جستجوی استاد راهنمای دانشگاهی

Esther Dufloمشاهده پروفایل

استاد

• Development Economics
• Poverty Alleviation
• Health Economics
• +۴ مورد دیگر

Esther Duflo is the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics at the Massachusetts Institute of Technology (MIT), where she is affiliated with the Department of Economics within the School of Humanities, Arts, and Social Sciences. She co-founded and co-directs the Abdul Latif Jameel Poverty Action Lab (J-PAL) and holds the position of Chaire, Pauvreté et politiques publiques at the Collège de France. Duflo also serves as President of the Paris School of Economics, demonstrating her significant international influence in economic policy and research. Her educational background includes first degrees in history and economics from Ecole Normale Superieure, Paris, followed by a Ph.D. in Economics from MIT in 1999. This strong foundation has enabled her to become one of the most influential economists of her generation. Duflo's research focuses on understanding the economic lives of people living in poverty, with the explicit aim of informing effective social policy design and evaluation. Her work spans critical areas including health, education, financial inclusion, environmental sustainability, and governance. What distinguishes her approach is the rigorous application of randomized controlled trials to evaluate development interventions, bringing scientific precision to poverty alleviation efforts. Her research methodology has revolutionized how economists approach development questions, moving beyond theoretical models to evidence-based policy recommendations. Her scholarly output demonstrates remarkable breadth and impact, with publications spanning from technical academic papers to influential books for general audiences. Duflo's work consistently bridges the gap between academic research and practical policy applications, with recent publications addressing contemporary challenges including climate change adaptation, pandemic response, and economic policy for hard times. Her research trends reveal a deepening commitment to translating complex economic concepts for broader audiences while maintaining scholarly rigor. Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (2019, with Abhijit Banerjee and Michael Kremer) Princess of Asturias Award for Social Sciences (2015) A.SK Social Science Award (2015) Infosys Prize (2014) John Bates Clark Medal (2010) MacArthur 'Genius Grant' Fellowship (2009) Member of the National Academy of Sciences (2017) Duflo has supervised numerous graduate students and collaborated extensively with researchers worldwide through J-PAL, which has grown into a global network conducting field experiments across multiple continents. Her grant portfolio includes substantial funding from major foundations and government agencies supporting large-scale development research. Beyond traditional academic advising, Duflo has mentored a generation of development economists through J-PAL's training programs and field research opportunities. Her primary institutional home is the Abdul Latif Jameel Poverty Action Lab (J-PAL), which she co-founded at MIT. J-PAL has grown into a major research center with offices worldwide, connecting academic researchers with policymakers to ensure that program evaluations inform real-world decisions. Duflo also leads research teams at the Collège de France and the Paris School of Economics, creating a transatlantic network focused on evidence-based poverty reduction strategies.

Stephen Lichtمشاهده پروفایل

دانشیار

• Marine Robotics
• Biologically Inspired Propulsion
• Nonlinear Attitude Control
• +۵ مورد دیگر

Stephen Licht is an Associate Professor of Ocean Engineering and Graduate Director at the University of Rhode Island's College of Engineering, where he directs the Robotics Laboratory for Complex Underwater Environments (R-CUE). His research focuses on developing maritime robots capable of operating in dynamic and unpredictable environments through biologically inspired propulsion, distributed pressure sensing, model-based optimal control, and compliant underwater manipulation technologies. Ph.D. in Oceanographic and Mechanical Engineering from MIT/WHOI Joint Program (2008) B.S. in Mechanical Engineering from Yale University (1998) Former Senior Research Scientist at iRobot and Senior Robotics Engineer at Vecna Robotics Current Research Affiliate with MIT Department of Mechanical Engineering Former Visiting Faculty at Libera Università di Bolzano (2019-2020) Dr. Licht's research spans marine robotics with emphasis on biologically inspired propulsion systems that provide high authority and bandwidth thrust, nonlinear attitude control for maneuvering in dynamic conditions, compliant underwater manipulation technologies, and unmanned aerial monitoring of coastal structures. His work bridges mechanical engineering principles with oceanographic applications to create more capable underwater robotic systems that can operate in complex marine environments. His recent publications demonstrate a strong trend toward soft robotics applications for deep-sea exploration, with particular focus on jamming grippers and neutrally buoyant manipulation systems. The research also shows increasing integration of additive manufacturing techniques for field-deployable solutions and computational methods for autonomous systems operating in challenging marine environments. His work spans fundamental control theory, mechanical design, and practical field applications. Dr. Licht has secured significant research funding as both Principal Investigator and Co-Principal Investigator from major organizations including the Office of Naval Research, NOAA, NSF, and various university collaborations. His grants focus on advancing unmanned underwater vehicle technology, soft robotics for deep-sea applications, and coastal monitoring systems. Active mentor to numerous graduate and undergraduate students in Ocean Engineering Successful track record of student placements at organizations including Jaia Robotics, Scripps Institution of Oceanography, FORSSEA Robotics, and government research labs Collaborates with researchers at MIT, WHOI, University of Connecticut, University of Maine, and international institutions Licht leads the R-CUE lab which develops innovative solutions for underwater robotics challenges, with particular expertise in biomimetic propulsion, soft robotics for deep-sea applications, and autonomous systems for environmental monitoring. The lab maintains strong industry connections with OceanGate Inc. and FabNewport, and engages with local educational institutions through outreach programs with Roger Williams Middle School.

Niki Kilbertusمشاهده پروفایل

استادیار

• Machine Learning
• Causal Inference
• Ethics in AI
• +۵ مورد دیگر

Prof. Niki Kilbertus is an Assistant Professor at the Technical University of Munich (TUM) in the Department of Informatics, and Group Leader at Helmholtz AI. His research focuses on causal machine learning, ethical AI systems, and applications in healthcare, climate science, and dynamical systems. He earned his PhD from the University of Cambridge (2020) and has held positions at DeepMind, Google, and Amazon during his studies. His research interests include causal discovery, fairness in AI, counterfactual reasoning, and integrating physics-based constraints into neural networks. Key contributions include foundational work on fair machine learning (e.g., avoiding discrimination through causal models) and developing methods for causal inference in complex systems like healthcare and climate modeling. Recent work emphasizes generative models for causal interventions, robust treatment effect estimation, and physically consistent neural differential equations. He leads a large interdisciplinary group with over 20 students and postdocs working on projects funded by Helmholtz Association, ERC, and industry collaborations. Notable awards include the Leopoldina Prize for Young Scientists (2024) and membership in the Junge Akademie. His lab maintains active partnerships with ELLIS, MCML, and the Zuse Institute Berlin.

Hassan Qudrat-Ullahمشاهده پروفایل

استاد

• Sustainability
• Global/Climate Change
• System Dynamics
• +۳ مورد دیگر

Dr. Hassan Qudrat-Ullah is a Professor at the School of Administrative Studies, York University, and Coordinator of the Certificate in Logistics Management. He holds a PhD in Decision Sciences from NUS Business School and completed a post-doctoral fellowship at Carnegie Mellon University. His research focuses on dynamic decision making, system dynamics modeling, energy planning, and interactive learning environments. He teaches courses on quantitative methods, logistics, and decision analysis, informed by global industry experience across 20+ countries. Research interests include sustainability, climate change, systems thinking, and educational applications of decision sciences. He serves as Editor-in-Chief of the International Journal of Complexity in Applied Science and Technology and is a member of IEEE, DSI, and the International System Dynamics Society. His work has been published in Energy , Decision Support Systems , and others. Key projects include studies on 'structured-debriefing in dynamic decision making' and renewable energy policies in Africa. His recent articles (2023–2025) address AI integration in energy governance, system dynamics for supply chain resilience, and education for sustainability. Hassan advocates for systems thinking in K-12 education and enjoys traveling (visited 129 countries) and bird-watching.

Maria Craigمشاهده پروفایل

استاد

• Childhood Diabetes
• Type 1 Diabetes
• Virology and Diabetes
• +۴ مورد دیگر

Professor Maria Craig is a distinguished academic and researcher at the University of New South Wales, Faculty of Medicine & Health, specializing in childhood diabetes research. She holds a prominent position as a Professor with extensive contributions to the field of pediatric endocrinology and diabetes, particularly focusing on type 1 diabetes in children. Professor Craig's educational background includes: MB BS from the University of Melbourne MMedSc(ClinEpid) from the University of Newcastle PhD from the University of Sydney FRACP (Fellow of the Royal Australasian College of Physicians) Professor Craig's research primarily focuses on childhood diabetes, with special emphasis on prediction and prevention of type 1 diabetes. She has a significant interest in the association between viruses and type 1 diabetes, collaborating with the Virology Research Group at Prince of Wales Hospital (POWH). Together with Professor Bill Rawlinson, she leads the viral theme for the multicentre ENDIA study (endia.org.au). As principal investigator for the CoRD trial, she is conducting a world-first phase 1 study using autologous cord blood for prevention of type 1 diabetes in children with islet autoimmunity. Additionally, she serves as principal investigator for the Australasian Diabetes Data Network (ADDN). Her research portfolio also encompasses the epidemiology of various forms of childhood diabetes (type 1, type 2, cystic fibrosis related diabetes and monogenic diabetes) and diabetes complications, in collaboration with Professor Kim Donaghue at the Children's Hospital at Westmead. Professor Craig's extensive publication record, including over 361 journal articles, demonstrates her leadership in advancing our understanding of childhood diabetes. Her recent work shows increasing focus on early detection methods, risk prediction models, technological interventions for diabetes management, and the complex interplay between viral infections and autoimmune diabetes development. She has been instrumental in developing clinical practice guidelines through her role as co-editor of the International Society for Pediatric and Adolescent Diabetes (ISPAD) guidelines. Professor Craig has received numerous prestigious awards recognizing her contributions to pediatric endocrinology and diabetes research: Australian Paediatric Endocrine Group Young Investigator's Award (1997) Asia Pacific Paediatric Endocrine Society Clinical Teaching Award (2008) Lifetime Honorary Member, Caring and Living as Neighbours (2013) Australian Diabetes Society Jeff Flack Diabetes Data Award (2019) Australian Paediatric Endocrine Group Norman Wettenhall Award for Research and Innovation (2019) Throughout her career, Professor Craig has demonstrated exceptional leadership in professional societies, having served as former president/treasurer of the Australasian Paediatric Endocrine Group (APEG) and currently as Scientific Convenor of the Asia Pacific Paediatric Endocrine Society Fellows school. Her work with the ENDIA study and Australasian Diabetes Data Network represents significant collaborative research efforts involving multiple institutions across Australia and internationally. Her principal investigator roles for major studies indicate substantial research funding support. Professor Craig leads several important research initiatives including the ENDIA study, the CoRD trial, and the Australasian Diabetes Data Network. These programs involve multidisciplinary teams of researchers, clinicians, and support staff working collaboratively to advance understanding and treatment of childhood diabetes. Her work at the intersection of virology and diabetes represents a unique and innovative approach to understanding the environmental triggers of type 1 diabetes.

Romain Lopezمشاهده پروفایل

استادیار

• Single-cell omics
• Spatial transcriptomics
• Deep generative models
• +۵ مورد دیگر

Romain Lopez is an Assistant Professor of Computer Science and Biology at New York University, with a joint appointment in the Courant Institute of Mathematical Sciences and the Department of Biology. He will be joining NYU in September 2025, bringing expertise at the intersection of machine learning and computational biology. Prior to joining NYU, he was a Postdoctoral Fellow at Genentech and Stanford Medicine from 2021 to 2025, working with Jonathan Pritchard and Aviv Regev. Dr. Lopez received his educational training at prestigious institutions: PhD in Computer Science (2021) from the University of California, Berkeley, advised by Mike Jordan and Nir Yosef M.S. in Applied Mathematics (2016) from École polytechnique, Palaiseau, France Dr. Lopez's research focuses on developing machine learning methods to understand biological systems at the cellular level. His work bridges computational techniques with biological applications, particularly in single-cell and spatial omics analysis. He pioneered probabilistic approaches for single-cell analysis with scVI and co-developed scvi-tools, now widely adopted tools in the field. His research spans deep generative models, causal inference, perturbation modeling, and representation learning for biological data. His publication record demonstrates a consistent trajectory of innovation in computational biology, with recent work focusing on spatial biology, disentangled representations of cellular perturbations, and causal modeling of cellular responses. He has made significant contributions to the field of single-cell analysis, developing methods that help scientists interpret complex cellular data and predict how cells respond to various perturbations. Dr. Lopez has received numerous honors and awards for his research: Best Paper Award from the ICML Workshop on AI for Science (2024) Best Paper Award Honorable Mention from the AAAI Conference on Artificial Intelligence (2021) Best Student Poster Award from the ICML Workshop on Computational Biology (2019) UC Berkeley EECS Departmental Graduate Fellowship (2016) Carnot Foundation Fellowship (2016) Monahan Foundation Fellowship (2016) French National Defence Medal, Bronze Echelon (2014) At NYU, Dr. Lopez will lead the Biological Machine Learning group, which develops probabilistic machine learning methods to uncover biological mechanisms governing cellular behavior and disease. His lab focuses on creating tools that transform complex cellular data into biological insights, with applications in understanding cancer, immune responses, and fundamental cellular processes. His work has significant implications for precision medicine and drug discovery.

Roger Giner-Sorollaمشاهده پروفایل

استاد

• Moral Psychology
• Social Psychology
• Emotion Research
• +۷ مورد دیگر

Roger Giner-Sorolla is Professor of Social Psychology at the University of Kent's School of Psychology, where he has been a faculty member since 2001 after completing his PhD at New York University in 1996. He served as Editor-in-Chief of the Journal of Experimental Social Psychology from 2016-2022 and currently leads a Leverhulme Foundation grant examining moral heroism across professions. His academic journey includes a postdoctoral fellowship at the University of Virginia and has established him as a leading figure in social and moral psychology. Professor Giner-Sorolla's research focuses on the social role of emotions, particularly moral emotions including self-condemning emotions (guilt and shame) and other-condemning emotions (anger, contempt, and disgust). His work extends to intergroup apologies, dehumanization, emotionally driven prejudice, and collective moral roles, with a notable side interest in the ironic enjoyment of music and aesthetic experiences. He is a strong advocate for transparency in scientific reporting, having written extensively on improved reporting guidelines, pre-registration, and open science practices. Analysis of his recent publications reveals a consistent focus on moral psychology with expanding interdisciplinary reach. His work bridges traditional social psychology with emerging areas including cross-cultural emotion research, replication science, and historical memory. The trend shows increasing attention to methodological rigor while maintaining core interests in emotion and morality, with growing emphasis on practical applications in conflict resolution and intergroup relations. Fellow of the Association for Psychological Science Member of Rising Stars selection committee (2023-2024) Promising Scholars Award (University of Kent, 2006) Vacation Research Scholarship (Wellcome Trust, 2005) Multiple ESRC grants totaling over £400,000 European Science Foundation Workshop Award (2004) Professor Giner-Sorolla has supervised an impressive number of PhD students, with 17 doctoral candidates listed in the documentation including both current and past students. His grant portfolio demonstrates significant research impact with funding from major organizations including ESRC, Wellcome Trust, and Leverhulme Foundation. His supervision style appears to encourage students to pursue research that aligns with his core interests in moral emotions while allowing exploration of novel applications and contexts. While the documentation doesn't specify laboratory or research team structures, his extensive collaborative work suggests leadership of research groups focused on moral psychology and emotion research. His numerous international collaborations and invited workshops indicate an active research program with global reach, likely involving multiple research teams working on interconnected projects related to his core interests in moral psychology and scientific methodology.

• Decision Making
• Team Cognition
• Team Effectiveness
• +۳ مورد دیگر

Shanique Brown serves as Assistant Professor of Management at the Zicklin School of Business, City University of New York (CUNY), where she investigates cognitive processes impacting organizational team dynamics and decision-making. Her research bridges industrial-organizational psychology with practical applications in extreme environments. Her academic foundation includes: Ph.D. in Industrial-Organizational Psychology from DePaul University M.A. in Industrial-Organizational Psychology from Southern Illinois University, Edwardsville B.Sc. in Psychology from the University of the West Indies Dr. Brown's research centers on decision-making mechanisms and team cognition within organizational contexts, with specialized focus on extreme environments like space missions. She examines how cognitive styles, working memory, and team composition influence performance in isolated, confined, and high-stakes settings. Her work integrates psychological theory with actionable frameworks for optimizing team effectiveness across virtual and physical workspaces. Analysis of her publication history reveals evolving expertise in team science, particularly regarding virtual team leadership, polycultural organizations, and NASA-relevant analog research. Recent work emphasizes selection-optimization-compensation models for team performance and psychosocial factors in extreme environments, demonstrating consistent contribution to organizational psychology literature. Her scientific recognition includes: Editorial Fellowship from Group Dynamics (2022) Wayne State University Faculty Accessibility Fellowship (2022) Teaching Innovation Development Excellence Award (2020) Faculty Teaching Award (2020) University Research Grant (2019) Robert A. Daugherty Memorial Award (2011) Dr. Brown actively collaborates on NASA-funded research through the Human Research Program, developing crew composition models for long-duration space missions. She serves on Baruch College's PhD Admissions and Interdisciplinary Business Major committees while maintaining leadership roles in the Society of Industrial-Organizational Psychology, including Task Force Chair and Conference Committee positions. Her grant work focuses on translating team dynamics research into operational frameworks for extreme environments. She leads interdisciplinary collaborations with NASA researchers and international scholars on projects including virtual escape room studies for team performance assessment and CREWS (Crew Recommender for Effective Work in Space) development, demonstrating commitment to solving real-world team challenges in high-consequence settings.

Osman Yağanمشاهده پروفایل

استاد پژوهش

• Machine Learning
• Data Science
• Network Science
• +۷ مورد دیگر

Osman Yağan is a Research Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with affiliate faculty status in the School of Computer Science. He is also a core member of CyLab Security and Privacy Institute. Prior to joining CMU in 2013, he was a Postdoctoral Research Fellow at CyLab. He holds a Ph.D. in Electrical and Computer Engineering from the University of Maryland (2011) and a B.S. from Middle East Technical University (2007). His research focuses on modeling, analysis, and optimization of computing systems, leveraging applied probability, network science, data science, and machine learning. Key areas include multi-armed bandits, resilient machine learning, contagion processes in networks, and cybersecurity. Research Interests include Machine Learning, Data Science, Network Science, Cybersecurity, and Robustness in Cyber-Physical Systems. He has advised numerous students, including current PhD candidates Yurun Tian, Orkun İrsoy, and Ishank Juneja, as well as notable alumni such as Mansi Sood (now at MIT) and Jun Zhao (Assistant Professor at Nanyang Technological University). Key Awards include the CIT Dean's Early Career Fellowship, IBM Academic Award, and Best Paper Awards at ICC 2021, IPSN 2022, and ASONAM 2023. His work spans theoretical contributions (e.g., contagion models in multi-layer networks) and applied research (e.g., mitigating cascading failures in power systems). He leads or co-leads grants from ONR, NSF, and ARO, focusing on resilient machine learning, network robustness, and pandemic modeling.

• Infectious Diseases
• Geriatric Infectious Diseases
• Antimicrobial Stewardship
• +۷ مورد دیگر

Vincent Quagliarello, MD, is Professor of Medicine in the Department of Infectious Diseases at Yale School of Medicine, where he also serves as Clinical Chief of Infectious Diseases and Vice Chair for Education and Academic Affairs in the Department of Internal Medicine. His research focuses on infections among older adults, with particular expertise in endocarditis, meningitis, and antimicrobial stewardship in geriatric populations. Dr. Quagliarello has been an NIH R01-funded principal investigator studying infections in older adults and received an NIH K07 Academic Leadership Award to mentor postdoctoral trainees and junior faculty. His publication record demonstrates consistent focus on antimicrobial use in elderly patients, particularly those with advanced cancer, nursing home residents, and end-of-life care scenarios. His research has significantly contributed to understanding appropriate antimicrobial therapy in geriatric populations and the management of infections in complex elderly patients. Scientific Awards: Clinical Teacher Award (2011) from Infectious Diseases Society of America Leah Lowenstein Award (2007) from Yale School of Medicine Department of Internal Medicine Teacher of the Year (1998, 1990) Laureate Award (1997) from American College of Physicians (CT Chapter) Bohmfalk Teaching Prize (1997) from Yale School of Medicine Dr. Quagliarello has served as an educational leader at Yale, directing the Internal Medicine Clerkship, the Yale Infectious Diseases Fellowship program, and creating the Department of Medicine Research in Residency Program. His clinical work spans the spectrum of infectious diseases with a special focus on public health impact.

Noah D. Goodmanمشاهده پروفایل

دانشیار

• Computational models of cognition
• Probabilistic programming languages
• Natural language semantics and pragmatics
• +۶ مورد دیگر

Noah D. Goodman is Associate Professor of Psychology and Computer Science, and Linguistics (by courtesy) at Stanford University. He directs the Computation & Cognition Lab (CoCoLab) at Stanford, where he leads research on computational models of cognition, integrating logic and probability. His work spans cognitive psychology, linguistics, and computer science. Primary Appointment: Psychology Department By Courtesy: Computer Science Department and Linguistics Department Director: Computation & Cognition Lab (CoCoLab) Goodman's research focuses on computational models of cognition, with particular interest in probabilistic approaches to understanding human thought. His work integrates logic and probability to model concepts, categorization, intuitive theories, causal learning and reasoning, social cognition (including reasoning about others' goals, beliefs, and actions), cognitive development (especially acquisition of abstract knowledge), and natural language semantics and pragmatics. He has made significant contributions to the development of probabilistic programming languages as tools for cognitive modeling. His recent publications demonstrate a strong trend toward integrating probabilistic modeling with linguistic theory and social cognition. The articles span computational cognitive science, natural language processing, and artificial intelligence, with a consistent theme of using probabilistic frameworks to understand complex cognitive phenomena. Many papers explore how humans make inferences under uncertainty across different domains. Goodman teaches several courses at Stanford including Language and Thought (Psych 132), Computation and Cognition: the Probabilistic Approach (Psych 204/CS 428), Foundations of Cognition (Psych 205), and Introduction to Cognitive Science. He has also led seminars on topics ranging from natural and artificial intelligence to the science of meditation.

Antonio Rangelمشاهده پروفایل

استاد

• Neuroeconomics
• Decision Neuroscience
• Behavioral Economics
• +۴ مورد دیگر

Antonio Rangel is the Bing Professor of Neuroscience, Behavioral Biology, and Economics at the California Institute of Technology (Caltech), where he also serves as Head Faculty in Residence. He is a faculty member in the Division of Humanities and Social Sciences (HSS) with research focusing on the computational and neurobiological basis of value-based decision-making. Dr. Rangel received his educational training at prestigious institutions: B.Sc. from Caltech in 1993 M.S. from Harvard University in 1996 Ph.D. in 1998 Professor Rangel's research lies at the intersection of neuroscience, economics, and psychology, with a focus on understanding how the brain makes decisions. His work investigates the neural mechanisms underlying value computation, choice processes, self-control, and social decision-making. Using a multidisciplinary approach that combines functional magnetic resonance imaging (fMRI), eye-tracking, computational modeling, and behavioral experiments, his lab has made significant contributions to the field of neuroeconomics. His research has revealed how value signals are represented in the brain, how attention influences choice, and the neural basis of self-control failures. Professor Rangel has pioneered methods for studying decision processes with high temporal resolution using eye-tracking data, demonstrating how fixation patterns relate to value computations and choice outcomes. His work spans from theoretical frameworks of value-based decision-making to practical applications in behavioral public economics. Professor Rangel's work has been recognized with prestigious awards: 2019 NOMIS Distinguished Scientist Award 2018 Fellow of the Association for Psychological Science As an academic leader, Professor Rangel has mentored numerous students and researchers who have gone on to make their own contributions to neuroscience and economics. His lab, the Rangel Neuroeconomics Laboratory at Caltech, serves as a hub for interdisciplinary research, bringing together students and scholars from neuroscience, economics, psychology, and computer science. The lab has received significant funding to support its research on the neural basis of decision-making, including support from the NOMIS Foundation. The Rangel Neuroeconomics Laboratory is equipped with state-of-the-art facilities including fMRI analysis capabilities, eye-tracking systems, and computational resources for modeling decision processes. The lab fosters a collaborative environment where researchers apply methods from experimental economics and cognitive neuroscience to unravel the complexities of human decision-making.

Oana Cocarascuمشاهده پروفایل

مدرس ارشد

• Argument mining
• Explainable AI
• Machine learning
• +۵ مورد دیگر

Dr. Oana Cocarascu is a Senior Lecturer in Artificial Intelligence at the Department of Informatics, Faculty of Natural, Mathematical & Engineering Sciences, King's College London. She holds a PhD and MEng in Computing (Artificial Intelligence) from Imperial College London and conducts applied research focusing on how artificial intelligence can be deployed to support real-world applications, with machine learning and natural language processing as core components of her work. Her research interests span argument mining, explainable AI, machine learning, natural language processing, and symbolic reasoning. She is particularly focused on developing AI systems that can provide transparent, accountable, and ethical decision-making processes. Her work addresses critical challenges in bias mitigation, fairness metrics, fact verification systems, and argumentation-based explanations for complex AI decisions. Analysis of her recent publications (2023-2025) reveals a strong focus on fairness in AI systems, with particular attention to individual fairness metrics and nuanced evaluation frameworks. She has made significant contributions to fact verification systems, especially in multimodal contexts involving charts and tabular data. Her work increasingly integrates argumentation theory with natural language processing to create explainable AI systems that can justify their decisions through structured reasoning. Dr. Cocarascu leads an EPSRC-funded project titled 'A framework for evaluating and explaining the robustness of NLP models' (2024-2027) and is actively involved in the Natural Language Processing Group at KCL. Her research fingerprint shows strong activity in argumentation (100%), decision-making (74%), artificial intelligence (50%), explainable AI (39%), and bias mitigation (35%). She has contributed to numerous high-impact publications in top venues including ACL, EMNLP, AAAI, and the Journal of Artificial Intelligence Research, with a particular focus on making AI systems more transparent, accountable, and aligned with human values. Her work intersects with UN Sustainable Development Goals, particularly those related to reducing inequality and building resilient infrastructure.

Felipe Csaszarمشاهده پروفایل

استاد

• Strategic Management
• Artificial Intelligence
• Organizational Behavior
• +۳ مورد دیگر

Felipe Csaszar is a Professor of Strategy and Chair of the Strategy Department at the University of Michigan's Ross School of Business. His research focuses on decision structures' impact on innovation, financial performance, and social outcomes, with particular attention to cognitive frameworks, organizational processes, and AI's role in decision-making. He holds a PhD and MA from the Wharton School, University of Pennsylvania. Education: PhD in Strategy, University of Pennsylvania (2009) MA in Strategy, University of Pennsylvania (2007) Research Interests: Strategic decision-making under AI integration Cognitive and structural drivers of innovation Organizational decision processes and design Formal modeling and empirical strategy research Editorial Roles: Senior Editor, Strategy Science and Management Science Former Editor, Organization Science Co-editor, Handbook of AI and Strategy Professional Experience: Prior role: Assistant Professor at INSEAD Previous career: CEO of an internet startup and Head of Research at an asset management firm Labs/Teams: Leading the Strategy Science division at INFORMS Co-chair of the SMS Behavioral Strategy division

Nuno Conceiçãoمشاهده پروفایل

استادیار

• Clinical Psychology
• Psychotherapy Integration
• Personality Disorders
• +۳ مورد دیگر

Nuno Conceição serves as an Invited Assistant Professor at the Faculty of Psychology, University of Lisbon (FP-UL), where he has taught since 2011. His clinical work focuses on adults with complex trauma, personality disorders, and structural dissociation of the personality. He earned his BA (1999), MA (2006), and Ph.D. in Clinical Psychology (2011) from FP-UL, following his Abitur at the German School of Lisbon (1994). BA: FP-UL (1999) MA: FP-UL (2006) Ph.D.: FP-UL (2011) His research centers on Psychotherapy Integration, examining General Change Processes, Case Formulation, Emotional Change in Trauma Therapy, and Ecological Dimensions in Psychotherapy. He investigates how experiential processing facilitates change in personality pathology through integrative clinical decision-making. Key trends in his 2016-2023 publications reveal consistent focus on transdiagnostic mechanisms, termination processes, and musical interventions for emotional processing, primarily using qualitative case studies to advance psychotherapy integration frameworks. No scientific awards were documented in the source material. Conceição has supervised over 50 master's research projects and designed the Integrative Perspectives in Psychotherapy curriculum. He directs the Paradigmatic Complementarity Lab—a practice-based research network using process coding to train clinical skills—and serves as a therapist trainer/supervisor at OneSession.org. Supervision: >50 master's projects Curriculum Development: Integrative Perspectives in Psychotherapy Professional Training: OneSession.org The Paradigmatic Complementarity Lab drives his research agenda, utilizing process-coding methodologies to study change mechanisms in complex trauma and personality disorders within real-world clinical settings.