جست‌وجوی استاد و پژوهشگر

Nikola Biller-Andornoمشاهده پروفایل

استاد

• Digitalization of healthcare
• Artificial Intelligence in medicine
• Patient experiences in healthcare
• +۴ مورد دیگر

Professor Nikola Biller-Andorno is a leading academic in biomedical ethics and digital health innovation at the University of Zurich , where she directs the Institute of Biomedical Ethics and History of Medicine and serves as Vice Dean for Innovation and Digitalization at the Faculty of Medicine . Her work bridges cutting-edge technology with ethical frameworks for patient-centered healthcare. Director, Institute of Biomedical Ethics and History of Medicine (WHO Collaborating Centre) Vice Dean for Innovation and Digitalization, Medical Faculty Founding Director, UZH Center for Medical Humanities Chair, PhD program 'Biomedical Ethics and Law' Research Interests focus on digital transformation in healthcare, including ethical implications of AI, patient experience integration via big data, and crisis management frameworks during pandemics. Her scholarship addresses: Digitalization of health systems Algorithmic decision-making ethics Equity in digital health access Scientific Awards include: Commonwealth Fund Harkness Fellowship (2012-2014) Fellowship at Collegium Helveticum (2016-2020) Master of Health Business Administration (2018) Leadership roles in International Association of Bioethics and European Association of Centres of Medical Ethics

• Machine Learning Ethics
• Philosophy of Science
• Interpretability in AI
• +۵ مورد دیگر

Thomas Grote is a Research Fellow at the University of Tübingen's Ethics and Philosophy Lab within the Cluster of Excellence 'Machine Learning: New Perspectives for Science'. His research focuses on philosophical and ethical dimensions of artificial intelligence, particularly interpretability, fairness, and reliability in medical and social contexts. He co-supervises the Carl-Zeiss-Stiftung-funded project 'Certification and Foundations of Safe Machine Learning Systems in Healthcare' and co-organizes the 'Philosophy of Science Meets Machine Learning' conference series. Research Focus Grote's interdisciplinary work bridges philosophy of science and applied AI ethics. Key areas include: Methodological foundations of AI ethics and epistemology Clinical reliability and safety of ML systems Fairness metrics in sociotechnical healthcare systems Interpretability requirements for medical AI Computational psychiatry and evolving mental health frameworks His recent publications demonstrate strong emphasis on healthcare applications, with critical analyses of reliability in foundation models, ethical paradigms for LLMs, and rethinking evaluation methodologies at the epistemology-ethics interface.

• Dental Informatics
• Teledentistry
• Oral Health Policy
• +۴ مورد دیگر

Professor Heiko Spallek is Head of School and Dean at the University of Sydney’s Sydney Dental School, leading the school’s integration with the Faculty of Medicine and Health. He also serves as Academic Lead for Digital Health and Health Service Informatics at the faculty level. His research focuses on advancing dental informatics, teledentistry, and evidence-based practice, while advocating for improved oral health policy and public health initiatives. He holds roles including director at Community Connections Australia and membership in the Charles Perkins Centre. Education: DMD, Dr. med. dent., MSBA(CIS), FACD, FAIDH Leadership: Oversees Sydney Dental School’s academic and clinical programs, emphasizing interprofessional education and digital health innovation. Research interests include leveraging big data and machine learning in dentistry, improving access to oral healthcare through teledentistry, and addressing systemic issues in dental education and policy. He has led projects on laser dentistry applications, dental caries prevention, and healthcare workforce regulation. Notable contributions include the OpenWide conference series, the BigMouth dental data repository, and advocacy for equitable dental funding in Australia. Grants include initiatives on oral hygiene in aged care and analysis of healthcare advertising perceptions. Media engagements highlight his role in public discourse on dental access and policy, including commentary on Australia’s dental crisis and aged care reforms. He actively promotes interdisciplinary collaboration through platforms like the Dental Informatics Online Community. Labs/Teams: Directs the Sydney Dental School’s research programs in informatics and public health, collaborating with national and international networks such as the National Dental PBRN.

Yang Youمشاهده پروفایل

استاد

• Machine Learning
• High-Performance Computing
• Parallel/Distributed Systems
• +۳ مورد دیگر

Yang You is a Presidential Young Professor at the National University of Singapore (NUS), affiliated with the Department of Computer Science under NUS Computing. He holds a PhD in Computer Science from UC Berkeley, advised by Prof. James Demmel. His research focuses on parallel/distributed algorithms, high-performance computing, and machine learning, particularly in scaling deep neural networks on distributed systems and supercomputers. Notably, his team achieved world records in ImageNet and BERT training speeds, with techniques adopted by tech giants like Google and NVIDIA. His optimizers (LARS/LAMB) are included in MLPerf benchmarks. Education - PhD in Computer Science, UC Berkeley - Outstanding Graduate of Tsinghua University (1st rank). Research Interests Yang You’s work spans machine learning system optimization, parallel computing, and distributed training infrastructure. He explores efficient algorithms for large-scale models, including techniques for reducing training time and improving scalability. His contributions emphasize practical implementations that bridge theory and industry applications, such as accelerating diffusion models and optimizing LLM inference. Awards & Honors Lotfi A. Zadeh Prize (2020) IPDPS 2015 Best Paper Award (0.8% acceptance) ICPP 2018 Best Paper Award (0.3% acceptance) ACM/IEEE George Michael HPC Fellowship Siebel Scholar (2020) Forbes 30 Under 30 Asia (2021) Advising & Labs He advises PhD students in cutting-edge research and leads the NUS AI Lab , focusing on advancing AI systems and high-performance computing. His lab collaborates with industry partners to deploy scalable machine learning solutions.

Aaron M. Dollarمشاهده پروفایل

استاد

• Robotics
• Mechatronics
• Robotic Grasping and Manipulation
• +۵ مورد دیگر

Aaron M. Dollar is the Frederick W. Beinecke Professor of Mechanical Engineering at Yale University, affiliated with the Yale Grab Lab. His research focuses on robotics, mechatronics, robotic grasping, and prosthetics, emphasizing adaptive mechanisms and human-robot interaction. He holds a PhD from Harvard University (2008) and degrees from UMass Amherst. Key research areas include dexterous manipulation, underactuated mechanisms, and assistive devices. His work bridges theory and practical applications, with contributions to prosthetic hands, robotic hands, and modular robotics systems. Recipient of prestigious awards: TR35 Innovator (2010), NSF CAREER Award (2010), DARPA Young Faculty Award (2013), and Air Force Young Investigator Award (2011). Developed the Yale MyoAdapt Hand, a single-actuator prosthetic with high functionality. Pioneered methods in real-to-sim transfer, modular lattice printing, and energy-aware robotic exploration. His lab, the Yale Grab Lab, explores robotics, prosthetics, and human motion analysis. Recent projects include autonomous calibration systems (ARC-Calib) and low-cost robotic hardware (RB5 Explorer).

Adegboyega Ojoمشاهده پروفایل

استاد

• Digital Government
• Artificial Intelligence Governance
• Public Sector Innovation
• +۶ مورد دیگر

Dr. Adegboyega Ojo is a Professor at the School of Public Policy and Administration (SPPA), Carleton University , holding the prestigious Canada Research Chair (Tier 1) in Governance and Artificial Intelligence since 2014. His work bridges digital government , AI governance , and smart city development , with a focus on public sector innovation and policy analytics . Research Interests Smart Cities and Urban Digital Infrastructure Open Government Data and Transparency Blockchain Applications in Public Administration AI Ethics and Algorithmic Governance Electronic Participation and Citizen Engagement Publication Trends : His research emphasizes interdisciplinary approaches to digital governance, often involving data-driven policy analysis , smart city frameworks , and open data platform design . Collaborations span institutions in Ireland, Poland, and the U.S., with citations exceeding 5,200. Scientific Awards : Canada Research Chair in Governance and AI (Tier 1) Labs & Teams : Collaborates with the Insight Centre for Data Analytics (Ireland), Delft University of Technology , and United Nations University on projects like OpenGovIntelligence and BOLD (Big and Open Linked Data).

Abdelhak Bentalebمشاهده پروفایل

استادیار

• Computer Networks
• Multimedia Systems
• Video Streaming Optimization
• +۵ مورد دیگر

Dr. Abdelhak Bentaleb is an Assistant Professor in the Department of Computer Science and Software Engineering at Concordia University and founder/director of the IN2GM Lab. His research focuses on optimizing networked multimedia systems using machine learning, with emphasis on video streaming, edge computing, and 5G/6G networks. He holds a PhD from the National University of Singapore (awarded SIGMM and DASH-IF Best Thesis prizes) and completed a postdoctoral fellowship there. Education: PhD in Computer Science, National University of Singapore (2019) Postdoctoral Research Fellowship, National University of Singapore (2019-2022) Research Interests: AI-driven video streaming optimization, low-latency media delivery, network protocols, immersive media technologies, and IoT systems. Current projects explore end-to-end AI-enabled systems for QoE optimization in video delivery using reinforcement learning and deep learning techniques. Awards: SIGMM Award for Outstanding PhD Thesis DASH Industry Forum Best PhD Dissertation Award Multiple DASH-IF Excellence Awards His work includes over 50 publications in top venues (e.g., ACM MMSys, IEEE INFOCOM, USNIX NSDI) and 3 patents. The IN2GM Lab focuses on applied AI/ML solutions for networked systems challenges.

• Information Theory
• Machine Learning
• Artificial Intelligence
• +۴ مورد دیگر

Miguel Rodrigues is a Professor of Information Theory and Processing at University College London's Department of Electronic & Electrical Engineering. He leads the Information, Inference and Machine Learning Lab at UCL and serves as the founder and director of the master programme in Integrated Machine Learning Systems. Rodrigues is also the UCL Turing University Lead and a Turing Fellow with the Alan Turing Institute, the UK National Institute of Data Science and Artificial Intelligence. His academic background includes an undergraduate degree in Electrical and Computer Engineering from the Faculty of Engineering of the University of Porto, Portugal, and a PhD in Electronic and Electrical Engineering from University College London. He has held appointments at prestigious institutions worldwide including Cambridge University, Princeton University, Duke University, and the University of Porto. Dr. Rodrigues's research spans information theory, information processing, and machine learning. His work has attracted over £5 million in funding from competitive national and international funding bodies and resulted in more than 250 publications with over 8000 citations in leading journals and conferences, including top AI venues like NeurIPS, ICML, and ICLR. His recent publications demonstrate a strong focus on multimodal learning, machine learning security, climate modeling with satellite data, and applications of AI in healthcare and precision medicine. His work shows increasing interdisciplinary collaboration across fields from climate science to pharmaceutical engineering. IEEE Communications and Information Theory Societies Joint Paper Award 2011 Fellow of the Institute of Electronics and Electrical Engineers (IEEE) Prize for Merit from the University of Porto Prize Engenheiro Cristian Spratley Prize Engenheiro Antonio de Almeida Fellowships from the Portuguese Foundation for Science and Technology Fellowships from the Foundation Calouste Gulbenkian Dr. Rodrigues has served as Editor for IEEE BITS – The Information Theory Magazine and IEEE Transactions on Information Theory, among other editorial roles. He consults widely in machine learning and AI with government institutions, funding agencies, industry, and startups, and sits on committees responsible for AI standardization such as the BSI Art/1 working group. His leadership extends to directing research labs and educational programs focused on advancing machine learning systems. He leads the Information, Inference and Machine Learning Lab at UCL, which focuses on fundamental aspects of information theory and their applications to machine learning and data processing. The lab works on both theoretical foundations and practical implementations of learning systems.

• Industrial Organization
• Environmental Economics
• Auction Theory
• +۳ مورد دیگر

Paul Klemperer is the Edgeworth Professor of Economics at the University of Oxford, renowned for bridging theoretical economics with practical policy applications. His work has directly influenced major economic initiatives including the Bank of England's Product-Mix Auction and the UK's £22.5 billion 3G spectrum auction, demonstrating exceptional real-world impact in market design and regulation. His educational credentials feature a BA in Engineering (1st Class Honours with Distinction) from Cambridge University and an MBA (Top Student Award) with PhD from Stanford University, reflecting his interdisciplinary foundation. Klemperer's research centers on industrial organization, environmental economics, and auction theory. He co-invented 'strategic complements,' developed consumer switching cost theory, and pioneered supply function analysis for electricity markets. His scholarship consistently translates complex theoretical frameworks into actionable insights for finance, political economy, and climate policy, emphasizing practical applicability without sacrificing academic rigor. Recent publications reveal sustained innovation in auction algorithms, financial stability mechanisms, and equilibrium theory, with growing emphasis on climate economics and banking regulation. His work shows increasing collaboration with policymakers and economists like Jeremy Bulow to address contemporary crises through market design solutions. His scientific recognition includes: Foreign Honorary Member, American Academy of Arts and Sciences Foreign Honorary Member, Argentinian Economic Association Fellow, British Academy Fellow, Econometric Society Fellow, European Economic Association Klemperer has provided critical advisory services to multiple governments, notably designing the UK's mobile spectrum auction and assisting the US Treasury during the 2008 financial crisis. His policy engagement extends to serving on the UK Competition Commission, with research frequently funded through government contracts and central bank partnerships focused on market design challenges. He maintains active academic leadership as past or present Editor/Associate Editor for 12 economics journals, fostering scholarly discourse across industrial organization, finance, and environmental economics.

Ari Schlesingerمشاهده پروفایل

استادیار

• Human-Centered Computing
• Anti-Discriminatory Computing
• Technology Policy
• +۴ مورد دیگر

Ari Schlesinger is an Assistant Professor of Computer Science at the University of Georgia (UGA), directing the Socially Responsible Tech Lab. She holds a PhD from the School of Interactive Computing at Georgia Institute of Technology. Her research focuses on anti-discriminatory computing, technology policy, and equitable sociotechnical systems. She advocates for reducing computing-enabled harm to advance justice in technology. Education : PhD in Human-Centered Computing (HCC), Georgia Tech Affiliations : ACM's U.S. Technology Policy Committee Her work spans Human-Computer Interaction (HCI), Artificial Intelligence (AI), and broader CS applications. Key interests include addressing algorithmic bias, inclusive design, and policy frameworks for ethical computing. She has developed strategies to mitigate discrimination in technical systems through frameworks like anti-discriminatory computing. Awards include the 2021 Outstanding Graduate Teaching Assistant Award and a Best Paper Award at CHI 2018. Her research has been featured in venues like CSCW and CHI, focusing on topics from chatbot ethics to decentralized social networks. Lab : Socially Responsible Tech Lab at UGA Grants/Advising : Advises graduate student Eddie Alexander Gomez Schieber. Active in policy advocacy and academic leadership roles.

Ying Caiمشاهده پروفایل

دانشیار

• AI
• Machine Learning
• Data Science
• +۴ مورد دیگر

Ying Cai is an Associate Professor in the Department of Computer Science at Iowa State University, joining in 2003 after earning his Ph.D. in Computer Science from the University of Central Florida (2002). His research focuses on AI, machine learning, data science, cybersecurity, privacy protection, and database systems. He leads projects funded by the Air Force Research Laboratory, including work on authentication data structures for rank-aware queries, requiring U.S. citizenship and expertise in linear algebra/cryptography. Dr. Cai’s work spans cybersecurity (e.g., adversarial example defense, secure secret sharing), spatio-temporal systems (e.g., traffic risk prediction, check-in time modeling), and healthcare AI (e.g., cervical spine diagnosis with transformers). His publications emphasize practical applications of ML in privacy, security, and distributed systems. Professional roles include Associate Editor for Multimedia Tools and Applications (since 2009), Co-chair for COMPSAC TAIN/NCIW symposium (2014–2017), and TPC Chair for Mobilware 2010. His service includes contributions to INFOCOM, ICDCS, and MDM conferences. Current research opportunities exist for graduate students with strong programming/math skills, particularly in cryptography and linear algebra. He emphasizes interdisciplinary work, such as bridging AI with social sciences via large language models.

• Quantum Physics
• Photonics
• Quantum Computing
• +۷ مورد دیگر

Professor Terry Rudolph is a Professor of Quantum Physics at the Department of Physics within the Faculty of Natural Sciences at Imperial College London. His affiliations include the Quantum Engineering, Science and Technology group, Quantum Optics and Laser Science Group, and The Light Community. His research focuses on quantum-anything, encompassing optical physics, quantum computing, photonics, and related interdisciplinary fields such as nanotechnology and communications technologies. Rudolph’s work emphasizes photonic quantum computing architectures, entanglement generation, and fault-tolerant quantum systems. His recent publications highlight advancements in cluster state generation, photonic multiplexing, and reconfigurable entangling systems. He has contributed to scalable quantum hardware design, including silicon photonic platforms and error-correction protocols. His academic contributions span theoretical and experimental quantum mechanics, with a focus on bridging quantum theory and practical implementation. Notable themes in his research include deterministic teleportation, photonic integrated circuits, and fusion-based quantum computing. He has also engaged in educational initiatives to introduce quantum information science to high-school students. Affiliations: Quantum Optics and Laser Science Group, Quantum Engineering Centre, and The Light Community at Imperial College London.

Allen Huskerمشاهده پروفایل

استاد پژوهشی

• Geophysics
• Seismology
• Planetary Seismology
• +۳ مورد دیگر

Allen Husker is a Research Professor of Geophysics at the California Institute of Technology (Caltech), affiliated with the Seismological Laboratory. He manages the Southern California Seismic Network (SCSN) and the Southern California Earthquake Data Center. Previously, he was a professor at the National Autonomous University of Mexico (UNAM), chairing the Seismology Department, and served as Station Manager for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) seismic stations in Mexico. His academic journey includes a B.S. from the University of Washington (1998), an M.S. from UCLA (2003), and a Ph.D. from Caltech (2008). Research Interests : Husker focuses on geophysical observations of crustal structure, slow-slip events, and seismic network analysis. His work bridges subduction zones (e.g., Mexico) and transform boundaries (e.g., Southern California). He explores planetary seismology, comparing Earth with the Moon and Mars. Recent studies include DAS technology for moonquake detection and seismic monitoring in the Guerrero seismic gap. Publications Trends : His 2024 work emphasizes DAS applications, Mexico’s San Andreas Fault dynamics, and socio-technical aspects of earthquake early warning (EEW) in Mexico. Earlier research (2020s) delves into slow-slip mechanisms, crustal anisotropy, and fault system dynamics in Mexico. He also investigates moonquake behavior and lunar regolith effects. Awards : No explicit scientific awards listed. Advising & Grants : Advises graduate students like Guillermo González (UNAM) and Yuri Tamama (Caltech). Former students include Francesco Civilini (Research Space Scientist) and Jiuxun Yin (Research Geophysicist). Collaborates widely, including with Jennifer Jackson on lunar seismology. Labs/Teams : Leads the SCSN and collaborates with UNAM’s Seismology Department. Engaged with the CTBTO and international seismological networks.

Daniel Chenمشاهده پروفایل

استادیار

• Business Analytics
• Operations Management
• Machine Learning
• +۶ مورد دیگر

Daniel Chen is an Assistant Professor of Business Analytics at the Carroll School of Management, Boston College. His research focuses on strategy in online platforms, leveraging machine learning and structural estimation to analyze two-sided markets and gig economy dynamics. He holds a Ph.D. in Operations Management from the Wharton School (University of Pennsylvania), advised by Gad Allon, and degrees from the University of Southern California, including an M.S. in Mathematical Finance and a B.S. in Economics/Mathematics. His work addresses strategic interactions between platforms and users, with a particular emphasis on data-driven solutions. Research Interests: Chen’s research spans gig economy operations, causal inference with machine learning, algorithmic transparency, and network-based rating systems. He collaborates with industry partners like driver analytics companies to study worker behavior, platform efficiency, and policy impacts. His methodologies combine theoretical modeling with empirical analysis, addressing real-world challenges in platform design and regulatory frameworks. Awards: Finalist, 2023 INFORMS Behavioral Operations Management Best Working Paper Award Labs/Teams: Collaborates with a driver analytics company to analyze gig economy datasets, contributing to both academic research and practical policy recommendations. His work bridges theoretical insights with actionable strategies for platforms and regulators.

Armando Rungiمشاهده پروفایل

استاد

• International Economics
• Industrial Organization
• Applied Econometrics
• +۵ مورد دیگر

Armando Rungi is a Professor of Economics at IMT School for Advanced Studies in Lucca, Italy. He teaches econometrics, international economics, and macroeconomics to PhD students. In addition to his academic role, he serves as a research fellow at the Observatory on Foreign Firms in Italy and has consulted for the European Commission, OECD, and UNCTAD on international trade and investment issues. His research focuses on international economics, industrial organization, applied econometrics, and statistical learning. Recent work emphasizes the organization of multinational enterprises, global value chains, labor markets, cyber-resilience of supply chains, and the integration of econometric and machine learning tools for policy evaluation and predictive analysis. His recent publications explore topics such as the impact of trade agreements, multinational enterprises' strategies, and the application of machine learning in predicting firm behaviors and evaluating economic policies. A common theme is the analysis of supply chain resilience, corporate ownership structures, and the effects of globalization on firms' competitiveness and productivity. No scientific awards are mentioned in the provided information. No advisees or grant details are listed in the text. His professional activities include consulting roles and research collaborations. He is affiliated with the Observatory on Foreign Firms in Italy, which evaluates the impact of multinational companies and strategies to attract foreign investment in Italy.