جست‌وجوی استاد و پژوهشگر

Benedikt Bergerمشاهده پروفایل

استاد

• Digital Transformation
• Generative AI
• Business Information Systems
• +۲ مورد دیگر

Benedikt Berger is Professor of Digital Transformation and Society at the University of Münster's School of Business and Economics, Department of Information Systems. He leads research on generative AI implementation impacts and digital business transformation, with ongoing projects funded by industry partners including BASF Coatings GmbH. His research examines AI integration in organizational contexts, voice commerce systems, and human-AI collaboration frameworks. Key projects investigate generative AI's effects on workplace structures and employee experience in industrial settings. Honors include the 2024 Best Paper Award from The Data Base for Advances in Information Systems and 2022 Best Associate Editor recognition from ECIS. He supervises graduate research on topics including robotic process automation implementation.

Hamid Alinejad-Roknyمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Bioinformatics
• Genomics
• +۷ مورد دیگر

Dr. Hamid Alinejad-Rokny is a Scientia Senior Lecturer at UNSW Sydney and Adjunct Associate Professor at Concordia University. He leads the UNSW BioMedical Machine Learning (BML) Lab within the Graduate School of Biomedical Engineering. His research focuses on applying machine learning, bioinformatics, and statistical methods to understand genomic mechanisms underlying diseases like cancer and neurodevelopmental disorders. Dr. Rokny holds a PhD in Biostatistical Machine Learning from UNSW and has secured over $13M in grants as a principal or co-investigator. He has published 80+ papers, including 10 as first author and 45 as senior author. Education: Bachelor’s in Software Engineering (2004-2009), Master’s in Artificial Intelligence (2009-2012), PhD in BioMedical Machine Learning (UNSW, 2014-2018), Postdoc at Harry Perkins Institute (2017-2019). Research interests include medical AI, deep learning, genomic data analysis, and systems biology. He actively supervises 20+ PhD/Master’s students and collaborates with industry partners like CSIRO and 23Strands. Awards include the DECRA 2023, NHMRC MERIT, and International Autism Fellowships. He also serves as a keynote speaker at conferences like HUGO and an Honorary Lecturer at Macquarie University. Grants total $2.75M as lead investigator and $10.6M as co-investigator. Industry partnerships include PORSPA Advance ($4.7M) and Australian Digital Domains ($3.6M). His lab develops tools like MaxHiC and DeepGenePrior for genomic analysis. Labs/Teams: Director of UNSW BML Lab, Health Data Theme Leader at UNSW Data Science Hub. Active in mentoring 13 researchers globally and co-supervising international teams.

• Digital Responsibility
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Thomas Arnold is a Postdoctoral researcher at Technische Universität Darmstadt, specializing in Digital Responsibility, Natural Language Processing, and Machine Learning. His work focuses on developing automated tools for measuring corporate digital responsibility activities and detecting machine-generated text across multiple domains and languages. He actively participates in initiatives like Semeval tasks and has contributed to frameworks like M4 and M4gt-bench for evaluating black-box text generation systems. His research spans advanced motif analysis in text-induced networks, hierarchical data summarization, and privacy-preserving text rewriting (DP-rewrite). Notable projects include QUEST, an educational tool leveraging engaging storytelling for interactive quizzes, and EmpiriST, a robust tokenization and POS-tagging system for diverse text genres. Publications highlight trends in ethical AI, corporate strategy evaluation, and cross-domain NLP challenges. Recent work emphasizes transparency in AI systems and the intersection of digital ethics with corporate governance. He is affiliated with TU Darmstadt's Department of Computer Science (implied through research focus) and maintains professional profiles on LinkedIn. No specific awards or grants are listed in the provided data.

Fan Gang Zengمشاهده پروفایل

استاد

• Cochlear Implants
• Auditory Neuroscience
• Speech Perception
• +۶ مورد دیگر

Fan Gang Zeng is a Professor in the Department of Otolaryngology at the University of California, Irvine (UCI), and Director of the Center for Hearing Research. His academic roles span multiple disciplines, including joint appointments in Anatomy & Neurobiology, Biomedical Engineering (BME), Cognitive Sciences, and SOM-Administration. His research focuses on auditory neuroscience, cochlear implants, tinnitus, and speech perception, with a particular emphasis on improving hearing restoration technologies and understanding neural mechanisms of hearing loss. Affiliations: Director, Center for Hearing Research Member, UCI Institute for Memory Impairments and Neurological Disorders (UCI MIND) NIH-funded investigator through grants like R01 DC015587 Research Interests: Professor Zeng’s work bridges engineering and neuroscience, addressing challenges in cochlear implant optimization, tinnitus biomarkers, and speech intelligibility. Key areas include: Noninvasive ear stimulation for tinnitus suppression Cochlear implant artifact attenuation techniques Cognitive correlates of auditory brainstem responses Speech processing algorithms for hearing aids and implants Grants & Funding: His research is supported by NIH grants and industry partnerships, including collaborations with companies like Axonics, Nurotron, and Syntiant. He holds patents related to cochlear implant design and neural stimulation technologies. Labs & Teams: The Center for Hearing Research at UCI integrates multidisciplinary teams to advance audiological innovations, with a focus on translating basic science into clinical applications.

Edward B. Kangمشاهده پروفایل

استادیار

• Science and Technology Studies (STS)
• History and Philosophy of Science
• Communication Studies
• +۹ مورد دیگر

Edward B. Kang is an Assistant Professor in the Department of Media, Culture, and Communication at New York University’s Steinhardt School. He co-directs a National Endowment for the Humanities (NEH)-funded project titled Machine Listening in the Age of Artificial Intelligence and co-organizes the AI in Society group at the Institute for Public Knowledge (IPK). His research explores how voice AI systems reconfigure human voices into measurable mechanisms, challenging assumptions about intelligence, emotion, and perception through frameworks spanning STS, philosophy of science, and sound studies. Education: Ph.D. in Communication with a graduate certificate in Science & Technology Studies from the University of Southern California’s Annenberg School. Previously affiliated with the AI research collective Knowing Machines (Sloan Foundation-funded) and served as Assistant Editor for the International Journal of Communication . Research focuses on intersections between AI, cognitive psychology, neuroscience, and digital platforms like Spotify and Tinder. His current book project, Machine Voices (MIT Press), examines voice AI systems’ epistemological underpinnings. Recent publications address AI benchmarking cultures, biometric data formation, and algorithmic policing infrastructure. Grants/Advising: NEH grant for Machine Listening project. No listed advisees but collaborates widely with interdisciplinary teams. Active in public knowledge initiatives through IPK and ACM conferences. Labs/Teams: Co-leads AI in Society at IPK; affiliated with NYU’s Media, Culture, and Communication program. Previously part of USC’s Knowing Machines collective.

Christian Pipalمشاهده پروفایل

پژوهشگر

• Digital political communication
• Elite behavior
• Computational social science methods

Christian Pipal is a Senior Research and Teaching Associate and External Lecturer at the Department of Communication and Media Research, University of Zurich, Switzerland. He concurrently holds a Ph.D. researcher position at the Department of Political Science, University of Amsterdam (since 2019), and has served as a Visiting Researcher at the University of Vienna (2020-2021) and a Research Associate at NEOS Lab (2018-2019). His academic journey includes a B.A. in International Development Studies (University of Vienna, 2013) and an M.A. in European Union and Russia Studies (University of Tartu, 2015). Pipal’s research focuses on digital political communication, elite behavior, and computational methods, with particular emphasis on text analysis, sentiment modeling, and multimodal data integration. His Ph.D. thesis, funded by the Horizon 2020 POLEMIC project, examines “The Emotional Rhetoric of Political Elites” , supervised by Gijs Schumacher, Mariken van der Velden, and Bert Bakker. Pipal’s work bridges political psychology, computational social science, and digital media studies, with contributions to datasets like EUSpeech V2 and methodological frameworks such as the MEXCA emotion pipeline. Pipal’s articles address challenges in computational text analysis, political tone dynamics, and social media engagement. His research agenda emphasizes overcoming gaps in validation practices, cross-lingual analysis, and methodological transparency. He has also explored TikTok’s role in political communication, NATO framing in the Ukraine conflict, and multiverse approaches to news-sharing behavior. His grants include the Horizon 2020 POLEMIC funding and collaborative projects at the NEOS Lab. Pipal actively contributes to labs like the Computational Communication Lab (University of Vienna) and co-develops tools for emotion expression analysis. His work intersects with interdisciplinary teams in political science, computer science, and behavioral psychology.

Philip Jacksonمشاهده پروفایل

استاد

• Machine Audition
• Audio-Visual Machine Learning
• Spatial Audio
• +۹ مورد دیگر

Philip Jackson is a Professor in Machine Audition at the University of Surrey's Centre for Vision, Speech and Signal Processing (CVSSP) within the School of Computer Science and Electronic Engineering. His research focuses on audio-visual machine learning, spatial audio technologies, object-based media production, and responsible AI applications. He has over 200 publications and an h-index of 30, contributing to projects like Nephthys, BALTHASAR, and SAVEE. He served as an associate editor for Computer Speech and Language and reviewer for major journals like IEEE/ACM Transactions on Audio, Speech and Language Processing. Key research interests include sound localization, audio-visual tracking, reverberation modeling, and ethical implications of AI in media. His work spans datasets such as Tragic Talkers, SurrRoom, and ForecasterFlexOBM, advancing immersive audio-visual systems and personalized media experiences. Notable projects include spatial audio reproduction for VR, parametric room acoustics, and citizen council research on algorithmic transparency. He has advised over 20 PhD/Master’s students and collaborates with industry on applications like the Catalan Pavilion's Venice Biennale installation. His grants include UK postdoctoral fellowships and leadership in EU-funded initiatives like UDRC2 and QESTRAL.

James Caverleeمشاهده پروفایل

استاد

• Machine Learning
• Recommender Systems
• Information Retrieval
• +۷ مورد دیگر

James Caverlee is a Professor in the Department of Computer Science and Engineering at Texas A&M University, and a Visiting Researcher at Google DeepMind. He holds a Ph.D. from Georgia Institute of Technology (2007), and degrees from Stanford University and Duke University. His research focuses on trustworthy, efficient, and personalized machine learning systems, including Recommender Systems, Large Language Models (LLMs), and bias mitigation. Recent work emphasizes fairness, efficiency, and transparency in AI, with applications in conversational systems, speech, and medical QA. He has been recognized with an NSF CAREER Award, AFOSR Young Investigator Award, and DARPA Young Faculty Award. His group has published extensively at top venues like KDD, EMNLP, WWW, SIGIR, and WSDM. Education: Ph.D., Computer Science, Georgia Tech, 2007 M.S., Computer Science & Engineering-Economic Systems, Stanford University, 2001–2000 B.A., Economics, Duke University, 1996 Research Interests: Machine Learning, Recommender Systems, NLP, LLMs Bias Mitigation, Efficiency, Personalization Social Computing, Information Retrieval Awards: NSF CAREER Award (2012) AFOSR Young Investigator (2012) SIGIR Test of Time Honorable Mention (2022) Grants: Supported by NSF, AFOSR, DARPA, and industry (Google, Amazon). Labs/Teams: InfLab research group at Texas A&M, collaborating with Google DeepMind. His publications address topics like adversarial attacks on LMs, gender bias in podcasts, and efficient recommendation algorithms. Recent trends show focus on generative AI for personalization and ethical AI challenges.

Nitesh Saxenaمشاهده پروفایل

استاد

• Cybersecurity
• Privacy Engineering
• Applied Cryptography
• +۵ مورد دیگر

Nitesh Saxena is a Full Professor of Computer Science & Engineering at Texas A&M University, serving as Associate Director of the Texas A&M Global Cyber Research Institute (GCRI) and 2022-23 Engineering Dean’s Research Fellow. His research focuses on cybersecurity, privacy, applied cryptography, and neuro security, with interdisciplinary approaches bridging computer science, psychology, and criminal justice. He leads the SPIES Lab, exploring security in emerging systems like IoT, AR/VR, and AI. Saxena is a key figure in cybersecurity education, having directed NSF-funded programs such as CyberCorps Scholarship for Service and M.S. cybersecurity initiatives. His work has been supported by NSF, DOD, NSA, Google, and industry partners. Education: Ph.D. (UC Irvine, 2006), M.S. (UC Santa Barbara, 2002), B.S. (IIT Kharagpur, 2000) Research interests emphasize transformative cybersecurity solutions, including privacy-preserving AI, device security, and human factors. Over 20 grants total over $10M, including a 2023 MURI award for neuro security. Awards include the Mark Weiser Best Paper Award (2019) and 2025 Dean’s Excellence Award. He serves on editorial boards for IEEE TIFS and ACM TOPS. Grants include $4.5M NSF Scholarship for Service (2022), $6.2M MURI (2023), and $75K MxD grants (2021, 2023). Advises on workforce development and chairs major conferences like CNS and WiSec. SPIES Lab innovations span secure messaging, biometric authentication, and AR/VR privacy.

• Predictive Analytics
• Machine Learning
• Biologically Inspired Knowledge Discovery
• +۷ مورد دیگر

Anasse Bari is a Clinical Assistant Professor of Computer Science at New York University’s Courant Institute of Mathematical Sciences. His research focuses on predictive analytics, machine learning, biologically inspired knowledge discovery, and data science. He leads the AI and Predictive Analytics research group and lab, which develops specialized AI solutions for healthcare, finance, politics, and societal challenges. Bari is an award-winning educator and author of Predictive Analytics for Dummies , and a Fulbright Scholar. Education: Ph.D. in Computer Science from George Washington University (2012). Research Interests: Bari’s work spans predictive analytics applications in diverse fields, including fake news detection, climate change modeling, vaccine hesitancy analysis, and cultural impact studies. He emphasizes interdisciplinary approaches, leveraging machine learning for societal and organizational challenges. Awards: Recipient of the Golden Dozen Award for research contributions and a Fulbright Scholar designation. His work has been featured in Science , CNBC , The Washington Post , and France24 . Labs/Teams: Head of the AI and Predictive Analytics Lab at NYU, which collaborates with global organizations to design AI solutions. He advises on data strategy for leading international entities and delivers keynote speeches on AI’s role in decision-making.

Laurent Girinمشاهده پروفایل

استاد

• Speech Processing
• Audio Signal Processing
• Signal Processing
• +۴ مورد دیگر

Laurent Girin is a Professor at Grenoble Institute of Technology (Grenoble-INP), a member of Univ. Grenoble Alpes. He teaches within PHELMA (Physics, Electronics and Materials Department) and conducts research at GIPSA-Lab, a CNRS-associated laboratory focused on image, speech, signal, and automation sciences. He also maintains a collaborative relationship with the INRIA-Perception research team, contributing to advanced perception systems and audio-visual signal analysis. His research interests lie primarily in speech and audio signal processing , with applications in human-machine interaction, acoustic modeling, and machine learning for audio. His work bridges engineering and cognitive sciences, aiming to model and understand complex audio signals in real-world environments. Laurent Girin has contributed extensively to the field through publications in signal processing and audio analysis. While specific titles are not listed here, his research trends indicate a strong focus on computational auditory scene analysis, speaker tracking, and multimodal perception systems. Member of GIPSA-Lab, CNRS & Univ. Grenoble Alpes Regular collaborator, INRIA-Perception team He advises students in signal processing and audio technologies, though specific names are not provided. There is no public information on grants or funding sources in the provided text. His work is supported through institutional collaborations between Grenoble-INP, CNRS, and INRIA. Laurent Girin is actively involved in research teams focusing on perception and signal processing, particularly within the GIPSA-Lab and INRIA-Perception environments. These labs specialize in advanced signal analysis, machine learning for sensory data, and intelligent systems development.

• Computer Vision
• Machine Learning
• 4D Vision
• +۹ مورد دیگر

Adrian Hilton is a Professor of AI and Computer Vision at the University of Surrey, UK. He serves as the Founding Director of the Surrey Institute for People-Centred AI and Director of the Centre for Vision, Speech and Signal Processing. His research focuses on advanced fields such as 4D Vision, Computer Graphics, and AI-driven Digital Doubles. He holds prestigious fellowships including Fellow of the Royal Academy of Engineering, IET Fellow, and IAPR Fellow. His work spans interdisciplinary areas like Virtual/Augmented Reality, Light Fields, and Audio-Visual Signal Processing. No specific grants, students, or recent publications are detailed in the provided text, but his leadership roles highlight significant contributions to AI and computer vision research.

Sasha Talaveraمشاهده پروفایل

استاد

• Financial Economics
• Banking
• Fintech
• +۸ مورد دیگر

Sasha Talavera is a Professor in Financial Economics at the Department of Economics, Birmingham Business School, University of Birmingham, where he joined in 2019. He previously held professorial and academic positions at Swansea University, University of Sheffield, Durham University, University of East Anglia, and DIW-Berlin. PhD in Economics, European University Viadrina MA in Economics, Boston College MA in Economics, Kyiv School of Economics BA in Economics, Ostroh Academy His research focuses on financial economics, with specific interests in online prices, big data analytics, banking, fintech, corporate finance, behavioral finance, and emerging markets. His work integrates empirical methods with real-world financial and economic data to address policy-relevant questions. The recent publications reflect a strong trend in analyzing financial behavior under crisis (e.g., war in Ukraine), monetary policy communication, and the application of big data and text analysis in economics. His research spans disciplines including econometrics, financial stability, labor economics, and public choice, often using innovative data sources such as online job ads and social media. Sasha Talavera is actively involved in the academic community, serving on the editorial boards of Bank i Kredyt , Visnyk NBU , and as founder of VoxUkraine.org . He is also an expert for the International Monetary Fund (IMF). He supervises several PhD students, including Zixi Guo, Mohammad Aldoub, and Fei Ge, and has successfully placed past advisees in institutions such as the Capital Market Authority of Kuwait, Aston University, and NHS England. He has not received any explicitly mentioned scientific awards in the provided text. He leads a dynamic research agenda involving big data, crisis economics, and financial decision-making, contributing significantly to both academic and policy-oriented discourse.

Concepción Godevمشاهده پروفایل

استاد

• Applied Linguistics
• Translation Studies
• Spanish Language Teaching
• +۴ مورد دیگر

Concepción Godev is a Professor in the Department of Languages, Cultures and Translation at the University of North Carolina at Charlotte. Her academic career spans decades of research and teaching in applied linguistics and translation studies. Ph.D. in Spanish Applied Linguistics (Pennsylvania State University, 1992) Ph.D. in Spanish Applied Linguistics (Universitat de Barcelona, 2006) M.A. in Spanish Literature and Linguistics (Pennsylvania State University, 1988) BA in Spanish Literature and Linguistics (Universidad de Málaga, 1984) Her research focuses on applied linguistics, translation pedagogy, blended learning, and gender inclusivity in Spanish language teaching. She has published extensively on these topics, often integrating technology and cross-cultural analysis into her work. Recent publications highlight her expertise in translation-project management, blended learning effectiveness, and inclusive language practices in educational settings. Her work bridges theoretical linguistics with practical applications in language acquisition. As a faculty member, she contributes to curriculum development and interdisciplinary research, with a particular emphasis on leveraging translation to enhance language learning in digital environments.

Itamar Jalonمشاهده پروفایل

پژوهشگر ارشد

• Cognitive Neuroscience
• Computational Neuroscience
• Natural Language Processing
• +۳ مورد دیگر

Itamar Jalon is a Postdoctoral Research Associate at the Princeton Neuroscience Institute (PNI) at Princeton University for the 2024-25 academic year, affiliated with both the Hasson Lab and Music Cognition Lab. His research leverages deep learning models to study social and higher-order cognitive processes—including meaning-making in naturalistic interactions, emotion, self- and other-perception, and creativity—in ecologically valid settings. Dr. Jalon earned his PhD (pending approval) in psychology from Tel Aviv University, where his doctoral work focused on computational representations of autobiographical emotions. Prior research spans the neuroscience of pain, creativity, neuromodulation, and psychiatric interventions, reflecting an interdisciplinary approach bridging psychology, neuroscience, and artificial intelligence. His current work applies large language models to decode naturalistic human speech and ECoG neural recordings, targeting real-world cognitive phenomena. This positions him at the intersection of machine learning and cognitive neuroscience, with emphasis on affective and social processes in uncontrolled environments. No scientific awards or honors were documented in the provided materials. Information regarding student mentorship, research grants, or advising activities was not specified in the source text. Dr. Jalon actively contributes to two specialized research units at PNI: the Hasson Lab (investigating neural mechanisms of communication) and the Music Cognition Lab (exploring cognitive foundations of musical experience), utilizing these platforms for naturalistic neuroscience methodologies.