جست‌وجوی استاد و پژوهشگر

Peter Müller-Buschbaumمشاهده پروفایل

استاد

• Materials Science
• Polymer Physics
• Energy Materials
• +۶ مورد دیگر

Prof. Peter Müller-Buschbaum is a Full Professor and Head of the Chair of Functional Materials at the Physics Department of the Technical University of Munich (TUM). He has held this position since April 2018 and also served as Scientific Director of the Research Neutron Source Heinz Maier-Leibnitz (FRM-II) and the Heinz Maier-Leibnitz Center (MLZ) from 2018 to 2023. His leadership extends to multiple roles including Core Member of the Integrated Research Institute Munich Institute of Integrated Materials, Energy and Process Engineering (MEP) since 2021, and Head of the Renewable Energies Network (NRG) at MEP. Full Professor (W3), Head of the Chair of Functional Materials at TUM School of Natural Sciences (since 04/2018) Deputy Editor of "ACS Applied Materials & Interfaces" (since 01/2024) Supervising Professor "Electronics Laboratory" at TUM School of Natural Sciences (since 11/2023) Member of TUM Sustainability Board (since 05/2023) Core Member of MEP Institute (since 10/2021) Head of Renewable Energies Network at MEP (since 10/2021) Prof. Müller-Buschbaum's research spans energy materials for photovoltaics and battery technologies, smart responsive materials that adapt to environmental stimuli, and nanocomposite materials with tailored properties. His group employs advanced scattering techniques to characterize materials at the nanoscale, providing insights into structure-property relationships critical for developing next-generation energy technologies. His extensive publication record demonstrates particular expertise in perovskite solar cells, lithium-ion battery technologies, and polymer-based functional materials, with recent work focusing on improving device stability and efficiency while understanding fundamental degradation mechanisms. His publications reveal a strong emphasis on energy conversion and storage technologies, with particular attention to interfacial engineering in both photovoltaic and battery systems. The research shows sophisticated integration of materials synthesis, advanced characterization, and device engineering to address critical challenges in renewable energy technologies. His work bridges fundamental science with practical applications through collaborations with major international research facilities. Scientific Service and Recognition Member of the Council of the Cluster of Excellence "ORIGINS" (since 01/2019) Spokesperson of the Chemical Physics and Polymer Physics Association of DPG (03/2021-10/2022) Member of the European Spallation Source Scientific Advisory Panel (since 03/2011) German representative at the European Polymer Federation for polymer physics (since 03/2011) Chairman of the Keylab "TUM.solar" in the Bavarian research project "Solar Technologies Go Hybrid" (since 03/2012) Prof. Müller-Buschbaum actively contributes to academic community through editorial work, having served as Associate Editor (2012-2022), Executive Editor (2023), and currently Deputy Editor (2024-present) of "ACS Applied Materials & Interfaces". He maintains strong international collaborations with synchrotron and neutron facilities worldwide, reflecting his expertise in advanced materials characterization techniques essential for cutting-edge materials research.

Cristian Danescu-Niculescu-Mizilمشاهده پروفایل

دانشیار

• Computational Social Science
• Data Science
• Natural Language Processing
• +۴ مورد دیگر

Cristian Danescu-Niculescu-Mizil is an Associate Professor at the Department of Information Science , Cornell University . His research focuses on computational frameworks for social behavior analysis through large-scale natural language data , particularly in online communities and crisis counseling contexts. Recipient of WWW Best Paper Award (2013) and Yahoo! Key Scientific Challenges Award Co-developer of ConvoKit , a comprehensive conversational analysis toolkit Principal investigator in NLP for mental health , antisocial behavior detection , and linguistic coordination studies His work spans computational social science and human-centered AI , with recent publications in EMNLP 2025 , ACL 2025 , and CSCW 2025 focusing on conversation dynamics modeling , pivotal moment detection , and talk-time equity analysis . He has advised multiple PhD students who became faculty at Harvey Mudd , University of Michigan , and Thompson Reuters . Key scientific contributions : 2013 : WWW Best Paper - Power dynamics through linguistic coordination 2016 : IJCAI NLP & Journalism Best Paper - Gender bias quantification 2017 : ICWSM Best Paper - Trolling behavior analysis He teaches NLP and Social Interaction (INFO/CS 6742) and Language and Information (INFO/CS 4300) , with teaching resources including the Politeness Web App and ConvoWizard interactive tool featured in NPR's Weekend Edition . His work has been covered by New Scientist , NBC Today Show , and New York Times .

Christopher Lawsonمشاهده پروفایل

استادیار

• Microbiome Engineering
• Systems Biology
• Synthetic Biology
• +۵ مورد دیگر

Christopher Lawson is an Assistant Professor in the Department of Chemical Engineering and Applied Chemistry at the University of Toronto, affiliated with the Faculty of Applied Science and Engineering. He serves as Principal Investigator of the Microbiome Engineering Lab and is part of BioZone – the Centre for Applied Bioscience and Bioengineering. His research focuses on engineering anaerobic microbiomes for resource recovery from waste streams using systems biology, synthetic biology, and machine learning approaches. B.A.Sc., M.A.Sc. (University of British Columbia) Ph.D. (University of Wisconsin-Madison) Postdoctoral Training (Berkeley Lab) Lawson's work addresses the challenge of controlling complex microbial interactions in engineered systems to enable scalable biotechnologies for renewable energy, chemicals, and materials. His lab develops high-throughput methods integrating automation and computational tools to optimize microbiome assembly and metabolic fluxes. Recent publications highlight advancements in metabolic modeling , isotope tracing , and systems-level analysis of anaerobic microbiomes, with applications in wastewater treatment , anammox granules , and bioenergy production . His research bridges fundamental microbiology with industrial-scale bioprocess engineering. Scientific Awards ISME/IWA BioCluster Rising Star Award (2022) Jacobs Engineering Group/AEESP Outstanding Doctoral Dissertation Award (2020) Wesley Eckenfelder Graduate Research Award (2019) WEF Canham Graduate Studies Scholarship (2018) NSERC Post-Graduate Scholarship – Doctoral (2014) Lawson actively mentors students and postdocs, emphasizing technical rigor, communication skills, and independence. His lab collaborates within BioZone and with industry partners to advance "team science" principles. Current projects focus on creating engineered microbiomes for commercial-scale waste valorization.

Oisin Mac Aodhaمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• 3D Understanding
• +۳ مورد دیگر

Oisin Mac Aodha is a Reader (Associate Professor) in Machine Learning at the School of Informatics, University of Edinburgh. He is also an ELLIS Scholar and founder of the Turing interest group on biodiversity monitoring and forecasting, having previously served as a Turing Fellow from 2021-2025. Mac Aodha completed his undergraduate degree in electronic engineering from the University of Galway in Ireland, followed by his MSc and PhD at University College London (UCL). His academic journey includes postdoctoral positions at UCL (2013-2016) working with Prof. Gabriel Brostow and Prof. Kate Jones, and at Caltech (2016-2019) in Prof. Pietro Perona's Computational Vision Lab as part of the Visipedia team. His research centers on computer vision and machine learning with emphasis on 3D understanding, human-in-the-loop methods, and AI for conservation and biodiversity monitoring. He has made significant contributions to monocular depth estimation (including the influential Monodepth2 paper), fine-grained visual categorization, and biodiversity monitoring systems. His work bridges theoretical machine learning with practical ecological applications, developing tools for species identification, range estimation, and conservation efforts. Recent publications reveal a strong trend toward ecological applications while maintaining fundamental contributions to 3D vision and representation learning. His major scientific achievements include: Turing Fellow (2021-2025) ELLIS Scholar Founder of the Turing interest group on biodiversity monitoring and forecasting Co-organizer of the Fine-Grained Visual Categorization (FGVC) workshop series at major vision conferences Mac Aodha advises multiple PhD students and postdocs working on computer vision for biodiversity monitoring, 3D understanding, and human-in-the-loop learning. His team has developed practical tools like Whombat (an open-source annotation tool for bioacoustics) and contributed to field-deployed biodiversity monitoring systems. He has served as Area Chair for top conferences including NeurIPS, CVPR, ICCV, and ICML, demonstrating his standing in the computer vision community. His research group collaborates extensively with ecologists at University College London, particularly with Prof. Kate Jones' team, bridging machine learning expertise with ecological domain knowledge. The Vision at Edinburgh group he contributes to focuses on developing practical AI tools that address real-world conservation challenges while advancing fundamental computer vision research.

Chunyan Laiمشاهده پروفایل

دانشیار

• Electric drives
• Motor control
• Power electronics
• +۲ مورد دیگر

Dr. Chunyan Lai is an Associate Professor at the Department of Electrical and Computer Engineering, Concordia University. Her research focuses on electric drives, motor control, power electronics, electrified vehicles, and vehicle-to-grid solutions. She contributes to both graduate and undergraduate education through courses such as Controlled Electric Drives and Hybrid Electric Vehicle Power Systems . Research Emphasis : Electric motor drives and control systems, electrified transportation, power electronics innovations, and energy management strategies. Publications : Specializes in sensorless control techniques for Permanent Magnet Synchronous Motors (PMSM), thermal management in electric machines, and advanced energy trading frameworks for smart grids. PhD Opportunities : The Power Electronics and Energy Research (PEER) Group under Dr. Lai offers positions for developing efficient motor drives for EVs and grid-connected power converters. Collaboration : Industry-adjacent research with requirements for professional communication, patent development, and technical dissemination.

• Mining Engineering
• Raw Materials Processing
• Underground Mining
• +۷ مورد دیگر

Prof. Dr.-Ing. Elisabeth Clausen is a Professor and Director of the Chair and Institute for Advanced Mining Technologies at RWTH Aachen University. She holds key roles in the Specialist Group for Raw Materials and Disposal Technology, serves as a rectorate representative, and leads the Commission for EU Research Funding. Her research spans Underground mining automation Acoustic emission diagnostics Sustainable mining systems Space resource extraction Advanced sensor technologies Her recent publications focus on autonomous mining machinery, underground communication systems, and acoustic emission analysis across 15+ studies from 2013–2025, with particular emphasis on Ultra-wideband positioning Thermographic detection Crack monitoring in planetary gearboxes Explosive atmosphere safety Mineral processing diagnostics Digitalization trends Prof. Clausen contributes to mining education reform through initiatives like CDIO™ and has developed innovative learning spaces in underground mines. She coordinates international educational labs and integrates sustainability into mining engineering curricula, with publications on Adaptive ventilation systems Mining education frameworks Future-proof mineral extraction Entrepreneurial mindset in engineering

Roberto Navigliمشاهده پروفایل

دانشیار

• Natural Language Processing
• Word Sense Disambiguation
• Word Sense Induction
• +۴ مورد دیگر

Roberto Navigli serves as an Associate Professor in the Department of Computer Science at Sapienza University of Rome, conducting pioneering research in Natural Language Processing. He holds editorial leadership positions including Associate Editor of the Artificial Intelligence Journal and membership on the Journal of Natural Language Engineering editorial board. His research program centers on multilingual semantic technologies, with foundational contributions to word sense disambiguation, ontology learning from unstructured text, and large-scale knowledge acquisition systems. Navigli's work bridges theoretical linguistics with practical applications in relation extraction and open information extraction, emphasizing cross-lingual capabilities and resource scalability. Publication analysis reveals a sustained focus on semantic resource development, evolving from early WordNet extensions (2003) to contemporary open knowledge extraction frameworks (2015). This trajectory demonstrates consistent innovation in transforming unstructured text into structured knowledge representations for multilingual applications. Major scientific recognition includes: Marco Cadoli 2007 AI*IA Prize for best doctoral thesis in AI Marco Somalvico 2013 AI*IA Prize for best young AI researcher ERC Starting Grant (2011-2016) for multilingual word sense disambiguation Google Focused Research Award on Natural Language Understanding Navigli directs significant research initiatives funded by competitive grants, including his ERC project and Google collaboration, while providing academic leadership through area chair roles at ACL, WWW, and *SEM conferences. His service as senior program committee member for IJCAI and editorial board positions underscores substantial community impact.

Jay Pujaraمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• Knowledge Graph Construction
• +۵ مورد دیگر

Dr. Jay Pujara is a Research Associate Professor of Computer Science at the University of Southern California (USC) and Director of the Center on Knowledge Graphs. He is also a Principal Scientist at the Information Sciences Institute (ISI) and leads research teams in data science and AI. Ph.D., University of Maryland, College Park (2016) M.S. and B.S. in Computer Science, Carnegie Mellon University Research Interests include artificial intelligence, probabilistic models, knowledge graph construction, statistical relational learning, NLP, and streaming inference. His work focuses on scalable algorithms for big data and uncertainty modeling in dynamic environments. Recent Publications highlight advancements in knowledge graphs, LLM reasoning, and table understanding. Notable topics include non-verbal abstract reasoning , faithful conversational datasets , and KGQA re-ranking . Scientific Awards : SWSA Ten-Year Award (2023), Outstanding Paper (IUI 2019), Top Reviewer (NeurIPS 2018), Best Paper (SRL Workshop 2016) Advising & Grants : Mentored 12+ graduate students, including Ph.D. advisees on topics like causal modeling and neuro-symbolic tasks. Secured NSF funding for table understanding in paleoclimate studies.

Piotr Zwiernikمشاهده پروفایل

دانشیار

• Statistical Computing
• Theoretical Statistics
• High-dimensional Statistics
• +۷ مورد دیگر

Piotr Zwiernik is an Associate Professor in the Department of Statistical Sciences at the University of Toronto's Faculty of Arts and Science, with a cross-appointment in the Department of Mathematics. Currently on leave from the University of Toronto, he is based in Barcelona following his return in July 2025. His academic journey includes a PhD in Statistics from the University of Warwick (2011), research positions at prestigious institutions including Mittag Leffler Institute, IPAM, TU Eindhoven, UC Berkeley, and the University of Genoa, and an Assistant Professorship at Universitat Pompeu Fabra in Barcelona (2016-2021). His research spans the intersection of statistics, mathematics, and computational methods, with particular emphasis on graphical models, covariance matrix estimation, convex analysis, tensors, and algebraic and combinatorial methods in statistics. Zwiernik's work demonstrates a consistent focus on high-dimensional statistics, mathematical statistics, and elegant theoretical frameworks that bridge abstract mathematics with practical statistical applications. His recent publications reveal a deepening exploration of tensor analysis, algebraic statistics, and the geometric properties of statistical models. Zwiernik serves as an associate editor for leading journals including Biometrika, Scandinavian Journal of Statistics, and Algebraic Statistics. His research program includes the development of the GOLAZO R package for asymmetric regularization of log-likelihood in Gaussian graphical models. As an academic leader, he has served as Associate Chair for Research in his department and actively participates in numerous international conferences and workshops, reflecting his significant standing in the statistical community. His recent publications show a strong trend toward algebraic and geometric approaches to statistical problems, with increasing focus on tensor methods, positivity constraints in statistical models, and the theoretical foundations of graphical models. The work demonstrates remarkable continuity in exploring the mathematical structures underlying statistical models while adapting to emerging challenges in high-dimensional data analysis. Zwiernik is committed to mathematical accessibility and education, guided by Federico Ardila's four axioms which emphasize equitable distribution of mathematical potential, joyful mathematical experiences, mathematics as a malleable tool, and treating every student with dignity and respect. He actively seeks PhD students with strong mathematical backgrounds for research at UPF or the Institute of Mathematics of UPC.

David De Roureمشاهده پروفایل

استاد

• Digital Scholarship
• Cybersecurity
• Artificial Intelligence
• +۷ مورد دیگر

David De Roure is Professor of e-Research at the University of Oxford and Academic Director of both the Digital Scholarship initiative and the Laboratory for AI Security Research. He is also an Honorary Research Professor at the Royal Northern College of Music (RNCM), where he serves as Technical Director of the Centre for Practice & Research in Science & Music (PRiSM). His work bridges computer science, digital humanities, cybersecurity, and music through his distinctive interdisciplinary approach. De Roure received his PhD in 1990 supervised by David W Barron and Peter Henderson, with research in Lisp and distributed systems. Prior to joining Oxford in 2010, he was Professor of Computer Science at the University of Southampton and Director of the Centre for Pervasive Computing in the Environment. His career spans multiple institutions and research domains, reflecting his commitment to interdisciplinary work. De Roure's research focuses on new methods of digital scholarship, innovation in knowledge infrastructure, cybersecurity, and computational approaches to music. His work uniquely combines humanities (digital musicology), social sciences (social machines and web science), engineering (Internet of Things), and computer science (distributed systems, AI). A key theme is empowering human creativity through technology rather than replacing humans with AI. He emphasizes co-creation between humans and machines, particularly in music composition where he explores how algorithms can generate fragments for human assembly. His recent publications reveal a strong focus on AI security in IoT systems, digital scholarship methods, and the intersection of music with computational approaches. There's a clear trajectory from foundational work in social machines and web science toward current applications in cybersecurity and music-AI co-creation. His publications consistently bridge technical domains with humanistic inquiry, demonstrating his commitment to interdisciplinary scholarship that addresses real-world challenges. Fellow of the British Computer Society (FBCS) Fellow of the Institute of Mathematics and its Applications (FIMA) Fellow of the Royal Society of Arts (FRSA) Chartered IT Professional (CITP) Turing Fellow at The Alan Turing Institute (2018-2024) De Roure has co-founded three major interdisciplinary initiatives: PETRAS National Centre of Excellence for IoT Systems Cybersecurity (the world's largest socio-technical research center focused on IoT security), the Software Sustainability Institute (dedicated to improving research software), and PRiSM at RNCM. He was Director of the Oxford e-Research Centre from 2012-17 and has led numerous research projects including SOCIAM (The Theory and Practice of Social Machines), FAST (Fusing Audio and Semantic Technologies), and Transforming Musicology. The Laboratory for AI Security Research, which he directs, took its first PhD students in 2024. At Oxford, De Roure chairs the Digital Research Cluster at Wolfson College and oversees the Laboratory for AI Security Research. The PRiSM team at RNCM has produced numerous musical works and performances, including six premieres in New York in 2024. He has been involved in designing gesture recognition software used in many performances and has collaborated on public engagement projects including the Science Together project which released a Hip Hop album. His current work includes exploring Chladni Plates for new musical instrument design and developing algorithmically enhanced instruments.

Kanwaljeet S. Anandمشاهده پروفایل

استاد

• Pediatric Pain and Stress Neurobiology
• Neonatal and Fetal Pain Assessment
• Biomarker Development
• +۳ مورد دیگر

Dr. Kanwaljeet S. Anand is a dual-appointed Professor of Pediatrics (Pediatric Critical Care) and Anesthesiology, Perioperative & Pain Medicine at Stanford University School of Medicine. As director of the Pain/Stress Neurobiology Lab and Jackson Vaughan Critical Care Research Fund, he serves as Editor-in-Chief of Pediatric Research and maintains active membership in Bio-X, MCHRI, and Wu Tsai Neurosciences Institute. Rhodes Scholar with D.Phil from University of Oxford Harvard postdoctoral fellowship and Boston Children's Hospital residency Founded Harmony Health Clinic - Arkansas' largest charitable medical-dental facility A translational researcher with 30+ years of impact, Dr. Anand established the first scientific framework for infant pain perception and developed novel pain assessment methodologies. Current research focuses on: Hair biomarker analysis for stress and social affiliation (cortisol/oxytocin) Machine learning systems for objective pain detection in non-verbal infants Biopsychosocial interventions for stress reduction in disadvantaged youth Neurotoxicity mechanisms of sedatives in developing brains Global NICU opioid usage patterns through the NeoOpioid Consortium His work has yielded over 260 publications and significant advances in: Pediatric pain management protocols Neonatal stress biomarker development Critical care neurobiology insights Community health initiatives AI-driven clinical decision support systems Scientific Recognition 9th Annual 'In Praise of Medicine' Public Address, Erasmus University (2014) Nightingale Excellence Award (2016) Honorary Doctorate from University of Örebro (2019) NIH SBIB-H82 Study Section Chair (2018) Multiple IASP and American Pain Society awards Swedish Academy of Medicine's Nils Rosén von Rosenstein Award (2009) St. Jude Endowed Chairholder (2010) As mentor to Med Scholar Anjali Gupta and advisor to numerous professional bodies, Dr. Anand maintains active clinical leadership in Pediatric Intensive Care while advancing computational approaches to pain detection through collaborations with Stanford's AI researchers.

• Computational Materials Science
• Condensed Matter Physics
• Nanomaterials
• +۶ مورد دیگر

Paul Erhart is a Professor in Condensed Matter and Materials Theory at the Department of Physics, Chalmers University. He received his PhD from Technische Universität Darmstadt in 2006, followed by postdoctoral and staff positions at Lawrence Livermore National Laboratory from 2007, before joining Chalmers in 2011. His research bridges computational physics, materials science, and machine learning to tackle fundamental problems in materials design and characterization. Dr. Erhart's research focuses on computational materials science with particular emphasis on condensed matter physics, nanomaterials, and quantum materials. His work spans from developing computational methods like machine-learned potentials (GPUMD, neuroevolution potentials) to studying fundamental phenomena in perovskites, 2D materials, thermal transport, and plasmonics. He has pioneered approaches connecting simulation with experimental techniques through correlation functions and has made significant contributions to understanding phase transitions, defect physics, and electronic structure in complex materials systems. Analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional computational physics methods. His work increasingly focuses on developing and applying neuroevolution potentials to study thermal properties, phase transitions, and optical phenomena in materials. There's also a clear emphasis on connecting computational results with experimental observations, particularly in neutron scattering, Raman spectroscopy, and plasmonic sensing applications. His research spans fundamental materials physics to applied areas like hydrogen sensing and sustainable materials development. Dr. Erhart has contributed to numerous software packages essential to the computational materials science community, including WulffPack for Wulff constructions, Dynasor for extracting dynamical structure factors, calorine for neuroevolution potential models, and ICET for alloy cluster expansions. His collaborative work spans multiple institutions and disciplines, reflecting the interdisciplinary nature of modern materials research. His contributions to understanding perovskite materials, thermal transport phenomena, and plasmonic systems have established him as a leading researcher in computational materials science.

Matthew Lee Smithمشاهده پروفایل

استاد

• Aging
• Health Behavior
• Chronic Disease Management
• +۶ مورد دیگر

Matthew Lee Smith is a Professor at the Texas A&M School of Public Health , part of Texas A&M University . He is a core faculty member of the Center for Community Health and Aging (CCHA) and the Center for Health Equity and Evaluation Research (CHEER) , and serves as the Director of the Texas Research, Analytics, Innovations, and Research Lab (TRAIL) . Education: Post-Doctoral Fellowship, Health Science Center, Texas A&M University (2010) PhD in Health Education, Texas A&M University (2008) MPH, Indiana University Bloomington (2004) BS in Public Health Education, Indiana University Bloomington (2002) Research Interests: Dr. Smith’s research focuses on aging , chronic disease management , and evidence-based public health interventions . He is particularly interested in health behavior change , health risk assessment , and survey research methodology . His translational work bridges research and practice across healthcare, aging services, and public health systems. He has a strong focus on social determinants of health , including social isolation , caregiving , diabetes self-management , and fall prevention among older adults. His work often targets underserved populations, particularly Black/African American men and rural communities . Scientific Awards: Immunization Neighborhood Champion Award (2024) Responsible Research in Management Award (2023) J. Mayhew Derryberry Award (2022) Consumer Education Program Award (Silver) (2022) Bluebonnet Award (2021) Innovators in Aging Award (2019) Redefining American Healthcare Award (2019) Community ConnecTivity Award (2019) Phillip G. Weiler Award for Leadership in Aging and Public Health (2018) Leadership & Mentorship: Dr. Smith holds leadership roles in several national and state-level initiatives. He is the Co-Director of the Advancing Gerontology through Exceptional Scholarship (AGES) Program and serves on the Steering Committees of the Texas Falls Prevention Coalition , Texas Alzheimer’s Research and Care Consortium , and Texas Social Isolation and Loneliness Coalition . He is also the Director of the Research Scholars & Mentorship Program (RSMP) at the American Academy of Health Behavior. Labs & Centers: He leads the Texas Research, Analytics, Innovations, and Research Lab (TRAIL) , which focuses on developing and evaluating community-based interventions. He is also affiliated with: Center for Community Health and Aging (CCHA) Center for Health Equity and Evaluation Research (CHEER)

• Multimodal Learning
• Multilingual NLP
• Vision-Language Models
• +۴ مورد دیگر

Desmond Elliott is an Associate Professor in the Natural Language Processing section at the Department of Computer Science, University of Copenhagen (UCPH). His research focuses on multimodal and multilingual models with specific emphasis on vision-language integration and tokenization-free NLP approaches. He teaches Bachelor and Master's level courses including Advanced Topics in Natural Language Processing (since 2019), Grundlæggende Data Science (since 2023), and previously Data Science (2021-2023). His research interests center on building and understanding multimodal and multilingual models , particularly exploring vision and language interactions through billion-parameter systems. Current work investigates cultural representation disparities in vision-language models, parameter-efficient captioning, and multimodal distributional semantics across diverse domains including food culture and medical imaging. His methodology emphasizes real-world applicability in non-English contexts and ethical considerations in multimodal systems. Elliott's recent publications (2025) demonstrate leadership in multimodal NLP, with significant contributions to vision-language pretraining, multilingual evaluation frameworks, and clinical NLP applications. His work spans theoretical advancements in model architectures and practical implementations addressing challenges in low-resource languages and domain adaptation. Best Long Paper Award at EMNLP 2021 Best Poster Award at COLING 2019 As an active educator, Elliott contributes to courses on Fair and Transparent Machine Learning and previously taught Information Retrieval. His research collaborations span international institutions with particular focus on European and non-English language contexts, reflecting UCPH's recognition as Europe's #1 institution for HCI research over the past decade.

Borivoje Dakicمشاهده پروفایل

دانشیار

• Quantum Information Theory
• Quantum Foundations
• Quantum Tomography
• +۵ مورد دیگر

Dr. Borivoje Dakic is an Associate Professor at the University of Vienna , affiliated with the Faculty of Physics and the Quantum Optics, Quantum Nanophysics and Quantum Information department. His research spans foundational and applied aspects of quantum theory. Operational reconstruction of quantum formalism Quantum interference as a resource for communication Tomography of large-scale quantum systems Macroscopic quantum phenomena His work includes scalable verification techniques for quantum devices and collaborations with experimental teams like Philip Walther’s and Markus Aspelmeyer’s groups. He received the Marko Jarić Prize (2025) for his contributions. Recent projects focus on diagnostics of quantum devices (FWF BeyondC SFB), information-theoretic foundations of quantum interference (FWF P36994), and local operations in quantum field theory (Cluster of Excellence QuantA). His research on quantum coherence in networks and macroscopic entanglement challenges traditional assumptions about quantum-classical boundaries. Publications emphasize resource-efficient tomography, device-independent verification, and foundational frameworks for quantum statistics and field theory. Teaching: Quantum Information (2025W), Theory in Quantum Optics (2025S), VCQ Summerschool Labs: Dakić Group at University of Vienna