Find Academic Supervisors

Dong Lou is a Professor of Finance at the Hong Kong University of Science and Technology (HKUST), where he serves as Associate Dean of Business and Management (Strategic Planning and Research) and Acting Head and Chair Professor of the Department of Finance. He is also a CEPR Research Fellow at the London School of Economics (LSE). His research focuses on asset pricing, investment management, and behavioral finance, with a particular emphasis on market inefficiencies, trading dynamics, and macrofinancial linkages. PhD in Finance, Yale University, 2009 His scholarly work explores liquidity provision, arbitrage activity, investor behavior, and the impact of information dissemination on financial markets. Recent studies include the effects of dollar asset holdings on global yields, retail margin trading dynamics, and the relationship between communication rates and security prices. His publications appear in top journals like Management Science , Journal of Financial Economics , and Review of Financial Studies . His research has been recognized with numerous awards, including the Crowell Memorial Award, NASDAQ OMX Award, and multiple INQUIRE and CRSP Forum grants. He mentors PhD students in finance and co-directs the HKUST-DXM AI for Finance Joint Laboratory, advancing AI applications in financial research and practice.

• Asset Pricing
• Investment Management
• Behavioural Finance
• +2 more

Harry R. Lloyd is an Assistant Professor of Philosophy at the University of North Carolina at Chapel Hill, serving as Core Faculty for the PPE Program and Research Affiliate at the Center for AI Safety. He joined UNC Chapel Hill in Fall 2025 after completing his PhD at Yale University, where his dissertation examined moral uncertainty and bargaining under Shelly Kagan. His academic foundation includes a Ph.D. in Philosophy from Yale University (2020-2025) and a first-class B.A. in Philosophy, Politics, and Economics from the University of Oxford's Lady Margaret Hall (2016-2019), where he graduated top of his cohort and won multiple prizes including the Hicks/Webb Medley Prize and Uehiro Essay Prize. He attended Monmouth Comprehensive School (2009-2016), becoming the first comprehensive school student to win Trinity College Cambridge's Philosophy Essay Prize. Lloyd's research integrates Ethics, Political Philosophy, and Philosophy of AI through innovative frameworks for moral uncertainty and bargaining theory. His work bridges abstract theory with urgent real-world applications in AI alignment, distributive justice, and urban policy. He critically examines how normative disagreement should be resolved in AI systems, challenges conventional views on gentrification's moral dimensions, and develops resource-rational approaches to contractualism in animal ethics and intergenerational justice. His publication trajectory reveals a cohesive intellectual project: advancing bargaining-theoretic solutions to moral uncertainty while applying these frameworks across AI safety, political philosophy, and bioethics. Recent work in Philosophical Studies and Ergo establishes novel connections between moral uncertainty and collective decision-making, while his Journal of Urban Affairs article redefines gentrification's ethical analysis beyond displacement metrics. Awarded significant fellowships and prizes including the Rocky Mountain Ethics Congress Young Ethicist Prize (2024) and Global Priorities Institute Essay Prize (2021), his honors demonstrate impact across multiple domains: Institute for Humane Studies Junior Fellowship (2025) Forethought Foundation Global Priorities Fellowship (2022-2024) Rocky Mountain Ethics Congress Young Ethicist Prize (2024) Global Priorities Institute Early Career Conference Programme (2022) Research funding includes the Global Priorities Fellowship (2022-2024) and Institute for Humane Studies Junior Fellowship (2025). He actively shapes academic discourse through peer review for journals including Philosophical Studies and Journal of Applied Philosophy, and co-organizes the Yale Moral Philosophy Working Group. Though newly appointed, his teaching portfolio spans Environmental Ethics, PPE Capstone, and Philosophy of Technology, building on Yale teaching experience where he served as primary instructor for Philosophy and Technology. Lloyd maintains active research affiliations with the Center for AI Safety and previously contributed as a Resident Fellow at Yale's Information Society Project (2023-2025). His collaborative networks extend to the Global Priorities Institute at Oxford and Happier Lives Institute, driving interdisciplinary work at the AI-society interface through regular presentations at PPE Society meetings and ethics conferences.

• Ethics
• Political Philosophy
• Philosophy of AI
• +6 more

Teemu Roos is a Professor at the Department of Computer Science , University of Helsinki , and a Principal Investigator for the Complex Systems Computation Group under the Helsinki Institute for Information Technology. He serves as a Supervisor for the Doctoral Programme in Computer Science and leads multiple research initiatives, including Distributed AI in Supercomputing , AI & Kids , and Generation AI . Dr. Roos also holds a Docent title in Computer Science. His research spans Artificial Intelligence , Machine Learning , and Data Science , with a focus on AI education , graph neural networks , Bayesian modeling , and health informatics . He has pioneered tools like Elements of AI , a free online course now translated into 22 EU languages, and explores the ethical implications of AI-generated content in authorship and inventorship. The 15 most recent publications highlight applications in environmental forecasting (e.g., Mediterranean Sea via graph-based deep learning), healthcare (e.g., skin cancer detection with transfer learning), and social media analysis (e.g., explainable AI platforms for K-12 education). Methodologically, his work advances clustering algorithms , dimensionality reduction , and approximate nearest neighbor search . Scientific Awards: Cor Baayen Award (2009) Nokia Foundation Recognition Award (2019) Best Paper Honorable Mention Award (2013) ICT Influencer of the Year 2019 (Vuoden TiVi-vaikuttaja 2019) World Summit AI's Top-50 Innovators in 2020 Dr. Roos has supervised 2 doctoral students and contributed to 163 academic activities , including invited talks at MIT, University of Cambridge, and the Finnish Institute in Rome. He has secured funding from the Academy of Finland and the Strategic Research Council, focusing on projects like Fast AI-assisted Space Environment Prediction and Urban Exerciser .

• Artificial Intelligence
• Machine Learning
• Data Science
• +6 more

Johan Eklöf is a Professor at Stockholm University within the Department of Ecology, Environment and Plant Sciences . His research emphasizes marine ecology , focusing on interactions between marine biodiversity, environmental conditions (including climate), and societal impacts . He teaches courses such as Management of Aquatic Resources in the Tropics , Marine Ecology for the Biogeo Program , and Ecology II . Research Focus: Causal relationships between biodiversity and ecosystem resilience Foundation species as drivers of ecosystem services Optimizing resource management under climate change Projects: Principal Investigator for FORCE (2023-present), a transdisciplinary Baltic Sea recovery project Contributor to NordSalt (climate impacts on Nordic salt marshes) and PlantFish (Baltic Sea vegetation-fish interactions) Scientific Leadership : Supervises 2 current PhD students and co-supervises 6 additional PhD/postdocs Formerly mentored 4 PhD graduates and >40 MSc students Environmental Context: His work spans Baltic Sea and Western Indian Ocean ecosystems, using seagrass beds , mussel beds , and coastal benthic systems as primary models. Recent publications highlight climate change impacts on trophic cascades , habitat connectivity , and policy frameworks for marine conservation .

• Marine Ecology
• Biodiversity and Ecosystem Resilience
• Environmental Change
• +3 more

Owen O'Donnell is a Full Professor of Applied Economics at the Erasmus School of Economics and Erasmus School of Health Policy & Management , Erasmus University Rotterdam. He is a Research Fellow at the Tinbergen Institute and an Editor of the Journal of Health Economics . Education: DPhil, University of York (UK) Research Interests: His work focuses on health economics, including health inequality, health insurance, financial protection, and labor economics, with applications in low-, middle-, and high-income countries. He employs cross-sectional analyses, equity-sensitive frameworks, and global health policy evaluation. Publications & Collaborations: He has published extensively in top journals like Lancet , PLOS Medicine , and Demography , addressing cardiovascular disease, hypertension screening, and healthcare access in India, Philippines, and Sub-Saharan Africa. His recent research emphasizes equity-sensitive welfare weights and treatment gain inequality. Professional Activities: He has served as an Editor for the Journal of Health Economics since 2007 and is actively involved in peer-review and editorial work until 2026.

• Health Economics
• Health Inequality
• Health Insurance & Financial Protection
• +4 more

Anamitra Pal is an Associate Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. His work focuses on power system resilience, renewable energy integration, and time-synchronized measurement analytics. He leads research initiatives combining artificial intelligence with grid modernization challenges. Ph.D. Electrical Engineering, Virginia Tech (2014) M.S. Electrical Engineering, Virginia Tech (2012) B.E. Electrical and Electronics Engineering, Birla Institute of Technology (2008) Prior to ASU, Pal conducted postdoctoral research at Virginia Tech's Network Dynamics and Simulation Science Laboratory (2014-2016). His research interests center on enhancing grid stability through: Advanced synchrophasor data analytics AI-driven power system security frameworks Renewable generation integration strategies Critical infrastructure protection during extreme events Recent publications demonstrate his focus on grid resilience during wildfires, deep learning-based state estimation, and innovative PMU applications. Pal has received multiple accolades including the NSF CAREER Award (2022) and IEEE Phoenix Section's Outstanding Young Professional Award (2019).

• Data Analytics
• Artificial Intelligence Applications in Power Systems
• Renewable Energy Integration
• +3 more

Ibo van de Poel is a Full Professor at Delft University of Technology , within the Faculty of Technology, Policy and Management , specifically in the Section Philosophy . He holds the prestigious Antoni van Leeuwenhoek professorship , awarded to excellent young researchers, and is a leading figure in Design for Values , engineering ethics , and technology as social experimentation . Education: Van de Poel studied Philosophy of Science, Technology and Society at the University of Twente , with a propaedeutic exam in Mechanical Engineering . He earned his PhD in Science and Technology Studies (STS) in 1998 from the University of Twente , under the supervision of Prof. Dr. A. Rip. Research Interests: His research spans three major themes: Design for Values : Investigating how moral values can be integrated into engineering design, including empirical studies on how engineers handle value conflicts. Moral Responsibility in R&D Networks : Exploring the "problem of many hands" in large-scale research and development projects, developing formalizations and empirical methods. Ethics of Emerging Technologies : Examining ethical issues in new technologies like nanotechnology and synthetic biology , with a focus on technology as social experimentation . Publications and Impact: Van de Poel has authored over 25 international peer-reviewed articles and 15 book contributions . He is co-editor of major works including the Handbook of Philosophy of Technology and the Engineering Sciences (Elsevier, 2009), Philosophy and Engineering (Springer, 2010), and Ethics, Engineering and Technology (Wiley-Blackwell, 2011). His recent work includes leading the VICI project "New Technologies as Social Experiments" , funded by NWO. Scientific Awards: Antoni van Leeuwenhoek Professorship (TU Delft) VICI Grant for "New Technologies as Social Experiments: Conditions for Morally Responsible Experimentation" Advising and Grants: Van de Poel has led and contributed to multiple high-impact projects, including: NWO Project on "Moral Responsibility in R&D Networks" (2007–2012) EU Project on ethical issues in synthetic biology (2009–2011) VICI Project on "New Technologies as Social Experiments" (ongoing) He has also supervised PhD students and contributed to educational innovations, including the development of the AGORA web-based program and the first Dutch textbook on ethics and technology . Labs and Teams: Van de Poel is an active member of 4TU.Ethics & Technology , a federation of Dutch technical universities focused on ethics and technology. He contributes to the Simon Stevin Series in the Ethics of Technology and participates in various reading groups and PhD communities within the network.

• Design for Values
• Engineering Ethics
• Moral Responsibility in R&D Networks
• +3 more

Xiaoming Hu is a Professor at the Division of Numerical Analysis, Optimization and Systems Theory within the Department of Mathematics at KTH Royal Institute of Technology (Kungliga Tekniska Högskolan) in Stockholm, Sweden. Born in Chengdu, China, he received his B.S. degree from University of Science and Technology of China in 1983, followed by M.S. and Ph.D. degrees from Arizona State University in 1986 and 1989 respectively. After serving as a research assistant at the Institute of Automation, Chinese Academy of Sciences (1983-1984), he was a Gustafsson Postdoctoral Fellow at KTH (1989-1990) before becoming a faculty member. His educational background includes: B.S. in Engineering, University of Science and Technology of China, 1983 M.S. in Engineering, Arizona State University, 1986 Ph.D. in Engineering, Arizona State University, 1989 Xiaoming Hu's research primarily focuses on multi-agent systems, nonlinear feedback stabilization, nonlinear observer design, and sensing and active perception. His work bridges theoretical control theory with practical applications in robotics and autonomous systems. He has made significant contributions to geometric control theory, mathematical systems theory, and nonlinear systems analysis and control. His research often involves developing theoretical frameworks for distributed control, formation control, and cooperative behavior in multi-robot systems. Professor Hu's publication record shows a consistent research trajectory with numerous high-impact publications in top-tier journals like Automatica, IEEE Transactions on Automatic Control, and Systems & Control Letters. His research has evolved from fundamental control theory to more applied problems in robotics and multi-agent systems, while maintaining strong mathematical foundations. Recent work shows increasing focus on safety-critical control, inverse problems in estimation, and networked systems. His scientific contributions include: Development of theoretical frameworks for multi-agent coordination and formation control Advances in nonlinear observer design for robotic systems Contributions to geometric control theory and systems theory Research on distributed estimation and control algorithms Applications of control theory to robotics and autonomous systems Professor Hu teaches several advanced courses including Mathematical Systems Theory, Geometric Control Theory, and Nonlinear Systems: Analysis and Control. He has supervised numerous degree projects at both undergraduate and graduate levels in mathematics, optimization, systems theory, and scientific computing. His teaching reflects his research expertise, providing students with both theoretical foundations and practical applications of control theory.

• Multi-agent systems
• Nonlinear control systems
• Systems theory
• +4 more

Younghoon Kim serves as a Visiting Professor in the Department of Asian Studies within the Faculty of Arts at the University of British Columbia (UBC), where he contributes to research and teaching in Korean studies, translation, and contemporary media. His work bridges cultural analysis with critical examinations of television and film across Korean and American contexts. Educational Background: Ph.D. from University of Alberta (2011) M.A. from University of Alberta (2006) M.A. from Sogang University (2004) B.A. from Myong Ji University (2002) Dr. Kim's research centers on Korean popular culture and national identity formation, with particular focus on entrepreneurship narratives and self-help culture in contemporary Korea. He investigates contemporary American television dramas as cultural artifacts reflecting societal shifts, while also exploring translation practices and fashion as expressions of cultural identity. His interdisciplinary approach connects media studies with sociological and philosophical frameworks. His recent publications reveal consistent thematic threads examining neoliberal subjectivity through television analysis (including Breaking Bad and Mad Men), Korean youth cultural expressions, and cross-cultural literary adaptations. The scholarly output spans musicology, television studies, and translation theory, with significant contributions to understanding how media shapes identity in both Korean and global contexts. Journal publications demonstrate strong engagement with A&HCI-indexed and Korean Citation Index venues.

• Korean Studies
• Translation Studies
• Television Studies
• +4 more

Prof. Dr. Jonas Schreyögg is a Professor of Healthcare Management and Scientific Director of the Hamburg Center for Health Economics (HCHE) at the University of Hamburg since 2010. He holds the Chair of Healthcare Management and serves as Deputy Chairman of the German Council of Economic Experts for Health and Nursing Care. His roles also include memberships on scientific advisory boards and associated research at Stanford University. Education & Career: Doctorate and Habilitation (2008) from Technical University of Berlin Former Professor at Ludwig-Maximilians-University of Munich (LMU Munich) Junior Professor at Technical University of Berlin Harkness Fellow at Stanford University (2006–2007) Research Interests: Focus on healthcare systems, health economics, hospital payment reforms, pandemic policy responses, and healthcare workforce optimization. Key areas include DRG systems, healthcare competition, and socioeconomic disparities in health outcomes. He has conducted extensive research on the impact of policy interventions during the COVID-19 pandemic, including lockdown perceptions and vaccine acceptance. Grants & Awards: Recipient of the Harkness Fellowship, German National Academic Foundation doctoral scholarship, and multiple research grants. His work has been published in leading journals like Health Affairs , Journal of Public Health , and Social Science & Medicine . Professional Activities: Engaged in international collaborations and teaching in Norway, Singapore, Taiwan, and the U.S. He advises on healthcare policy and has contributed to high-profile reports on healthcare workforce sustainability and pandemic response strategies.

• Healthcare Management
• Health Economics
• Health Policy
• +5 more

Mohammad Mohammadi Amiri serves as an Assistant Professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI), appointed in Fall 2023. His research focuses on advancing artificial intelligence through strategic data utilization, with emphasis on large language models, data valuation, federated learning, and deep learning. Previously, he held postdoctoral appointments at Princeton University and MIT Media Lab, building on his strong educational foundation from Imperial College London, University of Tehran, and Iran University of Science and Technology. Education: Ph.D. in Electrical and Electronic Engineering, Imperial College London (2019) - Best Ph.D. Thesis Award recipient M.Sc. in Electrical and Computer Engineering, University of Tehran (2014) - Ranked 1st among all M.Sc. students B.Sc. in Electrical Engineering, Iran University of Science and Technology (2011) - Ranked 1st among all B.Sc. students Dr. Amiri's research centers on optimizing artificial intelligence systems through innovative data strategies. His work addresses critical challenges in large language models including efficiency, memory usage, alignment, and reasoning capabilities. In data valuation, he develops principled methods to quantify data worth for fair trading platforms. His federated learning research tackles privacy concerns, heterogeneous data distribution, and communication overhead in decentralized environments. The deep learning component explores theoretical foundations to improve model interpretability and robustness. Analysis of his recent publications reveals a strong focus on making AI systems more efficient and accessible, with particular emphasis on large language model optimization, federated learning advancements, and data valuation frameworks. His work bridges theoretical foundations with practical applications in wireless communications and distributed computing environments. Scientific Awards: IEEE Communications Society Young Author Best Paper Award (2022) Best PhD Thesis Award from IEEE Information Theory Chapter of UK and Ireland (2019) Eryl Cadwallader Davies Prize for Outstanding PhD Thesis (2019) EEE Departmental Scholarship at Imperial College London (2015-2019) Ranked 1st among M.Sc. students at University of Tehran (2014) Ranked 1st among B.Sc. students at Iran University of Science and Technology (2011) Dr. Amiri actively mentors graduate students, currently supervising five Ph.D. candidates and one M.Sc. student working on efficient LLM fine-tuning, inference, and storage. His research has attracted significant attention, evidenced by numerous keynote invitations at prestigious institutions including Bell Labs, MIT, King's College London, and various IEEE conferences. He serves on program committees for major conferences including IEEE Globecom and ICC, demonstrating his growing influence in the academic community. His research group operates at the intersection of machine learning and wireless communications, developing innovative solutions for resource-constrained environments while addressing fundamental theoretical challenges in AI systems. Current projects focus on making advanced AI more scalable and accessible through efficiency improvements in model training and inference.

• Large Language Models
• Data Valuation
• Federated Learning
• +5 more

Xiaojiang Du is the Anson Wood Burchard Endowed Professor at Stevens Institute of Technology, directing research in IoT security, AI security, and wireless networks. An IEEE Fellow and ACM Distinguished Member, he leads NSF-funded projects on secure IoT systems and cross-platform security vulnerabilities. Education PhD in Electrical Engineering, University of Maryland MS in Electrical Engineering, Tsinghua University BE in Electrical Engineering, Tsinghua University Research Focus: Develops security frameworks for IoT ecosystems and adversarial machine learning, with recent breakthroughs in smart home security anomaly detection. Honors: IEEE Fellow, ACM Distinguished Member, multiple best paper awards at IEEE conferences. Graduated PhD students hold faculty positions at UNC Charlotte, UL Lafayette, and ShanXi University. Professional Service: IEEE ComSoc Distinguished Lecturer, Associate Editor for IEEE Transactions, and General Co-Chair for IEEE/ACM IWQoS 2023. Secured $9M+ in research funding from NSF, NSA, and DOD.

• IoT Security
• AI Security
• Wireless Networks
• +2 more

Natalia Rybczynski is an Adjunct Research Professor in the Department of Biology at Carleton University, affiliated with the Faculty of Science. Her primary research focuses on Paleobiology and Paleoenvironments of the Cenozoic High Arctic and functional morphology of vertebrate feeding and locomotion systems. She holds offices at the Canadian Museum of Nature in Gatineau and coordinates interdisciplinary projects on Arctic paleoenvironments, pinniped evolution, and vertebrate herbivore feeding mechanisms. Education: B.Sc. in Biology, Carleton University M.Sc. in Zoology, University of Toronto Ph.D. in Evolutionary Anthropology, Duke University Research Interests: Reconstructing Arctic paleoenvironments during the Neogene Evolutionary transitions in marine mammals (e.g., pinnipeds) Feeding kinematics in herbivorous vertebrates like hadrosaurs Integration of field-based paleontology with biomechanical and anatomical analyses Her publications span paleoclimatology, fossil analysis, and evolutionary studies, emphasizing Arctic ecosystems and vertebrate adaptations. Collaborative work includes geoscientists to reconstruct ancient Arctic climates and anatomists to model feeding systems in extinct species. Active in field expeditions and lab-based experimental studies. Labs/Teams: Collaborates with Canadian Museum of Nature researchers and international teams in Arctic paleontology projects. Engages in interdisciplinary initiatives like the PoLAR-FIT project studying Pliocene Arctic ecosystems.

• Paleontology
• Evolutionary Biology
• Functional Morphology
• +7 more

Mehmet Esat Belviranli is an Assistant Professor in the Computer Science Department at the Colorado School of Mines, where he directs the High Performance Systems and Software Lab (HyperSys). His research focuses on increasing resource utilization in heterogeneous architectures through runtime systems, scheduling algorithms, and performance modeling, with publications in top venues including MICRO, PPoPP, and SC. Education: Ph.D. in Computer Science, University of California, Riverside (2016) M.S. in Computer Science, Bilkent University (2009) B.S. in Computer Science, Bilkent University (2006) Belviranli's research spans heterogeneous architectures, runtime systems, performance modeling, parallel programming, autonomous computing, deep learning acceleration, cyber-physical systems, and edge-cloud platforms. His work develops analytical models and programming abstractions to address resource management, scheduling, and security challenges in diversely heterogeneous systems, with applications in edge computing, autonomous systems, and machine learning acceleration. Recent projects emphasize real-world constraints and security implications. His publication trends reveal increasing focus on edge-cloud resource management (e.g., HARNESS), security vulnerabilities in heterogeneous systems (e.g., MC3), and deep learning acceleration under resource constraints. Key themes include memory contention modeling, scheduling for cyber-physical systems, and concurrent DNN execution, reflecting a shift toward practical deployment in security-sensitive edge environments. Scientific Awards: U.S. Air Force Research Lab Summer Faculty Fellowship Award (2022) U.S. Air Force Research Lab Summer Faculty Fellowship Award (2021) Oak Ridge National Laboratory Significant Event Award (2019) Best Paper Finalist, IEEE HPEC 2018 Outstanding Paper Award, DATE 2024 Belviranli mentors Ph.D. students Ismet Dagli (MLCommons Rising Star 2024, CGO'24 SRC finalist) and Justin Davis (DATE'24 Outstanding Paper Award winner). He has secured $2M+ in funding from NSF, DoE, and SRC, including an NSF-SaTC grant on mobile security (2024), a DoE grant on superconductive systems (2023), and an NSF FuSe grant on graphene nanoribbons (2023), often leading multi-institutional teams from Rochester, Virginia, Arizona, and Minnesota. The HyperSys Lab develops ecosystems for high-performance heterogeneous systems, with recent projects including HARNESS for edge-cloud resource management and MC3 for mobile SoC security. The lab has received equipment donations from Google Coral.ai and Xilinx, and collaborates with national labs on security challenges and next-generation semiconductor technologies.

• Heterogeneous Architectures
• Runtime Systems
• Performance Modeling
• +5 more

Jonathan Shihao Ji is an Associate Professor in the School of Computing at the University of Connecticut (UConn), leading the Intelligent Systems Lab. He holds a Ph.D. in Electrical and Computer Engineering from Duke University and previously served as an Associate Professor at Georgia State University and Director of the DoD Center of Excellence (CiARE). His research focuses on deep learning applications in computer vision, NLP, robotics, and high-performance computing, with over 50 publications in top venues like CVPR, NeurIPS, and IEEE journals. He has secured grants from NSF, NIH, DoD, and industry partners including VMware and Nvidia. His work emphasizes efficient algorithms for large-scale data processing, parameter-efficient model fine-tuning (e.g., VB-LoRA), and 3D perception benchmarks for UAVs (UAV3D). Notable contributions include sparse network optimization (Dep-L0), energy-based models (M-EBM), and robust defenses against adversarial attacks (Defense-VAE). He is a Senior Member of IEEE and has developed open-source tools like Parallel Word2Vec and WordRank. Recent projects include accelerating Llama2 models on FPGAs (LlamaF) and improving text-to-image synthesis via contrastive learning. His research spans theoretical advancements and practical applications, with industry collaborations in healthcare, robotics, and embedded systems.

• Deep Learning
• Computer Vision
• Natural Language Processing
• +5 more