Andreas Vlachos is a Professor of Natural Language Processing and Machine Learning at the Department of Computer Science and Technology, University of Cambridge, and holds the Dinesh Dhamija Fellowship at Fitzwilliam College. His research spans dialogue modeling, automated fact-checking, imitation learning, semantic parsing, biomedical text mining, and trustworthiness in AI systems. PhD in Computer Science, University of Cambridge (supervised by Ted Briscoe and Zoubin Ghahramani) Lecturer at University of Sheffield Postdoctoral roles at UCL, University of Cambridge (NLIP group, Stephen Clark), and University of Wisconsin-Madison (Mark Craven) Current research focuses on evaluating and mitigating biases in language models, advancing fact-checking methodologies, and improving model robustness through interpolation, reinforcement learning, and causal reasoning. His work integrates natural logic, knowledge graphs, and multimodal evidence for verification tasks. Recent publications address uncertainty quantification, temporal planning benchmarks, and ethical framing of NLP artifacts. Grants from ERC, EPSRC, Facebook, Google, and the Alan Turing Institute fund his research team. Collaborations include Sebastian Riedel, Stephen Clark, and Mark Craven. Key projects explore disinformation detection, long-form generation, and confidence calibration in AI systems.
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Mohammad Saifur Rahman is the Daniels School Chair in Management and a Professor of Management Information Systems at the Mitch Daniels School of Business, Purdue University. Previously, he was an Associate Professor at the Haskayne School of Business, University of Calgary. His academic journey includes significant leadership roles such as co-chairing the Conference on Information Systems and Technology (CIST) in 2013 and serving as president of the INFORMS eBusiness Society in 2014. Currently, he serves as an associate editor for both Management Science and Information Systems Research (ISR). Ph.D. in Management Information Systems, Krannert School of Management, Purdue University (2008) MBA in Management Information Systems, Southern Illinois University (2004) BS in Computer Science, Southern Illinois University (2002) Rahman's research primarily focuses on the economic implications of digital transformations. His work examines how digitization affects consumer behavior, market structures, and business strategies across various industries. He investigates the value of digital traces in driving consumer behavior and improving decision-making, particularly in omnichannel retail environments. His research on the sharing economy has revealed important insights about economic disparities, showing how platforms like Airbnb provide economic benefits to predominantly white neighborhoods while failing to generate similar spillover effects in predominantly Black or Hispanic neighborhoods. His recent publications reveal a consistent focus on the intersection of technology, economics, and social impact. Rahman's work frequently examines how local market structures interact with digital platforms to create or exacerbate economic inequalities. His research spans multiple disciplines including information systems, economics, marketing, and operations management, with a particular emphasis on empirical studies using real-world data from major companies like Walmart and Cisco. CICP Faculty Commercialization Award (2020) INFORMS Sandy Slaughter Early Career Award (2018) World's Top 40 Business School Professors Under 40 by Poets and Quants (2017) Jay N. Ross Young Faculty Scholar Award (2015) Dean's Award for Outstanding Research Achievement (University of Calgary, 2014) Rahman has secured substantial research funding from organizations including Social Sciences and Humanities Research Council (SSHRC), Adobe Systems ($50,000 grants in 2017 and 2020), Trask Innovation Fund ($21,218), and NSF I-Corps ($50,000). He has advised numerous PhD students and collaborated with industry partners to translate research into practical applications. Rahman co-founded RightFit Analytics, a precision health analytics solution that utilizes AI to learn success patterns in healthcare. He has organized significant academic events including the Krannert-Walmart Data Dive (believed to be the first data dive on a college campus) and the Dawn or Doom Data Dive in cooperation with Cisco. Rahman actively engages with industry through consulting and collaborative research projects. His work with Walmart, Cisco, and other major corporations demonstrates his ability to bridge academic research with practical business applications. He has been particularly active in studying how AI and big data analytics can be leveraged to improve business decision-making while addressing potential negative consequences like algorithmic bias and economic inequality.
Lexing Xie is a Professor in Computer Science at the Australian National University. He leads the ANU Computational Media Lab ( http://cm.cecs.anu.edu.au ) and the ANU Integrated AI Network. His work focuses on the intersection of machine learning, social media analysis, and multimedia understanding. Dr. Xie's research broadly focuses on innovative design and use of machine learning algorithms, especially on large-scale graph data and collective behaviour. His recent work spans several key areas: Popularity in social media -- understanding, predicting, and optimization Multimedia knowledge graphs, vision and language integration Humanising machine intelligence through better understanding of social dynamics His publications reveal a strong trend toward understanding information diffusion patterns in social media, particularly through visual content. He has made significant contributions to the study of visual memes, popularity prediction using point processes, and multimodal learning that connects vision with language. His work often bridges theoretical machine learning with practical applications in social media analysis. Dr. Xie has received recognition for his research, including an Honourable Mention at CSCW 2019 for his work on attention flow in online video networks. His research has been supported by collaborations with major institutions including IBM Research and Columbia University. As an advisor, Dr. Xie has mentored numerous students who have gone on to contribute significantly to publications in top-tier conferences. His lab, the ANU Computational Media Lab, serves as a hub for interdisciplinary research connecting computer science with social sciences.
Tapio Schneider is the Theodore Y. Wu Professor of Environmental Science and Engineering at the California Institute of Technology. His research focuses on atmospheric dynamics across Earth and other planets, climate modeling innovations, and geophysical turbulence analysis. He contributes to the Climate Modeling Alliance (CliMA) and develops advanced computational tools for climate prediction. Albert-Ludwigs-Universität Freiburg (Vordiplom, 1993) Princeton University (M.Sc. 1997, Ph.D. 2001) University of Washington, Seattle (Visiting Graduate Student, 1994-1995) His research spans climate dynamics , atmospheric turbulence , and AI-enhanced climate modeling , addressing challenges in cloud dynamics, extreme weather patterns, and planetary climate systems. Current work emphasizes hybrid machine learning-physical models and computational acceleration for high-resolution simulations. Recent publications highlight trends in AI integration for climate science, with applications in hydrology , cloud microphysics , ocean circulation , snowpack modeling , and climate tipping points . His team develops open-source tools like ClimateMachine for GPU-accelerated simulations. Scientific Recognition: Fellow, American Geophysical Union (2022) Rosenstiel Award (2019) World Economic Forum Young Scientist (2012) David and Lucile Packard Fellow (2005-2010) Alfred P. Sloan Research Fellow (2004-2006) Tapio leads climate dynamics research at Caltech, directs the Linde Center for Global Environmental Science (2011-2012), and serves as Editor for the Journal of Advances in Modeling Earth Systems . His group collaborates with NASA Jet Propulsion Laboratory (2016-2024) and Google Research (2022-present).
Pieter van Goorمشاهده پروفایل
پژوهشگر ارشد
- Robotics
- Control Theory
- Equivariant Systems Theory
- +۵ مورد دیگر
Pieter van Goor is a Research Fellow at the Australian National University (ANU), affiliated with the School of Engineering and the Systems Theory and Robotics (STR) group. He holds a PhD in Control Theory (completed 2022) and dual bachelor's degrees (BEng/BSc, 2018). His research focuses on equivariant systems theory, state estimation, and robotics applications. Key contributions include equivariant observer design, Lie group-based control, and geometric data fusion. Education: Bachelor of Engineering (Research & Development) (Honours) in Mechatronics (ANU, 2018) Bachelor of Science in Mathematics (ANU, 2018) PhD in Control Theory (ANU, 2022) Research Interests: Equivariant systems theory, nonlinear control, robotics applications, state estimation on Lie groups, sensor fusion, and geometric control methods. His work emphasizes symmetry exploitation in filter design and observer construction for systems with inherent geometric structures. Grants & Collaborations: Active collaborations include work with Robert Mahony and institutions like the IEEE. Research spans theoretical frameworks (e.g., equivariant filters) and applied systems (e.g., ArduPilot autopilot, event cameras). Labs/Teams: Member of the Systems Theory and Robotics (STR) group at ANU, focusing on advanced control theory and robotics.
Yu-Ru Linمشاهده پروفایل
دانشیار
Yu-Ru Lin is an Associate Professor at the School of Computing and Information, University of Pittsburgh, and serves as Research & Academic Director at the Institute for Cyber Law, Policy and Security (Pitt Cyber). She leads the Pitt Computational Social Dynamics Lab (PICSO Lab) and holds secondary appointments in Political Science, Computer Science, and the Intelligent Systems Program. PhD in Computer Science from Arizona State University Postdoctoral research at Harvard University and Northeastern University Her research focuses on computational approaches for: Networked social dynamics High-dimensional social information summarization Trust and distrust propagation Misinformation detection Policy diffusion analysis Recent publications span 2014-2020, covering: Social media crisis response Graph visualization techniques Policy diffusion patterns Misinformation mitigation Temporal topic modeling Scientific support includes: National Science Foundation (NSF) awards Minerva/ONR funding AFOSR grant for distrust modeling DARPA Understanding Group Biases program As director of PICSO Lab, she leads interdisciplinary research teams on: Digital accountability Urban mobility patterns Health informatics via crowdsourcing Trust-influence dynamics
Roberto Berjón Gallinas is a Professor at the School of Computer Science, Deusto University. His research focuses on semantic technologies, internet of things, and data integration, with a strong emphasis on mobile applications and open data. He leads two research groups: ICS (Innovación en Ciencias Sociales) MARATON (Mobile applications, internet of things, data processing, semantic technologies, open data) His recent work includes developing smart tracking frameworks for IoT workflows and digital twins, event-driven architectures for IoT systems, and semantic integration solutions for university research. His projects often bridge technical innovation with practical applications in collaborative e-learning and spatial analytics. Key trends in his publications highlight advancements in IoT frameworks , semantic technologies for data integration, and real-time systems using BLE and open data. These works frequently intersect with collaborative e-learning , university transparency , and adaptive mobile platforms .
Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.
Khurram Azizمشاهده پروفایل
مدرس ارشد
Dr. Khurram Aziz is a Senior Instructor in the Faculty of Computer Science at Dalhousie University , Halifax, Canada. He is actively engaged in teaching and research, with a focus on optical networks, data center interconnects, and network performance modeling. Education: PhD in Electrical Engineering, Vienna University of Technology, Austria (2008) MSc in Electrical Engineering, National University of Singapore (2003) BSc (Hons) in Electrical Engineering, University of Engineering and Technology, Lahore, Pakistan (1998) His research interests include optical packet and burst switched networks , optical interconnects for data centers , analytical modeling and simulation , and network routing and switching . He has contributed extensively to the design and performance evaluation of scalable optical switches and hybrid switching systems. The recent publications reflect a strong trend in data center optical networks , focusing on performance, blocking probability, signal degradation, and architectural classification. His work bridges theoretical modeling with practical simulation frameworks, such as CloudNetSim++ in OMNeT++, contributing to cloud and high-capacity network research. Dr. Aziz has no listed scientific awards in the provided text. He teaches several core computer science courses including CSCI 2141: Intro to Database Systems , CSCI 3171: Network Computing , CSCI 3132: Object Orientation and Generic Programming , and CSCI 3120: Operating Systems . There is no mention of graduate student supervision or external research grants. He has co-authored book chapters in major handbooks on data centers and switched systems. Dr. Aziz has not listed any formal lab or research team affiliations in the provided content.
- Cognitive Neuroscience
- Neurophysiology
- Psychology
- +۴ مورد دیگر
Belkis Ezgi Arikan is a researcher at Justus Liebig University Giessen , affiliated with the Department of Psychology and Sports Science . Her work focuses on sensorimotor integration, tactile suppression, and neural mechanisms underlying action-outcome monitoring. She collaborates with Prof. Dr. Fiehler and Dr. Voudouris on project A4 (Predictive somatosensory processing during voluntary movements). Department: Psychology and Sports Science Collaborators: Dr. Dimitris Voudouris, Prof. Dr. Katja Fiehler Her research investigates: How the brain processes self-generated vs. externally generated sensory feedback Neural correlates of tactile suppression networks Role of cerebellum and angular gyrus in temporal recalibration Modulation of BOLD responses during action monitoring Recent publications reveal trends in predictive coding , sensorimotor recalibration , and neural suppression mechanisms across tactile, visual, and multisensory domains. Her work employs neuroimaging techniques like fMRI and behavioral paradigms to study self-motion perception and feedback processing. She contributes to understanding how the brain distinguishes self-initiated from external sensory events, with implications for motor learning and perceptual timing mechanisms.
Xiaowei Jiaمشاهده پروفایل
استادیار
Xiaowei Jia is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh. He holds a Ph.D. from the University of Minnesota (supervised by Prof. Vipin Kumar) and B.S./M.S. degrees from the University of Science and Technology of China (USTC) and SUNY Buffalo. His research focuses on integrating scientific theory with machine learning to address societal and environmental challenges, such as climate modeling, hydrology, and fairness in AI. Education: Ph.D., University of Minnesota (2020) M.S., State University of New York at Buffalo B.S., University of Science and Technology of China (USTC) Research Interests: Knowledge-Guided Machine Learning Spatiotemporal Data Mining Fairness in AI for Social Good Applications in Environmental Science and Healthcare Publications showcase his work on physics-integrated neural networks, spatiotemporal modeling (e.g., water temperature prediction), and fairness-aware algorithms. His work has been recognized with Best Paper awards at SIAM SDM (2022, 2023). Awards include the Best Applied Data Science Paper Award at SIAM SDM in 2022 and 2023. He teaches advanced machine learning courses, emphasizing theory integration with real-world applications.
Professor Lisa Strohschein holds dual roles as a Professor in the Sociology Department and Director of Undergraduate Programs at the University of Alberta's Faculty of Arts. Her research focuses on family dynamics and health inequalities, employing longitudinal methodologies to analyze large datasets. She teaches courses on health sociology, mental illness, and socialization, emphasizing sociological perspectives on health distribution and care systems. Her research interests include the interplay between socioeconomic factors and mental health, gender disparities in marital outcomes, and generational shifts in parenting practices. She has published extensively on topics like teen pregnancy correlates, poverty dynamics, and the mental health implications of family structures. Strohschein has received the 2019-20 Killam Annual Professorship and serves as Editor-in-Chief of Canadian Studies in Population, a peer-reviewed journal focusing on demographic research. She also contributes to policy through roles like membership in Statistics Canada's Demographic Statistics Advisory Committee and past presidency of the Canadian Population Society. Her scholarly work bridges theoretical frameworks (life course, stress process theory) with methodological rigor, often using growth curve models and competing risks analysis. Current research trends emphasize cross-national comparisons and applied policy relevance, particularly in understanding how family transitions impact health across the life course.
Nicholas J. Klein is an Associate Professor and Director of Undergraduate Studies in the Department of City and Regional Planning at Cornell University's College of Architecture, Art, and Planning. His research focuses on transportation equity, urban mobility, and marginalized communities' travel behaviors. Klein holds a Ph.D. from Rutgers University, an M.S. from the University of Pennsylvania, and a B.S. from Cornell University. He has taught at Columbia University, Temple University, and Pratt Institute. His work emphasizes how socioeconomic factors and life events influence transportation choices, particularly among low-income populations. Key research areas include car ownership dynamics, location affordability, and the intersection of transportation policy with social justice. Klein has led projects funded by the U.S. Department of Transportation and Cornell's Institute for the Social Sciences, exploring car donation programs' impacts on disadvantaged families. Grants: Principal investigator for studies on car donation programs (2018–2020) and immigrant access to public transit (2010–2013). Awards: Journal of Planning Education and Research Top Reviewer Award (2018). Teaching: Courses include quantitative methods for public policy analysis. His publications address topics such as transportation affordability, generational car ownership trends, and the role of life experiences in shaping travel behavior. Klein frequently presents at the Transportation Research Board Annual Meeting and contributes to high-impact journals like Transport Policy and Journal of Transport and Land Use .
Colin Jonesمشاهده پروفایل
دانشیار
Colin Jones is an Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL) in the Automatic Control Laboratory, School of Engineering. He earned his BASc and MASc in Electrical Engineering and Mathematics from the University of British Columbia (1994-2002) and a PhD in Control Theory from the University of Cambridge (2002-2005). Prior to EPFL, he was an assistant professor there and a senior researcher at ETH Zürich. Current role: Director of the Robotics, Control, and Intelligent Systems Doctoral Program at EPFL Research focus: Optimization-based and model predictive control (MPC) for renewable energy systems, green energy management, and data-driven control methods His recent work (2023-2025) spans high-speed predictive control , smart grid optimization , and physically consistent neural networks , with applications to buildings, hovercrafts, and power systems. He has secured an ERC Starting Grant for his research on optimal control of building networks. Publications include over 200 papers in journals like Automatica , IEEE Transactions , and Energy and Buildings . Notable article trends include distributed optimization , data privacy in energy systems , and nonlinear MPC for autonomous vehicles . Scientific Awards : ERC Starting Grant for optimal control of building networks Advising : Supervises 10 current PhD students and has advised 19 past PhD students, including Alessandretti Andrea and Diwale Sanket Sanjay. Grants and projects emphasize smart energy systems , predictive demand response , and nonlinear control .
Daniel Abadi is the Darnell-Kanal Professor of Computer Science at the University of Maryland, College Park. He leads the Data Systems Lab at Maryland (DSLAM) and is widely recognized for his groundbreaking contributions to database system architecture and implementation. Previously, he was a faculty member at Yale University where he received the Provost's Teaching Prize. Abadi's research primarily focuses on database system architecture, particularly at the intersection with scalable and distributed systems. He is best known for developing the storage and query execution engines of the C-Store prototype (a column-oriented database system commercialized by Vertica and later acquired by Hewlett-Packard), HadoopDB research (commercialized by Hadapt and acquired by Teradata), and deterministic distributed transactional systems like Calvin (currently being commercialized by Fauna). His work bridges theoretical innovation with practical industrial impact. Analysis of his recent publications reveals a consistent trajectory toward solving fundamental challenges in distributed database systems. His research has evolved from foundational work on column-stores and hybrid database architectures to cutting-edge innovations in geo-replicated transactions, concurrency control mechanisms, and the integration of machine learning with database systems. The trend shows increasing focus on practical implementations that address real-world scalability and performance challenges in large-scale data processing environments. ACM Fellow Churchill Scholarship recipient NSF CAREER Award winner Sloan Research Fellowship recipient VLDB Best Paper Award winner Two VLDB Test of Time Awards (for C-Store and HadoopDB) 2008 SIGMOD Jim Gray Doctoral Dissertation Award 2013-2014 Yale Provost's Teaching Prize 2013 VLDB Early Career Researcher Award Professor Abadi has successfully mentored several PhD students, most notably Alexander Thomson and Jose Falerio, both of whom won the prestigious SIGMOD Jim Gray Doctoral Dissertation Award for their work under his supervision. His research has been generously supported by multiple NSF grants including BIGDATA awards and other funding mechanisms that have enabled significant advances in database technology. He actively collaborates with industry partners, with several of his research projects leading directly to commercial products. At the University of Maryland, Abadi directs the Data Systems Lab at Maryland (DSLAM), which focuses on developing innovative database technologies that address contemporary challenges in data management. The lab's research spans distributed transaction processing, database architecture, and the integration of database systems with emerging computing paradigms. Notable projects include SLOG (Serializable, Low-latency, Geo-replicated Transactions), which eliminates traditional tradeoffs in distributed database design, and ongoing work in deterministic database systems that provide strong consistency guarantees without sacrificing performance.