جست‌وجوی استاد و پژوهشگر

David Bammanمشاهده پروفایل

دانشیار

• Natural Language Processing
• Cultural Analytics
• Computational Social Science
• +۳ مورد دیگر

David Bamman is an Associate Professor in the School of Information at UC Berkeley, specializing in applying Natural Language Processing (NLP) and machine learning to cultural and social science questions. He leads research in born-literary NLP, computational humanities, and cultural analytics, with affiliated roles in EECS, Linguistics, and Computational Precision Health. Bamman holds degrees from Carnegie Mellon (Ph.D., 2015), Boston University (M.A., 2006), and University of Wisconsin-Madison (B.A., 1998). His work is supported by NEH, NSF, and industry grants. Educations: Ph.D. in Computer Science (2015), Carnegie Mellon University M.A. in Applied Linguistics (2006), Boston University B.A. in Classics (1998), University of Wisconsin-Madison Research Interests: NLP for underserved domains (e.g., literature, social media), coreference resolution, cultural analytics, and computational methods for studying literature and culture. Projects include LitBank and BookNLP datasets. Grants & Awards: Hellman Fellow (2019), Amazon Research Award (2017), NSF CAREER Award, and NEH funding. Teaching: Courses include Natural Language Processing (Info 159/259), Computational Humanities (INFO 190), and Applied NLP (INFO 256). His research group explores topics like racial representation in high school literature, Hollywood diversity metrics, and the sociocultural implications of LLMs. Bamman advises multiple PhD students and collaborates on datasets like CMU Book Summaries and 11K Latin Books.

• Machine Learning
• Natural Language Processing
• Music Information Retrieval
• +۱۲ مورد دیگر

Colin Raffel , currently an Associate Professor at the University of Toronto and Associate Research Director at the Vector Institute , is a leading researcher in machine learning and natural language processing . His career spans roles at Hugging Face (Faculty Researcher), Google Brain (Senior Research Scientist), and UNC Chapel Hill (Assistant Professor). Education: PhD in Electrical Engineering (Columbia), MA in Music/Science (Stanford), BA in Mathematics (Oberlin) Key affiliations: Google Brain (2016-2020), Hugging Face (2021-present), Vector Institute (2023-present) His research focuses on language model development , attention mechanisms , efficient machine learning , and music information retrieval . Recent work explores model merging , parameter-efficient fine-tuning , and data-constrained language models . Teaching : Has instructed courses at University of Toronto and UNC Chapel Hill on Neural Networks , Deep Learning , and Information Theory . Academic service includes organizing ICLR workshops and serving as Senior Area Chair for NeurIPS and EMNLP . Notable awards : NSF CAREER (2022), Caspar Bowden Award (2023), NeurIPS Outstanding Paper (2023) Key contributions : Core developer of WT5 , Git-Theta , and mir_eval software

Jackie Chit Kit Cheungمشاهده پروفایل

دانشیار

• Natural Language Processing
• Natural Language Generation
• Automatic Summarization
• +۱۲ مورد دیگر

Jackie Chit Kit Cheung is an Associate Professor in the School of Computer Science at McGill University, where he co-directs the Reasoning and Learning Lab. He holds the Canada CIFAR AI Chair and serves as an Associate Scientific Co-Director at the Mila Quebec AI Institute. He is also a consulting researcher at Microsoft Research Montreal. Academic Background: Ph.D. in Computer Science, University of Toronto (2010–2014) M.Sc. in Computer Science, University of Toronto (2008–2010) B.Sc. (Honours) in Computer Science, minors in Linguistics and German, University of British Columbia (2004–2008) Research Interests: Jackie Cheung's research lies at the intersection of natural language processing, machine learning, and cognitive science. He focuses on natural language generation , automatic summarization , commonsense and pragmatic reasoning , and the evaluation of NLP systems . His work aims to build language models that reflect real-world structure and reasoning, with applications in health, education, and language revitalization. He is particularly interested in how implicit meaning is processed in context, a core concern in linguistic pragmatics. Publication Trends: His recent publications (2024–2025) show a strong emphasis on evaluation methodologies (e.g., COSMIC, ECBD), hallucination and factuality in language models, coreference and reasoning , and long-context modeling . He frequently collaborates across institutions and integrates insights from linguistics and psychology into NLP system design and analysis. Scientific Awards: Best Paper Award, ACL 2018 Outstanding Paper Award, NAACL 2018 Student Research Workshop SAC Award, ACL 2024 (for COSMIC) Best Poster Award, CMDO AI-Health Symposium 2024 Advising and Grants: He advises a large and diverse group of graduate students, including PhD and Master’s candidates, often in co-supervision with other faculty. His group has received support from major AI and health research initiatives, including CIFAR and Mila. He has trained alumni who have gone on to faculty and industry research positions. He has served in leadership roles in top NLP conferences, including as Senior Area Chair, Workshop Chair, and Program Chair of Canadian AI 2018. Labs and Teams: He co-directs the Reasoning and Learning Lab at McGill and is deeply involved with Mila – Quebec AI Institute . He founded the NLP Reading Group at McGill, which brings together researchers from computer science, linguistics, and information studies to discuss theoretical and applied NLP topics.

K. Michael Haysمشاهده پروفایل

استاد

• Architectural Theory
• European Modernism
• Critical Theory
• +۳ مورد دیگر

K. Michael Hays is the Eliot Noyes Professor of Architectural Theory at Harvard University's Graduate School of Design (GSD) and Co-Director of the Master in Design Studies program. He has been a faculty member since 1988, specializing in architectural history and theory. His research focuses on European modernism, critical theory, and contemporary architectural practice, with notable contributions to the field through writings on figures like Mies van der Rohe and Peter Eisenman. Education: He holds a Bachelor of Architecture (1976) from Georgia Institute of Technology, a Master of Architecture in Advanced Studies (1979) from MIT, and a PhD in History, Theory, and Criticism of Architecture and Art (1990) from MIT. Research Interests: Hays is renowned for founding the journal Assemblage , a pivotal forum for architectural theory. His work bridges historical analysis and contemporary practice, emphasizing theoretical frameworks for understanding modernism and its evolution. He has curated exhibitions at institutions like the Whitney Museum of American Art (as its first Adjunct Curator from 2000–2009). Publications: His authored and edited works include Architecture's Desire , Inscriptions: Architecture Before Speech , and critical studies on architects such as Buckminster Fuller and Diller + Scofidio. These publications explore themes of representation, modernist aesthetics, and interdisciplinary design. Awards and Roles: While no specific awards are listed, his academic leadership roles include Chair of the GSD PhD Committee (1995–2005) and Director of Advanced Independent Study Programs. He has also served on editorial boards for journals like Assemblage and Thresholds . Labs and Collaborations: Hays collaborates with academic and institutional partners, notably through curatorial projects and his role in shaping the GSD's theoretical curriculum. His influence extends to both pedagogical innovation and scholarly discourse in architectural education.

John McAuliffeمشاهده پروفایل

استاد

• Poetry
• Creative Writing
• Literary Translation
• +۳ مورد دیگر

John McAuliffe is Professor of Poetry at The University of Manchester, where he joined in 2004 and currently directs the Creative Manchester research platform focused on Creative Industries, Creativity/Health/Well-being, and Creative Civic Futures. He founded and directed the internationally renowned Centre for New Writing (2007-2021). Additional roles include Associate Publisher at Carcanet Press, co-editor of PN Review, and trustee of Manchester's UNESCO City of Literature. His creative scholarship centers on contemporary poetry with emphases on Irish literary traditions, cross-cultural translation, and poetry's civic applications. Work spans lyric composition, editorial curation of emerging voices, and critical analysis of poetry's intersections with theatre, conflict studies, and social identity. His practice bridges academic scholarship and public literary engagement through institutional leadership. Recent publications reveal evolving thematic trajectories: 2024's National Theatre examines theatricality in modern verse, while Selected Poems (2021/2022) consolidates decades of work exploring Irish landscapes and personal memory. The Kabul Olympics (2020) and Stockholm Syndrome (2019) demonstrate sustained engagement with geopolitical conflict and psychological dimensions of displacement through poetic form. Major recognitions include: Observer Book of the Year (2021/2022) for Selected Poems Guardian Poetry Book of the Month (June 2020) for The Kabul Olympics TLS and Irish Times Book of the Year (2020) for The Kabul Olympics Poetry Book Society Winter Pamphlet Choice (2019) for Stockholm Syndrome McAuliffe served as Deputy Director of the Irish Arts Council (2013-2018), chairs strategic initiatives, contributes to AHRC peer review, and writes extensively for The Irish Times (2013-2020 column). He actively shapes literary policy through Manchester City Council's Events Commission and UNESCO City of Literature governance.

Christopher Pottsمشاهده پروفایل

استاد

• Computational Linguistics
• Natural Language Processing
• Semantics
• +۵ مورد دیگر

Christopher Potts is Professor and Chair of Linguistics at Stanford University, with a courtesy appointment as Professor of Computer Science. He serves as Director Emeritus of the Stanford Center for the Study of Language and Information (CSLI) and leads the Pragmatic Enrichment & Contextual Interface Lab. His work bridges theoretical linguistics and computational approaches to language understanding. Education: B.A. in Linguistics from New York University (1999) Ph.D. in Linguistics from University of California, Santa Cruz (2003) Potts' research focuses on how computational methods can illuminate linguistic phenomena, particularly in the areas of semantics, pragmatics, and sentiment analysis. His work explores how emotion is expressed in language and how linguistic production and interpretation are influenced by context. He has made significant contributions to understanding conventional implicatures, sentiment analysis frameworks, and the application of neural networks to linguistic problems. His recent work has increasingly focused on the interpretability of large language models and the development of frameworks like DSPy for building reliable AI systems. An analysis of Potts' recent publications reveals a strong trend toward the intersection of linguistic theory and practical AI applications. His work spans theoretical linguistics (e.g., compositionality, preposing constructions), neural network interpretability, and practical NLP systems (e.g., ColBERT, DSPy). The research demonstrates consistent focus on making language models more transparent, controllable, and linguistically informed, with particular attention to how context shapes meaning. Scientific Awards: Best Paper Award at 2024 ACL for 'Mission: Impossible Language Models' Outstanding Paper Award at 2024 ACL for 'CausalGym' ACL Test of Time Award 2023 Dean's Award for Distinguished Teaching (2015-2016) Best New Data Set or Resource Award at 2015 EMNLP Potts has secured numerous research grants as PI or Co-PI from major organizations including Google, Amazon, NSF, Office of Naval Research, and Stanford's HAI institute. His current projects focus on evaluation of retrieval-augmented generation systems, LLM-mediated communication in organizations, interpretability techniques for language models, and frameworks like DSPy for building next-generation AI systems. He has mentored numerous researchers who have gone on to make significant contributions in NLP and computational linguistics. As Director of CSLI (2013-2020) and current Chair of Linguistics at Stanford, Potts has played a key leadership role in shaping interdisciplinary research at the intersection of language, computation, and cognition. His Pragmatic Enrichment & Contextual Interface Lab continues to be a hub for innovative research combining formal linguistic theory with cutting-edge computational methods.

• Art History
• Modern and Contemporary Art
• Audience Relations
• +۵ مورد دیگر

Dr. Patrick van Rossem is an Associate Professor of Modern and Contemporary Art at the Department of History and Art History within the Faculty of Humanities at Utrecht University (The Netherlands). He has been serving as Head of the Art History department since May 2022 and has coordinated various Master and Bachelor programs in Art History since 2008. His educational background includes Art History (Humanities) and Media and Communication (Social Sciences) from Ghent University, and a Curating program at Goldsmith College, University of London. He earned his Ph.D. in Art History in 2006 from Ghent University with a dissertation on artist-audience relations in the second half of the 20th century. Dr. van Rossem's research focuses on post-1960s art, with particular emphasis on artists' audience relations, the representation of audiences, and the performative turn. His teaching covers similar areas including post-1960s art, audiences for art, curating, and art mediation and education. His scholarly work demonstrates a consistent exploration of how artists engage with their audiences, the changing nature of art viewership, and the performative aspects of contemporary art practices. His recent publications span topics from art vandalism in digital contexts to historical analyses of museum visitors in the 19th century, showing the breadth of his research interests that bridge contemporary art theory with historical perspectives on art reception. Dr. van Rossem has been actively involved in academic service, including editorial work for Stedelijk Studies journal and organizing conferences such as 'Keeping silent, listening, speaking up: voice and silence in audience-response to arts and literature.' He has delivered numerous invited talks at institutions including the Stedelijk Museum Amsterdam and has participated in international conferences on contemporary art, audience studies, and art history methodologies.

Subodha Kumarمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Blockchain
• +۷ مورد دیگر

Subodha Kumar is the Paul R. Anderson Distinguished Chair Professor of Statistics, Operations, and Data Science at Temple University’s Fox School of Business. He serves as the Founding Director of the Center for Business Analytics and Disruptive Technologies and has a secondary appointment in Information Systems. His roles include Ph.D. Program Concentration Director for Operations and Supply Chain Management. With over 240 publications, he ranks #1 globally in Information Systems Research publishing and holds a robotics patent. His research focuses on AI, blockchain, healthcare analytics, and cybersecurity, with notable contributions to digital transformation and operations management. Awards include the INFORMS ISS Distinguished Fellow and POMS Fellow. He advises major journals like Production and Operations Management and organizes conferences like POMS 2018. Media mentions span NYT, WSJ, and CBS. Education: University of Washington faculty Texas A&M University faculty Research Interests: Dr. Kumar explores AI applications, blockchain in fintech, healthcare system optimization, and supply chain analytics. He investigates cybersecurity’s operational impacts and data mining strategies. His work bridges theory and practice, addressing challenges in digital transformation and platform economies. Publications Trends: Recent work emphasizes digital platforms (e.g., blockchain adoption, telemedicine impact), organizational behavior (real-time feedback systems), and healthcare operations (personalized treatment algorithms). He frequently collaborates internationally, with studies appearing in Management Science, Information Systems Research, and Decision Sciences. Awards & Recognition: Changjiang Scholars Chair (China) ISB Visiting Professorship POMS Executive Editor Grants & Labs: Secured NIH grants for health analytics projects. Leads Temple’s analytics center fostering industry partnerships. Active in editorial roles (e.g., Production and Operations Management Journal Deputy Editor). Teaching: Offers courses in data science, optimization methods, and innovation entrepreneurship at graduate/undergraduate levels.

Steve Mussmannمشاهده پروفایل

استادیار

• Data-centric machine learning
• Active learning
• Experimental design
• +۲ مورد دیگر

Steve Mussmann serves as an Assistant Professor in the School of Computer Science at the Georgia Institute of Technology, where he joined in Fall 2024. His research centers on data-centric machine learning, with emphasis on active labeling, data selection, and adaptive experimental design methodologies. He maintains active collaborations through Georgia Tech's Foundations of AI (FoAI) and ML@GT research groups. Mussmann earned his PhD in Computer Science from Stanford University in 2021 under Percy Liang's supervision, following a BS in Math, Statistics, and Computer Science from Purdue University in 2015. His professional trajectory includes a machine learning researcher role at Coactive AI and an IFDS postdoctoral fellowship at the University of Washington's Paul Allen School of Computer Science and Engineering. His research program investigates theoretical and practical aspects of data efficiency in machine learning systems, particularly focusing on active learning frameworks, statistical properties of data algorithms under concept drift, and task specification via prompts or demonstrations. Current projects address challenges in label-efficient training of large language models and multimodal dataset development. Analysis of his 15 most recent publications reveals a consistent focus on advancing data-centric methodologies, with increasing emphasis on large-scale applications like multimodal datasets and language model fine-tuning. His work bridges theoretical guarantees in experimental design with practical frameworks like LabelBench for benchmarking label efficiency. Mussmann has received recognition through the IFDS postdoctoral fellowship. His contributions to the field include foundational work on active learning theory and data selection algorithms. IFDS postdoctoral fellow He currently advises five graduate students including PhD candidates Kangping Hu (CS) and Hangyu Zhou (ML), alongside MS students Kabir Kang and Kalp Vyas, and undergraduate Saloni Bedi. Former advisee Wei-Liang (Edison) Liao completed BS research under his supervision. His teaching portfolio includes graduate courses CS 7545 (Machine Learning Theory) and CS 8803-DML (Data-centric Machine Learning). Mussmann operates within Georgia Tech's Foundations of AI initiative and ML@GT collective, which provide infrastructure for large-scale data-centric research. His lab develops open-source tools like LabelBench for reproducible evaluation of data selection techniques, with ongoing projects exploring video data exploration systems and adaptive finetuning frameworks for foundation models.

Ann D. Braudeمشاهده پروفایل

مدرس ارشد

• American Religious History
• Women's Studies in Religion
• Spiritualism and Women's Rights
• +۳ مورد دیگر

Ann D. Braude is a Senior Lecturer on American Religious History and Director of the Women's Studies in Religion Program at Harvard Divinity School (HDS), affiliated with Harvard University. She joined HDS in 1998 after roles at Carleton College and Macalester College. Her work emphasizes inclusive religious narratives, particularly exploring intersections of gender, spirituality, and social movements. Key research areas include 19th-century Spiritualism, Indigenous religious perspectives, and modern abstract art's relationship to spirituality. Braude holds an AB from Vassar College, MA from the University of Chicago, and PhD from Yale University. Her research has produced influential works like Radical Spirits (2008) and Sisters and Saints (2007), which examine women's roles in shaping religious history. She organized pivotal conferences such as the 2005 celebration of women at HDS and curated the bicentennial exhibition Faces of Divinity (2016). Her current projects include studying gender dynamics in abstract painting and Native American religious frameworks through a biennial speakers series. Braude’s courses focus on American religious history, feminist theology, and Indigenous religious studies. Her articles and public engagement reflect a commitment to bridging academic research with broader societal conversations about religion, gender, and culture. She maintains active roles in both Harvard Divinity School and the broader academic community, contributing to interdisciplinary dialogues on pluralism and religious diversity.

Clare Harrisمشاهده پروفایل

استاد

• Visual Anthropology
• Material Culture
• Tibetan Studies
• +۴ مورد دیگر

Clare Harris serves as Professor of Visual Anthropology and Head of the School of Anthropology and Museum Ethnography at the University of Oxford, concurrently holding curatorship of Asian Collections at the Pitt Rivers Museum and a Fellowship at Magdalen College. Her academic leadership spans institutional administration, museum curation, and doctoral supervision within Oxford's anthropological ecosystem. Her educational foundation includes a BA from the University of Cambridge and MA/doctorate from SOAS, University of London. Early career roles comprised Lecturer in Anthropology of Art at the University of East Anglia (1994-1998) before her Oxford appointment. Harris pioneers research at the intersection of visual anthropology, Tibetan studies, and museum decolonization. Her work critically examines Himalayan visual culture, colonial/post-colonial photography, and museum representation politics, evolving toward digital repatriation and community-centered curation. She integrates anthropological fieldwork (conducted in Tibetan diaspora communities since the 1990s) with art historical analysis and archival research. Her 13 recent publications (2004-2022) reveal a progressive trajectory from Tibetan art history toward urgent museum decolonization debates, with consistent focus on photographic practices and cross-cultural representation. Key thematic developments include the shift from historical analysis to active digital repatriation projects and increased engagement with contemporary artists. Harris's accolades include: Fellowship of the British Academy (2019) E. Gene Smith Prize for The Museum on the Roof of the World (2014) Visual Anthropology Prize for In the Image of Tibet (2000) She currently supervises five DPhil students while examining over 25 completed doctorates globally. Research funding spans British Academy personal grants, Leverhulme Trust support, and major collaborative projects including AHRC, Wenner-Gren Foundation, and EU grants—most notably the current AHRC-funded Decolonising the Museum: Digital Repatriation of the Gaidinliu Collection . At the Pitt Rivers Museum, Harris leads high-impact curatorial initiatives including the Abramović collaboration ( Gates and Portals ), Nyema Droma's Performing Tibetan Identities , and community projects like My Tibet Museum , establishing innovative frameworks for museum-public engagement.

Eero Hyvönenمشاهده پروفایل

استاد

• Semantic Web
• Linked Data
• Artificial Intelligence
• +۲ مورد دیگر

Eero Hyvönen is a Professor of Computer Science at Aalto University and Director of the Helsinki Centre for Digital Humanities (HELDIG) at the University of Helsinki. He leads the Semantic Computing Research Group (SeCo), specializing in Semantic Web technologies and applications. Hyvönen holds an Adjunct Professor title at the University of Helsinki's Department of Computer Science. His work focuses on developing national-level semantic web infrastructure, with applications in digital humanities, cultural heritage, and AI. He has published over 500 research articles and books, receiving numerous awards including the Decoration of Knight, First Class, of the Order of the White Rose of Finland (2018). Hyvönen chairs editorial boards of journals like Semantic Web and serves on committees for major conferences. His research spans semantic web technologies, linked open data, and AI applications in cultural heritage domains. Key projects include Sampo portals (e.g., LetterSampo, OperaSampo) for cultural data analysis, ParliamentSampo for parliamentary data, and FindSampo for archaeological finds. His work emphasizes interdisciplinary collaboration, integrating law, history, and computing through initiatives like FIN-CLARIAH. Hyvönen advises doctoral and master's students, notably Annastiina Ahola and Jouni Tuominen, who have won awards under his supervision. He directs research infrastructures, chairs international boards, and actively contributes to open data policies and standards development.

Kevin Lane Kellerمشاهده پروفایل

استاد

• Marketing Management
• Branding
• Brand Equity
• +۷ مورد دیگر

Kevin Lane Keller is the E.B. Osborn Professor of Marketing and Senior Associate Dean for Marketing and Communications at the Tuck School of Business, Dartmouth College. He holds a PhD in Marketing from Duke University (1986), an MSIA from Carnegie Mellon University (1980), and an AB in Math and Economics from Cornell University (1978). Prior academic appointments: Stanford University (marketing group head), UC Berkeley, UNC Chapel Hill, Duke University, and Australian Graduate School of Management. Industry experience: Marketing Consultant for Bank of America. Research Focus: Keller specializes in leveraging consumer psychology to enhance branding and marketing strategies. His work spans brand equity, brand architecture, integrated marketing communications, global branding, and digital brand management , with over 120 publications in top journals like the Journal of Marketing, Journal of Consumer Research, and Marketing Science. Recent research explores brand performance in hyper-competitive digital environments and the future of branding. Scientific Awards: 2019 Blair Award for Marketing Accountability (with Roger Sinclair) Ranked #105 Worldwide and #60 in the U.S. by Research.com (2023) Consulting & Public Engagement: Keller has advised Fortune 500 companies including Accenture, Disney, Ford, and Samsung. He co-authored the Marketing Management textbook (16th ed.) with Philip Kotler and Strategic Brand Management (5th ed.) with Vanitha Swaminathan, both foundational texts in their fields. His keynote speeches and workshops have influenced senior management at firms like Google, Microsoft, and Coca-Cola.

Ranjay Krishnaمشاهده پروفایل

استادیار

• Computer Vision
• Natural Language Processing
• Robotics
• +۳ مورد دیگر

Ranjay Krishna is an Assistant Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where he co-directs the RAIVN lab and leads the computer vision team at the Allen Institute for AI (Ai2). His research intersects computer vision , natural language processing , robotics , and human-computer interaction . PhD in Computer Science from Stanford University (2021) Bachelor's and Master's degrees from Stanford and Cornell His work has received best paper , outstanding paper , and orals at top conferences like CVPR, ACL, CSCW, NeurIPS, UIST, and ECCV. Media outlets including Science , Forbes , and PBS NOVA have covered his research. He has been supported by grants from Google , Apple , NFS , and others. Ranjay advises a diverse group of 15 PhD and postdoctoral researchers , including Jieyu Zhang, Benlin Liu, and Cheng-Yu Hsieh. His teams have developed benchmarks like MemoryBench and The Colosseum , and his PathFinder framework achieved 74% accuracy in skin melanoma diagnosis—surpassing human experts by 9%. Notable contributions include: Perception Tokens for visual reasoning in MLMs SAM2Act for robotic manipulation with memory Synthetic Visual Genome dataset with 5.6M relationships

Matthias Feurerمشاهده پروفایل

استاد

• Automated Machine Learning
• Hyperparameter Optimization
• Bayesian Optimization
• +۵ مورد دیگر

Matthias Feurer is a Thomas Bayes Fellow and interim professor at the Chair of Statistical Learning and Data Science, funded by the Munich Center for Machine Learning (MCML) at Ludwig Maximilian University of Munich. He is a member of the Department of Statistics at LMU Munich, working under Prof. Dr. Bernd Bischl. His academic background includes: PhD in Computer Science from Albert-Ludwigs-Universität Freiburg, supervised by Prof. Dr. Frank Hutter M.Sc. in Computer Science from the University of Freiburg B.Sc. in Computer Science and Media from the Media University Stuttgart Feurer's research focuses on simplifying machine learning usage through Automated Machine Learning (AutoML). His work encompasses hyperparameter optimization, meta-learning, and model selection, with increasing emphasis on multi-objective AutoML that considers factors beyond predictive performance such as interpretability, deployability, and fairness. He actively develops open-source tools to advance the field. His recent publications demonstrate a strong trajectory in practical AutoML systems, with growing attention to tabular machine learning, foundation models integration, and addressing real-world constraints in optimization. His work consistently bridges theoretical advances with practical implementations through several widely-used open-source projects. Notable achievements include: 1st place in the warmstarting-friendly leaderboard of the BBO NeurIPS challenge Winner of the 2nd AutoML challenge Winner of the kdnuggets blog contest on AutoML Feurer is actively mentoring and teaching, having advertised PhD positions focused on AutoML, optimization, and benchmarking. He co-founded the Open Machine Learning Foundation supporting OpenML.org. His upcoming move to TU Dortmund as an assistant professor in AutoML and Optimization signals continued growth in his academic career while maintaining his research focus on making machine learning more accessible and rigorous.