جستجوی استاد راهنمای دانشگاهی

Deepak Ganesanمشاهده پروفایل

استاد

• Networking and Distributed Systems
• Mobile and Sensor Systems
• Human-Computer Interactions
• +۳ مورد دیگر

Deepak Ganesan is a Professor at the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. His research focuses on low-power sensing and communication, networked systems, and machine learning applied to pervasive health monitoring and societal challenges. PhD, Computer Science, University of California, Los Angeles (2004) MS, Computer Science, University of California, Los Angeles (2000) BTech, Computer Science, Indian Institute of Technology, Madras (1998) Ganesan's work bridges wireless sensor networks, smart textiles, and healthcare applications. He designs ultra-low-power wearable devices for tracking health signals like drug use, smoking, and cognitive performance, often integrating machine learning for robust detection. His research emphasizes societal impact, particularly in aging and Alzheimer's care through the Massachusetts AI and Technology Center for Connected Care (MassAITC) and the Center for Personalized Health Monitoring (CPHM). Recent publications highlight innovations in edge-cloud collaboration, fabric-based sensors, and longitudinal health analytics. His NIH-funded MD2K Center for Excellence and affiliations with the Center for Data Science and Computational Social Science Institute further underscore his interdisciplinary approach. ACM Fellow NSF CAREER Award (2006) IBM Faculty Award (2008) UMass Junior Faculty Fellow (2008) UMass Lilly Teaching Fellow (2009) Best Paper at CHI 2013 Best Paper Runner-up at Mobicom 2014 Honorable Mentions at Ubicomp 2013 Ganesan leads the SENSORS: Wireless Sensor Networks Group and contributes to global initiatives like the Internet of Battlefield Things. His work spans academic research, industry partnerships, and policy development in AgeTech and digital health.

Mohammadreza Karamadمشاهده پروفایل

استادیار

• Electrochemistry
• Heterogeneous Catalysis
• Material Science
• +۳ مورد دیگر

Mohammadreza Karamad is an Assistant Professor in the School of Sustainable Energy Engineering at Simon Fraser University (SFU), with a joint appointment in the Sustainable Energy Engineering department. His research focuses on computational materials discovery, leveraging quantum-mechanical methods (e.g., DFT) and machine learning (ML) to design advanced energy materials for clean technologies like hydrogen storage and catalysis. He holds a Ph.D. from the Technical University of Denmark (DTU) and completed postdoctoral research at Stanford University. His academic background includes leadership roles in the CMD Lab (Computational Materials Discovery), where he explores novel materials for electrochemical energy conversion processes. Key research areas include electrochemistry, heterogeneous catalysis, and material science, with a particular emphasis on CO2 reduction, ammonia synthesis, and sustainable energy storage solutions. Dr. Karamad collaborates with industry and academic partners to advance materials discovery through high-throughput computational screening and AI-driven approaches. He actively seeks motivated students (undergraduate and graduate) to join his research program, focusing on developing next-generation energy materials. His lab is located in room B8220, and he can be reached at mkaramad@sfu.ca. Notable technical contributions include pioneering work on transition metal nitrides for CO2 reduction, single-atom catalysts for ammonia synthesis, and machine learning frameworks for predicting material properties. His research bridges fundamental theory with practical applications, addressing global challenges in sustainable energy and environmental technology.

• Quantitative Modeling
• Machine Learning
• Big Data Analytics
• +۶ مورد دیگر

Associate Professor Steven Lu is a faculty member at the University of Sydney Business School, serving as Deputy Head of Discipline (Education). He holds a PhD in Marketing from the University of Toronto, an MA in Economics from York University, and a BA from Nankai University. His research focuses on quantitative modeling, machine learning, and big data analytics applied to digital economy challenges such as digital retailing, search advertising, and blockchain. He co-directs the Consumer Insights Research Group and is affiliated with the Sydney Institute of Agriculture. Dr. Lu has published in top journals including Marketing Science , Production and Operations Management , and Journal of Retailing . His awards include the CNS Vithala Rao Award, ANZMAC Best Paper Awards (2022-2024), and the 2021 Vice Chancellor's Teaching Award. He teaches courses on machine learning in marketing, marketing research, and new product development. He leads research grants such as 'The Era of Mobile Payment' (2021) and 'Digital Transformation of Food Sensory Quality' (2017). His advising focuses on topics like neural recommender systems, e-coupon effectiveness, and heterogeneous treatment effects analysis.

• Radiotherapy
• Medical Imaging
• Clinical Imaging
• +۳ مورد دیگر

Dr. Mark Gardner is a Research Fellow in Clinical Imaging at the ACRF Image X Institute, part of the University of Sydney's Sydney School of Health Sciences and Faculty of Medicine and Health. His work focuses on advancing radiation therapy and medical imaging technologies, with particular emphasis on improving treatment accuracy and patient comfort. Gardner holds a PhD from Flinders University, completed in collaboration with the Medical Device Research Institute, and has held research roles at the Cystic Fibrosis Airway Research Group (CFARG). His current projects include the Nano-X radiation therapy device and the Remove the Mask initiative , which aims to eliminate immobilization masks in head and neck cancer treatments. Gardner is affiliated with organizations like the IEEE Engineering in Medicine and Biology Society and the American Association of Physicists in Medicine. Research interests span radiation oncology, translational research in medical imaging, and device innovation. His work integrates advanced imaging techniques (e.g., synchrotron X-rays, cone-beam CT) with machine learning and wearable sensors to address challenges in respiratory therapy and tumor targeting. Notable contributions include developing real-time motion tracking for radiation therapy and improving mucociliary transport measurements. Awards: FameLab 2020 State Finalist, 2018 Medtech e-Challenge Winner, 2017 3MT Runner-Up Grants/Projects: Nano-X radiation therapy development, Remove-the-Mask surface-guided system Collaborations: Industry partnerships, multi-institutional research networks Gardner advises Chen Cheng on real-time head/neck motion monitoring during radiation therapy. His lab contributes to open-source tools and preclinical imaging advancements, bridging engineering and clinical oncology.

Ran Spieglerمشاهده پروفایل

استاد

• Economic Theory
• Behavioral Economics
• Political Economy
• +۳ مورد دیگر

Ran Spiegler is a Professor of Economics at both Tel Aviv University and University College London (UCL). He holds a PhD in Economics from Tel Aviv University (1999). His research focuses on economic theory, behavioral economics, and bounded rationality, with notable contributions to understanding decision-making under flawed causal reasoning, narrative-driven political and economic dynamics, and market behaviors influenced by limited consumer rationality. Spiegler has held roles including Member at the Institute for Advanced Study (Princeton, 2000-2001) and Prize Research Fellow at Nuffield College, Oxford (1999-2000). Education: PhD in Economics, Tel Aviv University (1999) Affiliations: Professorships at Tel Aviv University (2009–present) and UCL (2006–present) Research Interests: Spiegler’s work explores how bounded rationality shapes economic outcomes, including consumer decision-making, market competition, and the role of narratives in political mobilization. He has authored influential books like Bounded Rationality and Industrial Organization (2011) and The Curious Culture of Economic Theory (2024), which critique and expand economic theory’s methodologies. Recent Articles: His recent work examines topics such as false narratives in politics, monopolistic data practices, and competitive markets with imperfectly discerning consumers. These studies highlight interdisciplinary applications of economic theory to modern challenges like algorithmic transparency and platform economics. Awards: Prize Research Fellow, Nuffield College, Oxford (1999–2000) Grants & Labs: While specific grants are not detailed, his research is funded through institutional affiliations. He collaborates widely, with notable co-authors like Kfir Eliaz and Yair Antler.

Song Maمشاهده پروفایل

استاد

• Innovation Economics
• Entrepreneurship
• Financial Economics
• +۷ مورد دیگر

Song Ma is a Professor of Finance and Entrepreneurship at Yale School of Management and a Faculty Research Fellow at the National Bureau of Economic Research (NBER). He is also an affiliated faculty member at Yale Law School Center for the Study of Corporate Law and Yale SOM Program on Entrepreneurship, having joined Yale SOM Faculty in 2016. His educational background includes: PhD in Finance from Duke University's Fuqua School of Business (2016) BA in Economics from Zhejiang University (2010) Professor Ma's research primarily focuses on innovation economics, entrepreneurship, financial economics, AI, and big data. His work extends to corporate strategy, industrial organization, antitrust, labor, and business law. He has made significant contributions to understanding how innovation interacts with financial markets, corporate strategy, and competition policy, particularly through his influential 'Killer Acquisitions' paper which has been cited in Congressional antitrust reports and lawsuits against major tech companies. His recent publications demonstrate an interdisciplinary approach combining finance, economics, and data science methodologies. Many papers examine the intersection of innovation and corporate finance, with increasing incorporation of AI and big data techniques as seen in his video analysis research. His work shows evolution from traditional finance topics toward more policy-relevant research with real-world impact on antitrust regulation and innovation policy. Professor Ma has received numerous prestigious awards: 2023 Best Paper Award, China International Conference in Finance 2022 Best Paper on Competition Economics, Association of Competition Economics 2022 Jerry S. Cohen Award for Antitrust Scholarship 2021 GARP Best Paper in Risk Management Award 40 Under 40 Best Business School Professors by Poets & Quants (2021) Robert F. Lanzillotti Prize for Antitrust Economics (2020) Jensen Prize for Best Paper on Corporate Finance (2019) In teaching, Professor Ma delivers popular courses including 'Entrepreneurial Finance,' 'Venture Capital and Private Equity,' and 'Finance and the Society.' He co-organizes WEFI (Workshop on Entrepreneurial Finance and Innovation), a bi-weekly virtual research forum. His research has been referenced by major regulatory bodies worldwide including the FTC, EU Competition Commission, and UK Competition and Markets Authority, and featured in leading media outlets like Wall Street Journal and New York Times. Professor Ma actively incorporates new data science technologies into his empirical economic research, focusing on unstructured data analysis and machine learning applications.

Elinor Benamiمشاهده پروفایل

استادیار

• Environmental Economics
• Development Economics
• Agricultural Economics
• +۳ مورد دیگر

Elinor Benami is an **Assistant Professor** in the Agricultural and Applied Economics Department at Virginia Tech. She holds affiliations with the VT Remote Sensing & Global Change Center, the Center for Advanced Innovation in Agriculture, and Stanford’s RegLab. Her research focuses on environmental and development economics, leveraging satellite imagery and machine learning to enhance disaster financing and environmental compliance. She earned a B.A. from UNC Chapel Hill, a Ph.D. from Stanford University, and a postdoc at UC Davis. **Research Interests**: Climate risk management, agricultural resilience, remote sensing applications, and policy design for sustainable agriculture. Current projects include NASA-funded work on Moroccan irrigation and drought financing, and evaluating U.S. environmental compliance using AI. **Awards/Grants**: Led a $650K NASA Harvest grant, part of a $80M climate-smart agriculture initiative, and received the VT Early Career Scholarly Impact Award Nominee. Active in policy, including advising the EPA on environmental compliance algorithms. **Teaching**: Courses include 'Remote Sensing in Social Sciences', 'Climate Risk Management', and 'Environmental and Sustainable Development Economics'. Mentors students at all levels, emphasizing computational skills and social impact. **Affiliations**: NASA Harvest, VT Remote Sensing IGEP, and the Alliance for Climate-Smart Agriculture. Collaborates with global institutions on drought financing and satellite data applications.

Ping Yangمشاهده پروفایل

استاد

• Cybersecurity
• Information Security
• AI-Based Security
• +۷ مورد دیگر

Ping Yang is a Professor and Associate Director for Research and Graduate Programs in the School of Computing at Binghamton University (SUNY). She holds a Ph.D. in Computer Science from Stony Brook University, an ME from the Chinese Academy of Sciences, and a BS from Zhongshan University. Her research focuses on cybersecurity, AI-based security, virtual machine security, privacy policy analysis, and formal methods. She directs the Center for Information Assurance and Cybersecurity and coordinates cybersecurity programs at both undergraduate and graduate levels. Education: BS in Computer Science, Zhongshan University ME in Computer Science, Chinese Academy of Sciences MS and PhD in Computer Science, State University of New York at Stony Brook Research Interests: Dr. Yang's work spans information and systems security, security in virtualized computing, access control mechanisms, privacy policies, and formal methods for security verification. Her projects include blockchain-based provenance storage, real-time anomaly detection in workflows, and privacy-preserving virtual machine migration. She has led NSF-funded initiatives on security in cloud environments and scientific workflows. Awards: Not explicitly listed in the provided materials. Advising & Grants: Advised over 30 PhD/Master’s students and contributed to grants including NSF Scholarship for Service and GenCyber programs. Her team develops tools like RBAC-PAT for access control analysis. Labs/Teams: Leads the Center for Information Assurance and Cybersecurity and collaborates on projects involving secure data workflows and blockchain applications in scientific research.

Marcel Dettlingمشاهده پروفایل

مدرس

• Predictive Analytics
• Applied Statistics
• Data Mining
• +۶ مورد دیگر

Dr. Marcel Dettling is a Group Lead in Data Analysis and Statistics at the ZHAW School of Engineering , focusing on predictive analytics, applied statistics, and complex data analysis. He also serves as a Lecturer at ETH Zurich , teaching advanced statistical methods. Education : PhD in Mathematics (2000-2004), ETH Zurich Postdoc in Applied Statistics (2004-2006), Johns Hopkins University His research spans predictive analytics (regression, classification, time series), data mining, and applications in health economics, transportation safety, social sciences , and business analytics . Recent work includes pharmaceutical cost group analysis for Swiss healthcare and predictive maintenance for marine vessels. Selected publications highlight his expertise in flight trajectory modeling , deep learning error mitigation , and statistical frameworks for rehabilitation finance . His projects address diverse fields like crowdworking in nursing, energy optimization for shipping, and customer behavior prediction.

Swati Aggarwalمشاهده پروفایل

استاد

• Artificial Intelligence
• AI in Health and Medicine
• AI in Society
• +۶ مورد دیگر

Swati Aggarwal is a Professor in Artificial Intelligence at the Faculty of Logistics, Molde University College (HiMolde). Her research focuses on AI applications in healthcare, ethics, cognitive development, and neural networks. She holds a PhD in Neutrosophic Neural Networks, a Master's in Information Technology, and a Bachelor's in Computer Science and Engineering. Previously, she was a Marie Curie Postdoc Fellow at NTNU, working on AI models for cognitive assessment in infants (AIM_COACH project). Research Interests - AI in Health/Medicine - Ethics in AI and Societal Impact - EEG/BCI for Cognitive Assessment - Machine Learning and Deep Learning Publications Her recent work spans AI ethics, BCI applications, adversarial attacks, and healthcare diagnostics. Notable contributions include EEG-based infant perceptual monitoring (2025) and malaria detection via EfficientNet (2023). She also explores cross-lingual adversarial robustness and blockchain in hospitality systems. Labs/Teams - ABC-AI: Applied, Basic, and Conscientious AI Group - Virtual Technologies and Learning Research Group

Laura Albertمشاهده پروفایل

استاد

• Operations Research
• Public Safety
• Emergency Management
• +۴ مورد دیگر

Laura Albert is a Professor of Industrial & Systems Engineering at the University of Wisconsin-Madison and former David H. Gustafson Department Chair (2021-24). She serves as a Fellow of AAAS and IISE, and previously held the INFORMS presidency. Her research focuses on optimizing public-sector systems, with applications in critical infrastructure protection, emergency response, and cybersecurity. She advocates for public engagement through op-eds and blogs like 'Punk Rock Operations Research.' Education: PhD in Industrial Engineering, University of Illinois at Urbana-Champaign (2006) MS in Industrial Engineering, University of Illinois at Urbana-Champaign (2001) BS in Industrial Engineering, University of Illinois at Urbana-Champaign (2000) Research Interests: Dr. Albert’s work bridges operations research and public policy, addressing challenges in emergency medical services, voting system security, law enforcement strategies, and opioid treatment diversion programs. She employs mathematical optimization, game theory, and stochastic modeling to design resilient systems. Awards: INFORMS Impact Prize (2018) NSF CAREER Award (2011) Fulbright Award (2020) AAAS Fellow (2020) Advising & Grants: While explicit student names aren’t listed, her research has been supported by grants from the NSF, Army Research Office, and other agencies. She advises on interdisciplinary projects involving public health, cybersecurity, and disaster management. Labs/Teams: Engaged in collaborative efforts across the College of Engineering, including affiliations with the Electrical & Computer Engineering department. Leads initiatives on resilient infrastructure and emergency response systems.

Jan Dirk Wegnerمشاهده پروفایل

دانشیار

• Machine Learning
• Computer Vision
• Remote Sensing
• +۷ مورد دیگر

Jan Dirk Wegner is an Associate Professor at the University of Zurich, holding the chair in 'Data Science for Sciences' and leading the EcoVision Lab. He previously served as a Postdoc (2012–2016) and senior scientist (2017–2020) at ETH Zurich's Photogrammetry and Remote Sensing Group, following his PhD (with distinction) from Leibniz University Hannover (2011). His research bridges machine learning, computer vision, and remote sensing to address environmental and geoscience challenges, focusing on large-scale environmental data analysis, vegetation monitoring, and climate change mitigation. Education: PhD (with distinction) in Geodesy, Leibniz University Hannover (2011) Postdoc, ETH Zurich (2012–2016) Senior Scientist, ETH Zurich (2017–2020) Research Interests: Machine Learning, Computer Vision, Remote Sensing, Environmental Science, Climate Science, Geosciences, Explainable AI, Uncertainty Quantification, and Applications in Sustainability. The EcoVision Lab develops data-driven methods for global-scale environmental monitoring, including vegetation parameter mapping, flood prediction, forest degradation detection, and AI-driven ecological modeling. Awards: ETH Postdoctoral Fellowship (2012–2016) Science Prize of the German Geodetic Commission WEF Young Scientist Class 2020 (Top 25 globally under 40) Advising & Leadership: Director of the University of Zurich's Doctoral School in Data Science, leading the EcoVision Lab, and coordinating the CVPR EarthVision Workshops. His roles include Vice President of ISPRS Technical Commission II, member of the ETH AI Center, ELLIS, and UN-ETH Partnership. Labs/Teams: EcoVision Lab focuses on interdisciplinary AI applications for environmental challenges, collaborating with NGOs, governments, and industry to translate research into societal impact.

Jochen Wirtzمشاهده پروفایل

استاد

• Service Management
• Intelligent Automation
• Artificial Intelligence (AI)
• +۶ مورد دیگر

Jochen Wirtz is the Vice Dean of MBA Programmes and Professor of Marketing at the National University of Singapore (NUS Business School). He holds a Ph.D. in services marketing from the London Business School and has held leadership roles, including founding director of the UCLA–NUS Executive MBA Programme and member of the NUS Teaching Academy. His research focuses on service management, intelligent automation, AI, and corporate digital responsibility. A globally recognized authority, he has authored over 20 books, including Services Marketing: People, Technology, Strategy (9th ed.) and Intelligent Automation , with translations in 26+ languages. His awards include the Christopher Lovelock Career Contributions Award (AMA) and the Academy of Marketing Science’s Outstanding Marketing Teacher Award. He advises international firms like Accenture and KPMG and is involved in start-ups such as Dataswyft and TranscribeMe. His work emphasizes ethical AI, service robots, and cost-effective excellence, contributing to both academic research and industry practice. Wirtz’s research spans service robots, platform economies, and luxury services. His recent studies explore generative AI’s impact on service encounters, corporate digital responsibility, and B2B customer experience strategies. He actively engages with industry through consulting, keynote speaking, and executive education.

Ivan Martinovicمشاهده پروفایل

استاد

• Cyber-Physical Systems Security
• Wireless Network Security
• Authentication Systems
• +۳ مورد دیگر

Prof. Ivan Martinovic is a Professor of Computer Science at the University of Oxford's Department of Computer Science, holding a Fellowship at the institution. He specializes in cyber-physical systems security, wireless network security, and behavioral biometrics. His research focuses on authentication mechanisms, intrusion detection, and trade-offs between security and performance in systems like satellite communications, EV charging infrastructure, and aviation networks. Education: PhD (TU Kaiserslautern); MSc (TU Darmstadt, Germany). Prior roles include postdoctoral research at UC Berkeley (2011) and UC Irvine (2009–2010), supported by a Carl-Zeiss Foundation Fellowship (2009–2011). He has also been an associate lecturer at TU Kaiserslautern. Research Interests: Cyber-physical systems security, wireless networks, behavioral biometrics (e.g., continuous authentication via physiological signals), robust communication protocols, and analysis of security vs. performance trade-offs in distributed systems. Technologies include software-defined radios, NFC/RFIDs, and EEG/eye-tracking devices. Scientific Awards: Carl-Zeiss Foundation Fellowship (2009–2011). Advising & Grants: No explicit student listings; however, his work involves interdisciplinary collaborations and has been funded by government and industrial grants. His research spans labs and teams focused on satellite cybersecurity, smart infrastructure security, and biometric systems. Labs/Teams: Engages with groups exploring satellite communication security, EV charging infrastructure vulnerabilities, and behavioral authentication systems, though specific lab names are not disclosed in the text.

Stephanie Gilمشاهده پروفایل

استادیار

• Artificial Intelligence
• Robotics and Control
• Computer Science
• +۴ مورد دیگر

Stephanie Gil is an Assistant Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences. Her research focuses on artificial intelligence, robotics, and distributed systems, particularly addressing challenges in multi-agent coordination, resilience to adversarial attacks, and wireless communication for autonomous systems. She leads the REACT Lab, advancing research in resilient multi-robot networks and cyber-physical systems. Her work integrates machine learning, control theory, and wireless sensing to solve problems such as whale tracking via autonomous robots, proactive multi-robot routing, and decentralized exploration without explicit information exchange. She has received prestigious awards, including the DARPA Young Faculty Award (2024) and the Amazon Research Award (2021). Key research areas include resilient distributed optimization, trust-centered coordination in multi-agent systems, and leveraging wireless signals (e.g., WiFi-CSI) for sensing and bearing estimation. Her contributions span both theoretical frameworks and practical implementations, with a focus on real-world applications like autonomous rideshare routing and environmental monitoring. Dr. Gil’s research also explores trust and cybersecurity in dynamic networks, with publications on crowd vetting, malicious robot detection, and adaptive communication strategies. She collaborates on interdisciplinary projects, such as Project CETI, combining AI and robotics for ecological studies.