Andrea Voyer is a Professor of Sociology at Stockholm University , focusing on social norms, boundaries, and their role in shaping social inequality , particularly in the context of immigrant integration , class disparities, and ethnic inequality. She employs both qualitative and computational methods , including large-scale text analysis and cultural theory, to explore these themes. Her research has received funding from Riksbankens Jubileumsfond , the Swedish Research Council , the National Science Foundation (USA) , and the Russell Sage Foundation . Voyer serves as a program coordinator for master's programs in sociology and applied social research, and leads the department's research groups in qualitative methods , computational sociology , and cultural sociology . She is also an editorial board member for Sociological Theory and American Journal of Cultural Sociology , and contributes to public discourse on immigration, segregation, and social norms. Her recent publications highlight the use of computational techniques to analyze immigrant incorporation through shifts in mainstream discourse, the cultural processes of inequality during the COVID-19 pandemic , and the evolving role of class distinction-making in etiquette literature. These works bridge cultural theory with empirical analysis, offering actionable insights for addressing social inequality.
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Jan Alber is a Professor of Modern English and American Literature at the Department of English and American Literature and Culture, Justus Liebig University Giessen . He previously held positions at RWTH Aachen, Aarhus University, TU Darmstadt, and the University of Freiburg. His work bridges narrative theory, cognitive studies, and postcolonial literature, with a focus on unnatural narratives and empirical approaches to literary analysis. Fields of Interest: Unnatural Narratology, Cognitive Literary Studies, Climate Fiction, Postcolonial Literature Key Themes: Storyworlds, Ideology, Empirical Methods, Narrative Beginnings Alber's recent publications explore narrative theory's intersections with cognition and ideology, including analyses of digital post-postmodernist novels and climate change narratives. His empirical studies examine how readers process experimental narratives, particularly unnatural narrators and metaleptic structures. He has received prestigious awards such as the Habilitation Prize from the German Association of Anglists (2013) and the FRIAS junior group competition (2008). His research is funded by the AHRC, DFG, and Alexander von Humboldt Foundation, notably supporting interdisciplinary work on post-truth political narratives and Ukrainian scholars. Alber co-founded the Aachen Center for Cognitive and Empirical Literary Studies and serves as President of the International Society for the Study of Narrative. He organizes international workshops on cognitive narratology and teaches courses spanning literary history, theory, and postmodern fiction.
David Bammanمشاهده پروفایل
دانشیار
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.
Aarti Singh is a Professor in the Machine Learning Department at Carnegie Mellon University and Director of the NSF AI Institute for Societal Decision Making. She leads research at the intersection of machine learning, statistics, and decision making, with applications to scientific and societal domains. Her work focuses on designing principled interactive algorithms for learning and decision making under uncertainty. Education: Ph.D. in Electrical Engineering, University of Wisconsin-Madison (2008) M.S. in Electrical Engineering, University of Wisconsin-Madison (2003) B.E. in Electronics and Communication Engineering, University of Delhi (2001) Research Interests: Professor Singh's research centers on developing interactive machine learning algorithms that go beyond finding input-output associations to make higher-level decisions about the most informative data and actions. Her work spans autonomous decision making, including active sampling, stochastic optimization, bandits, and reinforcement learning that are statistically optimal, computationally tractable, and robust. She also investigates human factors in decision making, designing algorithms that model and leverage human feedback while accounting for bias, memory effects, and calibration. Her research has applications in material science, cosmology, and peer review systems. Research Trends: Professor Singh's recent publications demonstrate a strong focus on reinforcement learning, particularly in developing more efficient and robust algorithms for decision making under uncertainty. Her work bridges theoretical foundations with practical applications, spanning from fundamental algorithm development to real-world implementation in scientific domains. There's a clear trajectory toward integrating human factors into decision-making algorithms, with significant contributions to peer review systems and preference learning. Scientific Awards: NSF Career Award United States Air Force Young Investigator Award A. Nico Habermann Faculty Chair Award Harold A. Peterson Best Dissertation Award Multiple paper awards Advising and Grants: Professor Singh has advised numerous PhD and master's students, many of whom have gone on to faculty positions or research roles at leading institutions. Her research is supported by prestigious grants from ONR, Simons Foundation, AFRL, ARL, and NSF. She serves as General Chair (2025) and Program Chair (2020) for the International Conference on Machine Learning (ICML) and has held leadership roles in multiple professional organizations. Research Team: Professor Singh leads a vibrant research group within the Machine Learning Department at CMU, with current PhD students working on topics including reinforcement learning, human-AI collaboration, and decision making under uncertainty. She also directs the NSF AI Institute for Societal Decision Making, which brings together researchers from multiple disciplines to develop AI systems that support human decision making in societal contexts.
- Syntax
- Psycholinguistics
- Relative Clauses
- +۶ مورد دیگر
Elaine Francis is a Professor of English and Linguistics at Purdue University's College of Liberal Arts, where she serves as Associate Head of the Department of English and directs the Experimental Linguistics Lab. She holds additional affiliations as an Affiliate Faculty Member in the Department of Linguistics and a Courtesy Faculty Member in the Department of Speech, Language, and Hearing Sciences. Ph.D. in Linguistics, University of Chicago (1999) B.A. in Linguistics, College of William and Mary (1993) MA in Linguistics, University of Chicago (1995) Former Assistant Professor at the University of Hong Kong (1999-2002) Professor Francis's research focuses on syntax and its interfaces with semantics, discourse information structure, and language processing in production and comprehension. She employs experimental methods to investigate syntactic, semantic, discourse-pragmatic, and cognitive factors underlying complex sentence structures. Her primary research areas include word order alternations, filler-gap dependencies, resumptive pronouns, and grammatical acceptability. She examines how various factors contribute to grammatical alternations in language use and explores how processing pressures in production and comprehension contribute to grammatical conventions. Her recent publication record shows consistent output across multiple linguistic subfields, with a strong emphasis on experimental syntax and psycholinguistics. Her 2022 book, Gradient Acceptability and Linguistic Theory , represents a significant contribution to understanding acceptability judgment tasks in relation to syntactic theory. Her work spans theoretical syntax, experimental linguistics, second language acquisition, and cross-linguistic comparison, often bridging the gap between theoretical frameworks and empirical evidence. Regularly teaches short courses at Linguistic Society of America Linguistic Institutes Member of Linguistic Society of America Ethics Committee Editorial board member of Glossa Psycholinguistics Co-editor of Polymorphous Linguistics: Jim McCawley's Legacy (2005) Co-editor of Mismatch: Form-Function Incongruity and the Architecture of Grammar (2003) Professor Francis actively supervises graduate students in linguistics, though she has indicated she will be unable to take on new graduate students for the 2025-2026 academic year. She has received research support for her experimental work, particularly for investigating syntactic phenomena through controlled experiments and corpus analysis. Her collaborative work extends across multiple institutions and disciplines, including collaborations with researchers in computational linguistics, cognitive science, and clinical linguistics. She directs the Experimental Linguistics Lab at Purdue University, which conducts research on syntactic processing using various experimental methodologies. The lab investigates how speakers produce and comprehend complex sentence structures, with particular attention to how grammatical knowledge interacts with processing constraints. Current projects include research on relative clauses, syntactic islands, and acceptability gradient phenomena across multiple languages.
- Learning
- Memory
- Decision Making
- +۶ مورد دیگر
Samuel J. Gershman is a Professor of Psychology at Harvard University, affiliated with both the Department of Psychology and the Center for Brain Science. He directs the Computational Cognitive Neuroscience Lab (CCNLab), where he investigates how the brain acquires richly structured knowledge about the environment and uses this knowledge to guide adaptive behavior. Gershman received his B.A. in Neuroscience and Behavior from Columbia University in 2007 and his Ph.D. in Psychology and Neuroscience from Princeton University in 2013, followed by postdoctoral training in the Department of Brain and Cognitive Sciences at MIT (2013-2015). His research spans computational neuroscience, cognitive psychology, and machine learning. His primary research interests include learning, memory, decision making, and computational neuroscience. Gershman's work integrates behavioral, neuroimaging, and computational techniques to understand cognitive processes. He has made significant contributions to understanding memory systems, reinforcement learning, and the computational principles underlying human cognition. Analysis of Gershman's recent publications reveals a strong focus on computational approaches to understanding cognitive processes, with particular emphasis on memory systems, decision-making mechanisms, and the intersection of artificial intelligence with cognitive neuroscience. His work often bridges theoretical computational models with empirical neuroscience data, exploring how the brain implements efficient cognitive algorithms. Gershman actively mentors graduate students and postdoctoral researchers, with current advisees working on diverse projects spanning computational modeling, neuroimaging, and behavioral experiments. His lab investigates topics ranging from dopamine signaling to social cognition using a combination of theoretical and experimental approaches. The CCNLab, which Gershman directs, brings together researchers from psychology, neuroscience, computer science, and related fields to explore the computational principles of cognition. The lab utilizes a range of methodologies including behavioral experiments, neuroimaging, computational modeling, and theoretical analysis to address fundamental questions about how the mind works.
Jiayi Luمشاهده پروفایل
پژوهشگر
- Syntax
- Psycholinguistics
- Chinese Linguistics
- +۳ مورد دیگر
Jiayi Lu is a PostDoc Researcher at the University of Pennsylvania School of Arts & Sciences, working under the supervision of Dr. Julie Anne Legate. Her research focuses on syntax, psycholinguistics, and Chinese linguistics, with a particular emphasis on grammaticality judgments, satiation effects, and island phenomena. She has contributed to understanding how sentence processing and discourse factors influence syntactic structures. Her research interests encompass syntax, psycholinguistics, and formal semantics, with a focus on exploring grammaticality illusions, the role of discourse in syntactic constraints, and cross-linguistic variations in Chinese. Key areas include the study of extraction islands, coordination effects, and the cognitive mechanisms underlying sentence processing. Her recent work (2020-2024) demonstrates a strong focus on syntactic satiation, island effects, and experimental methods in syntax. Publications analyze both English and Chinese data, investigating how linguistic structures are processed and judged by speakers. Trends include exploring the generalizability of satiation across island types and the interplay between discourse and syntactic constraints. Dr. Lu has not listed any scientific awards or grants in the provided information. Dr. Lu has not listed any advisees or grants in the provided information.
Peter Bühlmann is a Professor at ETH Zürich within the Seminar für Statistik , focusing on high-dimensional statistics, causal inference, and machine learning. His work bridges theoretical advancements with practical software implementations in R packages like pcalg , mboost , and glmmlasso , impacting fields such as genomics, proteomics, and intensive care analytics. Key Contributions : Causal structure learning, stability selection, anchor regression, and deconfounding. Software : Developed widely used R packages for statistical modeling and causal inference. Teaching : Courses on high-dimensional statistics at ETH Zürich and international institutions. Research Trends : Recent articles emphasize causal robustness, domain adaptation, and applications in medicine. His work addresses challenges in heterogeneous data, missing values, and covariate shifts using methods like spectral deconfounding and residual prediction tests. Scientific Recognition : Co-author of a paper designated as a New Hot Paper (Meinshausen and Bühlmann, 2006) by Essential Science Indicators, indicating significant impact in high-dimensional multiple testing.
Ariel Pakes is the Thomas Professor of Economics at Harvard University, part of the Faculty of Arts and Sciences and the Department of Economics. He previously held the Charles and Dorothea Dilley Professorship at Yale University and tenured roles at institutions including the University of Wisconsin and the Hebrew University of Jerusalem. His research focuses on industrial organization (I.O.), the economics of technological change, and econometric theory. Pakes has advised notable students who now lead economics departments globally and has received prestigious awards including the Frisch Medal (1986) and election to the American Academy of Arts and Sciences (2002). Education: Pakes earned his Ph.D. in Economics from Harvard University in 1980. His academic journey includes roles as a lecturer at Harvard and positions at the University of Jerusalem. Research Interests: Pakes has pioneered methodologies for analyzing I.O. models, including demand and cost system estimation. Recent work examines AI’s impact on pricing strategies, antitrust policy implications of market dynamics, and healthcare cost structures. His theoretical contributions include simulation estimators and frameworks for dynamic oligopolies. Awards: Frisch Medal (Econometric Society, 1986) Fellow of the Econometric Society (1988) Fellow of the American Academy of Arts and Sciences (2002) Best Graduate Student Advisor Award (Yale University, 1996) Advisory and Grants: Pakes has served on NSF panels, including the Economics Advisory Panel and Presidential Fellow Advisory Board. His consulting work spans government agencies and large firms. He edited the RAND Journal of Economics and co-chaired the AEA Census Advisory Panel. Labs/Teams: Collaborates with NBER as a Research Associate and contributes to interdisciplinary projects like the PNAS issue on 'Science, Technology and the Economy.'
Prof. Dr. Oktay KIZILKAYA is a full-time Professor at Kirsehir Ahi Evran University, Faculty of Economics and Administrative Sciences, Department of Economics , Turkey. He has held academic positions since 2004, including Associate Professor (2019-2024) and Assistant Professor (2012-2018). Education: PhD and MA in Economics (2007-2012, 2004-2007), BA in Economics (1999-2004) from Selçuk University. Research Areas: International Political Economy, International Trade, International Investments, and International Economic Theories. His research focuses on the interplay between economic policies, foreign direct investment (FDI), energy consumption, environmental sustainability, and growth dynamics. Key themes include panel data analysis , co-integration , and policy implications for Turkey and emerging economies like BRICS-T. Recent publications analyze topics such as pandemic-induced uncertainty on tourism demand, eco-innovation in Germany, and the impact of political institutions on FDI. His work often employs time-series econometrics and panel causality methods . Scientific Awards: Publication Encouragement Award (2023) Publication Encouragement Award (2020) Best Researcher Award (2017, International Conference on Strategic Research in Social Science and Education) Award of 2017 (Strategic Researches Academy) Key Projects: Led 13 research projects on FDI, economic growth, environmental sustainability, and energy policy, all as principal investigator.
Salvatore Callesano is an Assistant Professor of Hispanic Linguistics at the University of Illinois Urbana-Champaign (UIUC), affiliated with the Department of Spanish and Portuguese and the College of Liberal Arts & Sciences. His research focuses on sociolinguistics, particularly bilingual communities in the U.S., language perception, and digital media representations of bilingualism. He employs both quantitative and qualitative methods to investigate how language variation interacts with identity, media, and social structures. Dr. Callesano collaborates on Project 16 of the Asociación de Lingüística y Filología de América Latina, addressing linguistic aspects of Latin American diaspora communities. His work bridges traditional sociolinguistic inquiry with modern digital practices, analyzing how social media shapes perceptions of language use among Latinx populations. Recent research highlights include studies on code-switching in Miami's linguistic landscape, dialect perception, and the role of media in mediating language attitudes. His publications span peer-reviewed articles and book reviews, emphasizing empirical rigor and interdisciplinary connections between language, culture, and society.
- Ancient History
- Turkic Studies
- Eurasian History
- +۵ مورد دیگر
Prof. Dr. Ahmet Taşağıl is a prominent historian specializing in Turkic studies, Eurasian history, and pre-Islamic cultures. He holds the rank of Professor at Yeditepe University's Faculty of Arts and Sciences, History Department, since 2015, and previously served at Mimar Sinan Fine Arts University. His academic journey includes a PhD from Istanbul University (1989-1991) and extensive research on ancient Turkic empires like the Gokturks and Huns. Education: PhD in General Turkish History (Istanbul University), MSc in Medieval History (Istanbul University), BA in History (Istanbul University). Affiliations: Currently at Yeditepe University; previously at Mimar Sinan Fine Arts University and Kirgizistan-Türkiye Manas Üniversitesi. Research Interests : Focuses on early Turkic states (Gokturks, Huns, Uyghurs), cross-cultural relations between Turkic and Chinese empires, shamanism, and pre-Islamic Turkic societies. His work bridges archaeology, ethnohistory, and political analysis, with a particular emphasis on primary sources like Chinese records and Orkhon inscriptions. Publications : Over 50 books and articles, including seminal works like Kök Tengri’nin Çocukları , Avrasya'nın Sekiz Asrı Çengizoğulları , and İslamiyet Öncesi Türkler . His research often examines the socio-political structures of nomadic empires and their legacy in Eurasian history. Awards : Recipient of the Moğalistan Devlet Onur Madalyası, Muğla Sıtkı Koçman Tarih Ödülü, and numerous academic honors. His contributions to Turkic cultural heritage are widely recognized internationally. Grants & Projects : Led projects on Central Asian archaeology, cultural atlas of the Turkic world, and historical studies of Siberian tribes. Collaborated with institutions in Kazakhstan, Russia, and Turkey. Teaching : Offers courses on pre-Islamic Turkic history, Eurasian empires, and historical methodology in Turkish and English.
Jenna Wise DiVincenzo is an Assistant Professor at the Elmore Family School of Electrical and Computer Engineering at Purdue University. She specializes in research areas such as software verification, formal methods, and programming languages, with a focus on gradual verification techniques that combine static and dynamic analysis. Her work emphasizes usability and scalability in verification tools, and she has contributed to projects like Gradual C0 and gradual null-pointer analysis. Dr. DiVincenzo earned her PhD in Software Engineering from Carnegie Mellon University (2023) and a BS in Mathematics and Computer Science from Youngstown State University (2017). She has interned at IBM Research, MIT Lincoln Laboratory, and the Software Engineering Research and Empirical Studies Lab at YSU. Her awards include the Google PhD Fellowship, NSF GRFP Fellowship, and 2022 Rising Star in EECS. Her research projects span theoretical advancements in gradual verification, empirical studies on usability, and practical tool development. She advises PhD students (e.g., Craig Liu, Conrad Zimmerman) and collaborates on initiatives like gradual verification for Rust and educational tools to teach verification concepts. Her work also explores leveraging large language models for specification generation and enhancing verification tool soundness through formal proofs.
Rizwan Ahmedمشاهده پروفایل
مدرس ارشد
- Sustainable Finance
- Green Finance
- FinTech
- +۵ مورد دیگر
Rizwan Ahmed is a Senior Lecturer in Accounting and Finance at the University of Kent 's Kent Business School . He serves as Director of Studies for the Department for Accounting and Finance, with prior experience as an Assistant Professor at institutions like the University of Birmingham, Cardiff Business School, and Birkbeck University of London. His research focuses on Sustainable Finance , FinTech , and Corporate Governance , with funding from the Economic and Social Research Council (ESRC) for collaborative projects. Fellowship of Higher Education Academy (HEA-UK) Associate Fellow Member, Chartered Institute of Securities and Investment (CISI-UK) His publications in journals like Energy Economics and International Journal of Finance and Economics examine intersections between climate risk, financial markets, and regulatory frameworks. He supervises PhD research in areas including Sustainable Finance, Climate Finance, and Corporate Governance in the financial sector. Research Trends Recent articles analyze climate change impacts , energy market spillovers , and ESG performance under sanctions, utilizing empirical methods and data from the UK, China, and emerging economies. Methodological innovations include cross-quantilogram analysis and portfolio optimization frameworks. Scientific Awards Fellowship of Higher Education Academy (HEA-UK) Associate Fellow Member, Chartered Institute of Securities and Investment (CISI-UK) Rizwan also acts as a peer reviewer for journals including International Review of Financial Analysis and Technological Forecasting & Social Change .
Daniel Cooneyمشاهده پروفایل
استادیار
Daniel Cooney is an Assistant Professor in the Department of Mathematics at the University of Illinois Urbana-Champaign. He holds additional affiliations as an Affiliate at the Carl R. Woese Institute for Genomic Biology. His research focuses on applying partial differential equations (PDEs), dynamical systems, and stochastic processes to study evolutionary dynamics, particularly in biological and social systems. Key themes include multilevel selection, evolutionary game theory, and the emergence of cooperative behavior. Cooney earned his PhD in Applied and Computational Mathematics from Princeton University, advised by Simon Levin, and completed a postdoc as a Simons Fellow in Mathematical Biology at the University of Pennsylvania. His work bridges theoretical mathematics with applications in ecology, epidemiology, and social sciences. Recent publications explore topics like altruistic punishment in cultural systems, classroom-turnover dynamics, and protocell evolution. He actively participates in academic outreach, co-organizing conferences such as the AMS Special Session on Mathematics of Infectious Disease and the SIAM Minisymposium on Social-Ecological Systems. His research has been published in high-impact journals including *Proceedings of the National Academy of Sciences* and *Bulletin of Mathematical Biology*.
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