology , and the commercialization of bacteriology in the early 20th century. His scientific contributions have earned recognition through editorial roles in journals like Big Data and Society , and collaborative projects such as 'Working with Diagrams' (2022) which investigates the epistemological role of visual tools in medical knowledge production. Scientific Awards and Funding: ERC Starting Grant (2021-2025) Wellcome Trust Institutional Support Fund British Academy/Leverhulme Small Research Grant Chancellor's Fellowship (University of Edinburgh) 'Sulphuric Utopias' listed in The Guardian's 30 Books to Understand the World (2020)
Keith Obadike is a Professor in the Department of Art at Cornell University's College of Architecture, Art, and Planning (AAP), where he also serves as Director of Undergraduate Studies. He is an acclaimed interdisciplinary artist and composer, known for his collaborative work with Mendi Obadike, which spans sound art, digital media, public installations, performance, and internet-based projects. His artistic and academic work critically engages with technology, race, history, and identity. Obadike earned a B.A. in Visual Art from North Carolina Central University and an M.F.A. in Sound Design from Yale University. Prior to joining Cornell, he taught at William Paterson University and held visiting positions at Princeton University, Columbia University, Northwestern University, and the Art Institute of Chicago. His research and creative practice focus on sound art, digital media, public art, performance, and collaborative practice , with strong interdisciplinary connections to Afrofuturism, data sonification, and social justice. He explores how sound and technology mediate racial identity, memory, and liberation, notably through the concept of acousmatic blackness , which he and Mendi developed to describe the racial perception of sound when its source is unseen. Obadike’s selected works include large-scale public sound installations such as Blues Speaker (for James Baldwin) , Free/Phase , Compass Song (Times Square Arts), and GuideStar (Space Needle, Seattle). His projects often use data sonification, archival research, and mythic storytelling, blending historical inquiry with futuristic vision. Notable series include the Opera-Masquerades , Americana Suites , and Numbers Station works, which transform databases of violence into sonic experiences. His honors include: Rockefeller New Media Arts Fellowship (2004) Louis Comfort Tiffany Biennial Award (2015) New York Foundation for the Arts Fellowship in Fiction New Music USA Creator Development Fund (2022) Obadike has received commissions and support from institutions such as the Vera List Center, Harlem Stage, Times Square Arts, the American Composers Orchestra, and the Cornell Mui Ho Center for Cities. He has exhibited and performed at The New Museum, The Whitney Museum of American Art, MoMA, and The Studio Museum in Harlem. His writings and publications include contributions to Studies into Darkness (2022), and artist books such as Four Electric Ghosts and Big House / Disclosure (both 2014). He has also released albums like Crosstalk (2008) and created internet artworks such as Blackness for Sale (2001) and The Interaction of Coloreds (2002), which are foundational in new media and critical race art. While specific advisees are not listed, his role as Director of Undergraduate Studies and Professor indicates active mentorship. His work is deeply collaborative, often co-created with Mendi Obadike, and supported by interdisciplinary teams and institutions.
Benjamin Bach serves as a Reader (equivalent to Associate Professor) in Data Visualization and Design within the School of Informatics at the University of Edinburgh, where he maintains active faculty status as of the page's publication date (October 24, 2024). He is formally affiliated with the Institute for Language, Cognition and Computation, contributing to the university's interdisciplinary research ecosystem in computational sciences. His research spans Data Visualization, Design, Computational Linguistics, Cognitive Science, and Human-Computer Interaction, with emphasis on developing visual representation frameworks that enhance human interpretation of complex data systems—particularly in language processing and cognitive modeling contexts. This work bridges theoretical design principles with practical applications in data-intensive domains. Dr. Bach's professional contact includes the email address bbach@exseed.ed.ac.uk and a personal website, though specific educational credentials remain undocumented in available sources. Regarding academic contributions, no details about graduate student supervision, research funding, or laboratory infrastructure are provided; however, his Institute for Language, Cognition and Computation affiliation indicates collaborative engagement with researchers exploring language, cognition, and computational methodologies.
Dr. Sam Ferguson is a Senior Lecturer at the School of Computer Science, University of Technology Sydney (UTS), with a multidisciplinary background in music performance, cognitive science, and psycho-acoustics. His research explores the intersection of sound, music, and human experience through creative coding, machine learning, and interactive systems. Key Research Areas: Sound and Music Computing, Human-Computer Interaction, Creative Coding, Cognitive Science, Installation Art, and Acoustics. Current Projects: ARC Linkage project on creative coding and multiplicitous media; industry collaborations on IoT-based audiovisual systems. Recent Publications: Focus on spatial audio complexity, gestural interaction with networked sound, music emotion recognition frameworks, and robotic performance through genre-based cultural platforms. Leadership Roles: Director of Teaching & Learning Engagement; former Deputy Head of School (Teaching and Learning); active in ACM Creativity and Cognition Steering Committee. Teaching: Courses like Digital Media Studio , Prototyping Physical Interaction , and Data Processing using R within UTS's interdisciplinary Software Development Studio.
Sri Kurniawan is a researcher at the Computational Media Department within Baskin Engineering, University of California Santa Cruz . With a focus on Human-Computer Interaction , their work spans assistive technology , virtual reality applications , and accessibility design for aging populations and people with disabilities. Key research areas: Accessibility , Virtual Reality , Human-Computer Interaction Recent work explores immersive systems for emergency preparedness and Mixed Reality in biomedical visualization Publications from 2000-2025 demonstrate sustained engagement in mobile health and inclusive game design . Collaborations with institutions like University of Manchester and University of California systems highlight cross-continental research impact.
Maurizio MUZZUPAPPA is a Full Professor at the Department of Mechanical, Energy and Management Engineering (University of Calabria) since 2018. His roles include Rector's Delegate for Technology Transfer, Academic Delegate for Education at DIMEG, and Head of the Physical Prototyping Laboratory at the MaTeRiA Center (UNICAL-CNISM collaboration). He supervises the Unical Racing Team in Formula SAE competitions and co-founded three university spin-offs: 3DResearch, Tech4Sea, and Q-BOT. As Scientific Director of projects like TECH4YOU (climate change adaptation technologies) and GROWN IN THE BLUE (Mediterranean reef conservation), he integrates research in industrial design, augmented reality, and underwater cultural heritage. He has authored over 200 publications (h-index 27) and holds 10 patents. His teaching includes Tools and Methods for Industrial Design and Formula SAE LAB . His research focuses on: Industrial design methodologies with parametric and sustainable approaches 3D prototyping and additive manufacturing User-Centered Design for product ergonomics Virtual/Augmented Reality applications in engineering and cultural heritage Underwater robotics and artifact restoration Recent publications highlight trends in AR for industrial maintenance, generative design tools, and mechatronic solutions for underwater heritage. He has supervised over 300 theses and 10 Ph.D. students while leading technology transfer initiatives.
Daniel Pettersson is a Professor at University of Gävle specializing in educational science with a particular focus on international knowledge measurements, comparative education, and curriculum studies. His work critically examines the hegemony of comparisons in education, particularly through large-scale assessments like PISA, and explores how these influence educational policy and practice. Professor Pettersson's research spans several interconnected domains within educational science. He investigates how international comparisons shape educational discourse and policy, examining the historical development of assessment practices and their impact on national education systems. His work frequently analyzes the production of educational knowledge through data visualization and quantification, revealing how numbers become authoritative in educational decision-making. A significant portion of his research focuses on Swedish education within international contexts, exploring how global educational trends are adopted, adapted, and contested in national settings. His extensive publication record reveals several key trends in his scholarly work. Over the past two decades, Pettersson has traced the evolution of international large-scale assessments from marginal research tools to central policy instruments. His recent work increasingly examines data visualization techniques in educational research and the historical construction of educational knowledge through quantification. He also explores the intersection of teacher education with international assessment frameworks, revealing tensions between global educational discourses and local teaching practices. Professor Pettersson has made significant contributions to understanding how educational policy is shaped by international comparisons. His research demonstrates how assessment data becomes transformed into policy narratives that influence educational reform. He has documented the historical trajectory of international assessment research, showing how it evolved from marginal academic interest to central policy instrument. His collaborative work with scholars like Sverker Lindblad, Thomas Popkewitz, and Tatiana Mikhaylova has been particularly influential in critically examining the political dimensions of educational measurement. His research activities include extensive work with international research teams, participation in major conferences including the Nordic Education Research Association (NERA) and the International Standing Conference for the History of Education (ISCHE), and contributions to systematic reviews of international comparative research. Professor Pettersson's work bridges historical analysis, policy studies, and critical examination of educational measurement practices, providing valuable insights into how global educational knowledge is produced and circulated.
Professor David E. Gloriam is a leading expert in G protein-coupled receptors (GPCRs) at the University of Copenhagen , Department of Drug Design and Pharmacology. Recognized as a top 1% Clarivate Highly Cited Researcher, he leads GPCRdb, a major database with >50,000 annual users, and develops computational tools like GPCRgraphs for drug discovery. His innovation roles include Senior Scientific Expert at Kvantify A/S and applications in pharmaceutical industry tools with patent citations. Education: Ph.D. in Medicine (Uppsala University, 2006), M.Sc. in Pharmaceutical Sciences (Uppsala University, 2003) Leadership: Head of GPCRdb (2014–), EU COST Actions member (2014–17), and institutional leadership roles in Pharmaceutical Data Science unit and Research Leadership Forum Research Interests: His work spans computational modeling of GPCR dynamics, virtual screening methods for inaccessible receptors, pharmacogenomics (PGxDB platform), and biased signaling for safer drugs. He integrates structural biology, data science, and bioinformatics to advance pharmaceutical discovery. Awards: Clarivate Highly Cited Researcher (2022) IUPHAR Analytical Pharmacology Award (2023) Lars Arge Prize for Big Data (2021) UCPH Forward Talent Program (2019) ERC Starting Grant (2014) Teaching & Supervision: Teaches Molecular Pharmacology and AI in Drug Discovery , and supervises 3 current PhD students. He has mentored 13 PhDs and 14 Postdocs, with former members attaining tenured academic or industry roles.
Nakul Gopalan serves as an Assistant Professor at Arizona State University's School of Computing and Augmented Intelligence (SCAI) in Tempe, where he founded and leads the Logos Robotics Lab since joining in August 2022. His academic foundation was established through a PhD in Computer Science from Brown University completed in 2019. Education: PhD in Computer Science, Brown University (2019) Research Focus: Dr. Gopalan pioneers work at the critical intersection of language grounding and robot learning, developing algorithms that enable robots to interpret natural language instructions and learn from human demonstrations. His research directly addresses real-world usability challenges by focusing on hierarchical reinforcement learning, task planning, and human-robot collaboration frameworks that empower non-expert users to train robots for home and office environments. Key innovations include plannable representations for natural language instruction following and transfer learning techniques for robotic task execution. Publication Evolution: Recent publications (2023-2025) demonstrate accelerating specialization in language-conditioned robot learning, with 80% of his latest work exploring compositional instruction following, novice-user teaching interfaces, and explainable AI for robotics. His research trajectory shows a deliberate shift from foundational language grounding (2017-2020) toward practical human-robot collaboration systems, evidenced by increased focus on hardware-software co-design, cross-embodiment transfer, and clinical applications of explainable AI in neurology support systems. Scientific Recognition: Best Paper Award at RoboNLP workshop (Association for Computational Linguistics) 2017 RSS 2023 Best Student Paper Finalist Mentorship & Service: As lab director, Dr. Gopalan actively mentors graduate researchers while teaching core courses including Data Structures and Algorithms (CSE 310) and specialized seminars on robot learning. His significant service contributions include organizing the RSS 2021 "Robotics for People" workshop, serving as Action Editor for ICRA 2023/2024, and extensive reviewing for top-tier robotics conferences (RSS, ICRA, CORL) and AI venues (NeurIPS, AAAI). Research Infrastructure: The Logos Robotics Lab operates as his primary research vehicle, focusing on natural language interfaces for robot training, hierarchical task decomposition, and real-world deployment of language-grounded learning systems. Current projects integrate large language models with robotic control frameworks to enable zero-shot task generalization across different robot embodiments.
Professor Stephan A. Sieber is a leading researcher in bioorganic chemistry at the Technical University of Munich (TUM), where he holds the Chair of Organic Chemistry II within the TUM School of Natural Sciences. His research program focuses on developing new drugs against multidrug-resistant bacteria through a multi-disciplinary approach that integrates synthetic chemistry, functional proteomics, microbiology, and protein biochemistry. His laboratory has made significant contributions to identifying unprecedented antibacterial targets beyond the scope of current antibiotics and exploiting these for chemical manipulation. Recent work has increasingly incorporated machine learning approaches to accelerate antibiotic discovery, with notable publications on AI-guided pipelines, drug-target interaction prediction, and high-throughput screening optimization. Sieber's research has resulted in the discovery of new active substances, some of which are currently being optimized for medical applications. His group's publications reveal a strong focus on chemical proteome mining, natural product mode of action studies, and novel antibacterial target identification. The lab has published extensively in top journals including Nature Chemistry, Nature Communications, and ACS Central Science. Inhoffen Medal (2024) Max Bergmann Medal (2023) ERC Advanced Grant (2023) Merck Future Insight Prize (2020) Klaus Grohe Prize (2020) ERC Consolidator Grant (2016) Professor Sieber leads an active research group that maintains a strong presence in the scientific community through regular publications, conference presentations, and collaborations. His laboratory website and BlueSky presence (@sieberlab.bsky.social) demonstrate ongoing research activities and engagement with the broader scientific community. He has successfully secured significant research funding including multiple ERC grants that have supported his innovative work in antibiotic discovery.
Johannes Schöning is a Professor of Human-Computer Interaction (HCI) at the University of St. Gallen and leads the Ubiquitous Media Technology Lab . His research focuses on developing user interfaces that empower individuals and communities through data-driven decision-making, with interdisciplinary applications in geographic information science, public health, medical contexts, and extreme environments like space missions. He emphasizes methodological rigor from AI, computer graphics, and cognitive psychology. Organizes AlpCHI 2026 Chair of ACM Eugene Lawler Award Committee Editorial Board, AI Perspectives (Springer Nature) Research Trends : His publications from 2025–2024 reveal a focus on Mixed Reality (autoethnography, weight perception), Accessibility (visual impairment support), Environmental HCI (CO2 eco-feedback), and Geospatial Technologies (navigation externalities, map analytics). Interdisciplinary work appears in journals like Nature and PLOS ONE . Scientific Recognition : ACM Distinguished Member Best Paper & Accessibility Awards (Interact 2019, MobileHCI 2015) Junior Fellow, Gesellschaft für Informatik (2013) Academic Service : Active in conference leadership (SIGCHI Switzerland Chair 2021–2023, ISS 2016 Program Chair) and reviewing for top venues including ACM CHI , Ubicomp , and IEEE VR . Regular reviewer for European science foundations and DFG/BMBF proposals.
Dr. George C Tseng serves as Professor and Vice Chair for Research in the Department of Biostatistics at the University of Pittsburgh School of Public Health, with secondary appointments in Human Genetics and Computational and Systems Biology. His educational background includes a BS (1997) and MS (1999) in Mathematics from National Taiwan University and an ScD (2003) in Biostatistics from Harvard School of Public Health. Dr. Tseng's research focuses on developing statistical methodologies for genomic and bioinformatic applications to advance precision medicine. His work spans multiple high-impact areas including multi-omics data integration, machine learning for high-dimensional data, cluster analysis for disease subtyping, and statistical methods for experimental design in omics studies. His approach emphasizes close collaboration with biological and clinical researchers to ensure methodological relevance to real-world problems. His publication record demonstrates consistent contributions to top statistical and bioinformatics journals, with recent work focusing on congruence analysis between animal models and humans, outcome-guided clustering methods, and high-dimensional causal mediation analysis. Elected Fellow, American Statistical Association (2017) Statistician of the Year, ASA Pittsburgh Chapter (2017) Provost's Award for Excellence in PhD Mentoring, University of Pittsburgh (2019) Clinical Research Scholar (K12) Award, NIH (2007-2009) Elected Member, International Statistical Institute (2012) Dr. Tseng has successfully mentored over 25 PhD students who have secured positions in academia, industry, and government agencies. His laboratory has maintained continuous NIH funding as principal investigator since 2012, including current grants R01CA285337 (2025-2030) and R01LM014142 (2023-2026). The Tseng Lab operates as a collaborative research environment focused on translating statistical innovations into practical solutions for biological and medical challenges, with strong connections to multiple research centers and clinical departments at the University of Pittsburgh.
Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.
Maarten Sap is an Assistant Professor at Carnegie Mellon University's Language Technologies Institute with a courtesy appointment in the Human-Computer Interaction Institute. He also holds a part-time research scientist position at the Allen Institute for AI (AI2) as an AI safety lead. Current affiliations: CMU (2022–present), AI2 (2022–present) Prior: Postdoctoral Researcher at AI2 (2021–2022), Research Intern at AI2 (2018–2019) and Microsoft (2019) His research focuses on enhancing AI systems with social intelligence and addressing social biases in language technology. Key themes include: Ethical AI and Human-Centric Design Narrative Dynamics and Social Context Analysis AI Agents and Social Intelligence Toxic Language Detection and Cultural Bias Mitigation Recent publications examine: AI safety frameworks like HAICOSYSTEM Clinical reasoning alignment (ALFA) Multilingual moderation (PolyGuard) Cultural sensitivity in non-verbal AI (Mind the Gesture) Personality shaping in LLMs (BIG5-CHAT) Scientific Recognition: 2025 Okawa Research Grant Best Paper Runner Up - NAACL 2025 Outstanding Paper - EMNLP 2023 Best Paper - FAccT 2023 Best Paper - WeCNLP 2020 He advises a diverse group of PhD students across CMU and MIT, and has served on multiple program committees including ACL, EMNLP, and FAccT. His work appears in top venues like Nature Machine Intelligence, PNAS, and ACL.
