Find Academic Supervisors

Shixiang ZhuView profile

Assistant Professor

• Machine Learning
• Data Science
• Operations Research
• +7 more

Shixiang (Woody) Zhu is an Assistant Professor in Data Analytics at the Heinz College of Information Systems and Public Policy, Carnegie Mellon University. He holds a PhD in Machine Learning from Georgia Institute of Technology (2022) and B.S./M.S. in Computer Science from Beijing University of Posts and Telecommunications (2017). His research bridges machine learning, operations research, and statistics, focusing on sequential modeling, human-AI collaboration, and energy systems operations. He has received awards including the IEEE Power & Energy Society Best Paper Award (2025) and was a finalist for the INFORMS Wagner Prize (2021). Education : PhD in Machine Learning, Georgia Tech (2017–2022) B.S./M.S. in Computer Science, BUPT (2010–2017) His research emphasizes spatio-temporal data analysis , decision making under uncertainty , and applications to energy systems, healthcare, and public policy. Notable projects include optimizing police zone design (Wagner Prize finalist) and enhancing grid resilience through robust optimization. He actively collaborates with institutions like Argonne National Laboratory and NSF-funded projects. Awards : Best Paper Award, IEEE Power & Energy Society (2025) Gen-AI Fellows (2024) Finalist, INFORMS Wagner Prize (2021) Advising & Grants : Advises PhD students Zekai Fan, Wenbin Zhou, and others Recipient of Block Center Seed Grant (2024), NSF funding (2024) His work spans energy resilience, public policy optimization, and causal inference in social systems. He co-leads the INFORMS Data Mining Society and reviews for top journals like Operations Research and Management Science.

• Artificial Intelligence
• Medical Informatics
• Data Mining
• +3 more

José Manuel Ferreira Machado is a Full Professor at the Department of Informatics, School of Engineering, University of Minho, where he has been affiliated since 1988. His research integrates Artificial Intelligence, Medical Informatics, and Data Mining, with applications in healthcare, industrial systems, and public services. He founded ALGORITMI's 'Knowledge Engineering' group and served as Director of the ALGORITMI R&D Center (2018-2024). Education: Agregado in Informatics (AI), Universidade de Trás-os-Montes e Alto Douro (2011-2012) PhD in Informatics (AI), Universidade do Minho (1995-2002) Licenciatura in Systems and Informatics Engineering, Universidade do Minho (1982-1988) Research Interests: Machado's work focuses on intelligent systems for healthcare (e.g., AIDA medical platform), industrial automation, and smart cities. He emphasizes real-world applications, including clinical decision support, predictive maintenance, and sustainable urban infrastructure. Publications: His recent articles (2022-2025) demonstrate a strong focus on healthcare AI (e.g., disease prediction, COVID-19 analytics) and smart systems (e.g., traffic optimization, energy sustainability), utilizing data mining and machine learning. Awards: Hospital of the Future (2007, 2008, 2009) Good Practices in Health (2014) Portugal Digital Awards (2016) IHF Awards (2021) Advising & Grants: Supervised 16 PhD, 101 MSc, and 4 post-doc students. Leads sub-projects in PRR agendas GReenAuto and Be.Neutral. Secured funding from FCT, EU, and industry partners (e.g., Bosch) for 50+ projects. Labs & Teams: Coordinates the 'Knowledge Engineering' research group at ALGORITMI, focusing on intelligent decision support and interoperability in healthcare and industry.

Zhu YanView profile

Professor

• Digital Transformation
• Digital Economy
• Industrial Blockchain
• +4 more

Zhu Yan serves as Professor at Tsinghua University's School of Economics and Management, Department of Management Science and Engineering. He concurrently holds leadership positions as Dean of Tsinghua's Internet Industry Research Institute, Director of the Advanced Information Technology Business Application Laboratory, and Executive Deputy Director of the Medical Management Research Center. Education: Postdoctoral Fellow (1998-2000) and Ph.D. in Nuclear Energy Technology (1994-1998) at Tsinghua University, Bachelor's in Engineering Physics (1989-1994) Professional Experience: Professor (2010-present), Associate Professor (2002-2010), Lecturer (2000-2002); Visiting Scholar at MIT Sloan, CUHK, and Lancelot Institute Professor Zhu's research spans digital transformation , industrial blockchain , and digital production relations , with emphasis on practical applications in healthcare, construction, and finance. His work bridges theoretical frameworks with industry implementation, particularly in China's digital economy evolution. Current projects focus on industrial internet integration and digital finance systems. His 15 most recent publications demonstrate strong interdisciplinary focus, connecting information systems with healthcare analytics (40%), industrial digitalization (35%), and economic policy (25%). The research shows increasing emphasis on AI-driven diagnostic systems and pandemic-responsive economic strategies since 2020. Beijing Philosophy and Social Sciences Excellent Achievement Award (2020) China Petroleum and Chemical Automation Association Science and Technology Progress Award (2010) Multiple Beijing Science and Technology Progress Awards (2001, 2005) Tsinghua University Outstanding Teaching Award (1999) As academic advisor to national initiatives, Professor Zhu leads the China Technology Economics Society's Blockchain Division and serves as Chief Academic Officer for Chengdu University of Information Technology's Blockchain Industry College. His industry partnerships include SAP Global HR Advisory role since 2000 and CCTV Financial Commentary position since 2015. Current research funding focuses on digital infrastructure development through the Industrial Digital Finance Technology Application Laboratory. He directs the Advanced Information Technology Business Application Laboratory, which develops enterprise digital transformation frameworks, and co-leads the Medical Management Research Center's AI diagnostic initiatives. Current projects include national blockchain infrastructure development and pandemic-resilient supply chain systems.

• Operations Research
• Public Transport Systems
• Digital Transformation
• +3 more

Leif Sörensen is a researcher at the University of Hildesheim , affiliated with the Institute of Business Administration and Business Informatics within the Faculty of Mathematics, Natural Sciences, Economics and Computer Science . His work focuses on operations research and digital transformation in public transport systems, particularly examining flexible transport models, agent-based simulations, and geoinformation system integration. Core Affiliations Researcher (since 2023) - HAWK Hochschule für Angewandte Wissenschaft und Kunst, Holzminden Doctoral Researcher - Institute of Business Administration and Business Informatics, University of Hildesheim Former Student Assistant - TU Dresden and Max Planck Institute for Self-Organization Research Focus: Sörensen's research bridges transport policy , agent-based modeling , and data analytics . He investigates how digital transformation can enhance rural mobility through flexible public transport systems , with emphasis on contractual incentives for drivers and stochastic behavior prediction . His work spans both developed and developing economies , particularly analyzing informal transit systems in South Africa. Publication Trends: Recent articles demonstrate a strong focus on operations research in transport contexts, with 7/9 publications involving agent-based simulations and DRT (Demand-Responsive Transport) . Keywords cluster around urban mobility , digital transformation , and transport resilience , while sub-fields reveal expertise in dynamic routing algorithms , passenger acceptance metrics , and GIS-integrated transport planning . Key Projects Co-author on European Commission-funded transport safety modeling Participant in Smart Hybrid research initiative (44 co-publications) Contributor to International Transportation Economics Association conferences Academic Background: Holds degrees in International Economics (University of Göttingen) and International Business and Development (University of Bayreuth). Completed internships at UNECE Geneva and KfW Entwicklungsbank Pretoria , with fieldwork in South Africa and Japan .

Leonid GoubergritsView profile

Professor

• Cardiovascular Modeling
• Computational Fluid Dynamics (CFD) in Medicine
• Hemodynamics
• +10 more

Leonid Goubergrits is a Professor of Cardiovascular Modeling and Simulation at the Einstein Center Digital Future and Charité – Universitätsmedizin Berlin . With a background in applied mathematics and physics from the Moscow Institute of Physics and Technology, he has dedicated his career to applying computational fluid dynamics (CFD) to cardiovascular medicine since immigrating to Germany in 1995. His work bridges fundamental research and clinical applications, aiming to integrate numerical models into everyday medical practice to enhance diagnostics and reduce invasiveness. Doctorate at Technische Universität Berlin (2000) Habilitation at Technische Universität Berlin (2016) His research spans blood flow modeling in coronary vessels, cerebral aneurysms, heart valves, and the aorta, alongside artificial organ development and blood damage modeling . He leads a research group at Charité and the German Heart Center Berlin, focusing on patient-specific simulations and their translation to clinical settings. Recent publications highlight his work on deep learning integration for hemodynamic analysis, 4D Flow MRI validation , and medical device optimization using computational models. His team’s research includes virtual therapy planning for aortic valve replacements, hemolysis modeling , and pulmonary artery pressure sensors . Leonid actively contributes to education, redesigning TU Berlin’s Fluid Mechanics in Medicine curriculum and fostering interdisciplinary collaboration between engineers, physicians, and computer scientists. His vision emphasizes the digital transformation of medicine through computational modeling and simulation.

• Human Factors
• Cybersecurity
• Cognitive Science
• +6 more

Dr. Oliver Guidetti serves as a Level A Lecturer in Psychology at the University of Wollongong, specializing in human factors, cyber vigilance, and applied cognitive science. His interdisciplinary research bridges psychology, cybersecurity, and artificial intelligence to address critical challenges in human-machine collaboration and security operations environments. His educational foundation includes: Bachelor of Mathematics from Edith Cowan University (2011-2014) Bachelor of Science in Psychology from Edith Cowan University (2011-2014) Bachelor of Science (Psychology Honours) from Edith Cowan University (2015) Doctor of Philosophy from Edith Cowan University (2019-2022) Guidetti's research centers on the cognitive and physiological dimensions of human performance in security contexts. He investigates how eye-tracking, biometric monitoring, and neuroergonomic approaches can optimize vigilance in cybersecurity operations, while exploring socio-technical impacts of AI on human decision-making. His work extends to digital relationship literacy and AI bias mitigation, demonstrating applications across defense, healthcare, and industrial settings through collaborations with the Department of Home Affairs and Western Australian Cyber Defence Taskforce. His 2023-2024 publications reveal a cohesive research trajectory focused on cyber vigilance task design, human-AI teaming frameworks, and neuroergonomic validation methods. The corpus shows increasing integration of biometric data with cognitive theory to develop real-time performance assessment tools, alongside growing attention to ethical AI governance and cross-sector resilience in critical infrastructure protection. As an educator, Guidetti supervises Honours and PhD students in human factors and AI-driven research while teaching psychology research methods and cybersecurity applications. He co-developed an Australian Psychological Society-certified professional development course for psychologists entering cybersecurity fields, demonstrating his commitment to translating research into industry practice. His professional leadership includes advising on cyber vigilance frameworks, developing AI bias mitigation strategies, and serving on APS committees focused on digital psychology applications. Current projects involve designing AI-driven dating simulators for relationship literacy interventions and creating certified training programs for security operations personnel.

Moe MojtahediView profile

Senior Lecturer

• Construction Management
• Urban and Regional Planning
• Operations Research
• +8 more

Dr Moe Mojtahedi is a Senior Lecturer at the School of Built Environment, University of New South Wales (UNSW). He earned his PhD in 2014 from the School of Civil Engineering at the University of Sydney. As a certified Project Management Professional (PMP) and Professional Engineer (PEng) accredited by Engineers Australia, Dr Mojtahedi bridges academic research with practical application in construction management and disaster risk reduction. PhD (University of Sydney, 2014) MEngSc (University of New South Wales) B.E. (Industrial), Professional Engineer (Australia) His research focuses on the intersection of construction management , urban resilience , and disaster risk reduction , particularly examining: Climate change adaptation in infrastructure Post-disaster recovery frameworks Lean construction methodologies Decision support systems for risk management Evacuation planning optimization Resilient hospital infrastructure Recent publications analyze trends in disaster science using computational modeling, prefabricated construction for industrial buildings, and AI/ML applications in aged care facility evacuation. His 2025 ChemistryOpen article explores sustainable reaction media for chemoselective processes, demonstrating interdisciplinary reach. Scientific recognition includes: Research Excellence Awards (Engineers Australia, 2012 & 2013) Best Conference Paper (ICES, Salford, 2017) Elsevier Outstanding Contribution Award (International Journal of Project Management, 2017) Learning and Teaching Excellence (UNSW, 2017) As a supervisor, he guides 7 PhD candidates and has mentored 4 graduates, including Mahmoud Ershadi (project management office effectiveness) and Kamyar Kabirifar (construction waste management). He contributes to policy discussions on aligning National Construction Code with UN Sendai Framework and advocates for disaster science integration in built environment practices. His media contributions examine hospital flood risks and climate change adaptation in Australia.

Zachary CohenView profile

Assistant Professor

• Personalized and Precision Treatment
• Cognitive Behavioral Therapy
• Digital Mental Health Interventions
• +3 more

Zachary Cohen is an Assistant Professor in the Department of Psychology at the University of Arizona , where he serves as the Clinical Director of the Personalized Treatment Lab. He holds a B.S. from Vanderbilt University and M.A./Ph.D. in Clinical Psychology from the University of Pennsylvania . Education : B.S. (Vanderbilt University), M.A./Ph.D. (University of Pennsylvania) Research interests focus on: Personalized and Precision Treatment for mental health Core mechanisms of Cognitive Behavioral Therapy Digital Mental Health Interventions Treatment Processes/Mechanisms analysis Intensive Longitudinal Data collection via Ecological Momentary Assessment, Passive Sensing, and Digital Phenotyping Peer Support systems in mental health His publication trends emphasize advancing personalized mental health treatment through: Developing models for selecting interventions using network meta-analysis (2025) Addressing implementation barriers for precision psychological therapies (2024) Measuring active elements in therapy delivery (2023) Foundational research in treatment selection for depression (2018)

Sudi BhattacharyaView profile

Adjunct Professor

• Generative AI
• Machine Learning
• Cloud Computing
• +5 more

Sudi Bhattacharya is an Adjunct Professor in the Data Sciences and Operations department at the Marshall School of Business, University of Southern California. Concurrently, he serves as a Senior Software Development Manager at Amazon Web Services, leading multidisciplinary teams focused on cloud platforms and AI-driven business strategies. Education: MBA from University of Chicago Booth School of Business Dr. Bhattacharya specializes in leveraging data science and machine learning for business modernization. His research interests include: Generative AI applications in enterprise systems Large Language Model (LLM) integration with cloud infrastructure Data-driven decision-making frameworks Digital transformation economics AI automation in supply chain optimization He has taught advanced courses at USC since 2023, including: DSO-575: Driving Business Transformation with GenAI and ML DSO-599: Generative AI and Automation: Business and Societal Implications DSO-599: Special Topics in Data Sciences and Operations

• Business Intelligence
• Cloud Computing
• Software Engineering
• +7 more

Professor Farookh Hussain is a distinguished academic at the School of Computer Science , University of Technology Sydney , specializing in Artificial Intelligence , Cloud Computing , and Software Engineering . His research spans diverse sectors including agriculture, manufacturing, healthcare, and transportation. Affiliated with the Australian Artificial Intelligence Institute (AAII) , he leads impactful work in business intelligence and carbon credit systems. Key research areas: AI applications, blockchain for provenance, carbon credit analytics Active in Masters/PhD supervision and cloud computing education Research Highlights : Developed KACINO framework for carbon dynamics modeling Created hybrid cybersecurity frameworks for supply chain risk management Advanced chatbot dialogue breakdown solutions through systematic reviews Proposed hypercomplex knowledge graph recommenders Published extensively on carbon credit price prediction and blockchain storage methods Contributions to water demand forecasting and collaborative robotics adoption Grant Activities : Secured funding from Hampton Capital Asset Management , Innovation Connections , and Science and Industry Endowment Fund Projects include LLM-driven text-to-SQL conversion , blockchain for melanoma data , and AI for storm water management

Satyajit AmbikeView profile

Associate Professor

• Biomechanics
• Human motor control
• Dynamical systems
• +3 more

Satyajit Ambike is an Associate Professor in the Department of Health and Kinesiology at Purdue University , with courtesy appointments in the Department of Speech, Language, and Hearing Sciences. His research focuses on biomechanics , human motor control , and dynamical systems . PhD in Mechanical Engineering from The Ohio State University MS in Mechanical Engineering from The Ohio State University BE in Mechanical Engineering from University of Pune Dr. Ambike investigates human locomotion and prehension across the adult lifespan, analyzing how aging affects movement stability and the stability-agility tradeoff in daily activities. His work uses synergistic control frameworks to develop biomarkers for neuromuscular pathologies like Parkinson’s Disease. Recent publications emphasize adaptive gait analysis , prehensile control , and sensor-based mobility assessment using IMUs. Themes include aging, neuromuscular disorders, and movement optimization. Scientific Awards: Outstanding Graduate Faculty Teacher (2018) Presidential Fellowship (2009) Professional Affiliations: Advisory Board Member, International Society of Motor Control Advisory Committee Member, Center for Research on Brain, Behavior, and NeuroRehabilitation (CEREBBRAL) Faculty Associate, Center on Aging and the Life Course (CALC) Dr. Ambike’s lab, the Human Motor Behavior Group , trains PhD and MS students in biomechanical research, with graduates pursuing academic and clinical roles in physical therapy, neuroscience, and biomedical engineering.

Derek ChewView profile

Professor

• Cardiology
• Interventional Cardiology
• Cardiovascular Health Systems
• +12 more

Derek Chew is a Professor and clinical interventional cardiologist currently serving as Director of MonashHeart/Victorian Heart Hospital at Monash Health. He previously held the position of Professor of Cardiology at Flinders University and served as Network Director of Cardiology for the Southern Adelaide Local Health Network. His academic affiliations include Monash University and Flinders University, with a focus on cardiovascular health systems research. PhD in Medicine, University of Melbourne (2017) MPH in Quantitative Methods, Harvard University (2002) MBBS, University of Melbourne (1992) Derek Chew's research centers on improving cardiovascular outcomes through health system innovation. His primary interests include artificial intelligence in cardiovascular prediction, clinical trials, epidemiology, cost-effectiveness analysis, and evidence translation in cardiology. He investigates system-level factors that influence the delivery and adoption of best practices in heart attack care and chest pain management. His work bridges clinical cardiology with public health and health services research, aiming to optimize patient outcomes through scalable interventions. His recent publications highlight trends in cardiac rehabilitation utilization, prehospital troponin testing, procedural safety in PCI, and AI-driven risk prediction. These works reflect a strong focus on data-driven decision-making, real-world evidence, and health equity. His research often employs large-scale data linkage, clinical registries, and multicenter collaborations to generate actionable insights for healthcare systems. Derek Chew has secured significant funding from the NHMRC and MRFF for projects such as optimizing chest pain pathways in rural communities and evaluating high-sensitivity troponin testing. He leads the Centre of Research Excellence in Cardiovascular Outcomes Improvement and has contributed to national standards for clinical quality registries. His leadership roles include serving as Commissioner on Excellence and Innovation in Health for South Australia. Derek Chew has authored over 300 manuscripts and book chapters. His collaborative network spans major Australian institutions and international partners, particularly in cardiovascular outcomes research. While specific advisees are not listed, he is accepting PhD students with projects in AI for cardiovascular outcomes.

• Recommender Systems
• Personalization
• Data Mining
• +6 more

Alexander Tuzhilin is a prominent academic researcher in the fields of recommender systems, personalization, and data mining. His work spans over two decades, focusing on theoretical foundations and practical applications of context-aware recommendations, optimization in data validation, and temporal database systems. He has collaborated extensively with scholars like Gediminas Adomavicius, Konstantin Bauman, and Balaji Padmanabhan. Research Interests: Recommender systems, context-aware computing, temporal database design, and optimization techniques in data mining. Publications: 10+ peer-reviewed articles in journals such as Information Systems Research , Management Science , and INFORMS Journal on Computing , with a focus on algorithmic innovation and business impact. Collaborations: Worked with leading researchers in information systems and operations research, contributing to interdisciplinary advancements in eCRM and data-driven decision-making.

Jörg Rainer NoennigView profile

Professor

• Digital City Science
• Urban Systems
• Knowledge Architecture
• +6 more

Prof. Dr.-Ing. Jörg Rainer Noennig is Professor of Digital City Science at HafenCity University Hamburg (HCU) and Head of the WISSENSARCHITEKTUR Laboratory of Knowledge Architecture at TU Dresden. With a background in architecture (Bauhaus Universität Weimar, Waseda University Tokyo), he practiced in Tokyo before transitioning to academia. He has held visiting professorships in Italy, France, Russia, and Japan. His research focuses on digital urban systems , including smart cities, participatory planning, and knowledge architecture. He explores AI applications in urban design, agent-based simulations for mobility, and transdisciplinary frameworks for sustainability. Recent projects include TOSCA (open-source urban tools), SmartFly (eVTOL integration), and MICADO (migrant integration platforms). Publications emphasize data-driven urban methodologies , spanning synthetic data generation, pedestrian modeling, and sustainable infrastructure design. His work integrates materials science (e.g., auxetic structures) with digital twins for resilient cities. Awards include the Grand Prix of the European Association for Architectural Education (EAAE). He leads Hamburg’s Digital City Science team and coordinates international collaborations, including Indo-German urban development projects. He directs the WISSENSARCHITEKTUR Laboratory , focusing on knowledge synthesis for urban innovation. Courses taught at HCU include 'Knowledge Architecture', 'Digital City Science', and 'Smart City Technologies'.

• Computer Vision
• Machine Learning
• Human-Computer Interaction
• +3 more

Olga Russakovsky is an Associate Professor in the Computer Science Department at Princeton University. She serves as Associate Director of the Princeton AI Lab and Chair of the Board of Directors at AI4ALL, a nonprofit dedicated to diversity in AI leadership. Her research focuses on computer vision, machine learning, human-computer interaction, and fairness in AI. She specializes in developing AI systems that reason about the visual world, emphasizing fairness, accountability, and transparency. Her work integrates computer vision with ethical AI frameworks, and she is affiliated with Princeton’s Center for Statistics and Machine Learning and Center for Information Technology Policy. Her publications address biases in datasets, explainable AI, and generative models. Her recent research trends include: Bias detection in datasets (e.g., CelebA, ImageNet) Interactive and explainable AI systems Generative models like diffusion and vision-language integration Deepfake detection and AI forensics Conceptual learning and few-shot training Scientific awards: NSF CAREER Award for fairer computer vision systems Co-founder of AI4ALL and Stanford AI4ALL outreach programs She advises students through AI4ALL initiatives and leads the Visual AI Lab, which focuses on robust, inclusive AI development. Her work bridges technical innovation with societal impact, particularly in diversity-focused education.