Find Academic Supervisors

Florian ZemminView profile

Professor

• Islamic Studies
• Religion and Society in Islamic and Arab Contexts
• Islamic Reformism
• +3 more

Florian Zemmin is a Professor at Freie Universität Berlin's Institute of Islamic Studies , serving as Co-Director of the Berlin Graduate School Muslim Cultures and Societies (BGSMCS). His research focuses on Islamic reformism , Middle Eastern conceptual history , and Arabic sociologies of religion within broader debates about modernity and secularity . Current affiliations: Freie Universität Berlin (since 2020) Previous affiliations: Universität Bern (2010-2020), Universität Leipzig (2015-2021) His research interests examine how Islamic traditions intersect with modern secular concepts through: Historical conceptual analysis in Arabic and Ottoman contexts Comparative secularisms beyond Western frameworks Postcolonial critiques of Eurocentric theory Sociological approaches to Islamic knowledge production Current projects include: Das soziokulturelle Leben soziologischer Konzepte – creating a critical lexicon of 60 sociological terms in Arabic Global Secularity: A Sourcebook – co-editing a 7-volume series on secular formations across regions Arabic Sociologies of Religion – challenging Eurocentric sociology through Arabic theoretical work Key publications address: Conceptual transfers in Islamic modernism Secularism in Islamic intellectual history Arabic sociology of religion Ottoman conceptual transformations Islamic responses to global social theory

Guy DoveView profile

Professor

• Philosophy of Psychology
• Abstract Concepts
• Embodied Cognition
• +5 more

Guy Dove is a Professor in the School of Arts & Sciences Humanities at the University of Louisville. His research bridges philosophy, cognitive science, neuroscience, linguistics, and artificial intelligence, focusing on the philosophy of psychology and abstract concept formation. PhD in Philosophy from the University of Chicago His work explores how language shapes cognition, advocating for a multimodal and flexible framework to understand abstract concepts. Recent publications address the implications of large language models for human cognition and the role of linguistic scaffolding in semantic memory. Key journals include Philosophical Transactions of the Royal Society B , Cognitive Neuropsychology , and Topics in Cognitive Science . He co-authored the book Consciousness and Physicalism: A Defense of a Research Program . Prior to his current role, Dove worked in the Developmental Neuropsychology and Electrophysiology Lab (2002-2003) and taught in the Department of Psychological and Brain Sciences (2004-2008).

Ka I IpView profile

Assistant Professor

• Developmental neuroscience
• Emotion regulation
• Cross-cultural psychology
• +8 more

Ka I Ip is an Assistant Professor at the Institute of Child Development , University of Minnesota. As director of the D.A.N.C.E. Lab , Dr. Ip employs multimodal methods including neuroimaging, cortisol assays, and cross-cultural experiments to study emotion regulation and developmental psychopathology. PhD in Developmental Psychology (University of Michigan) Susan Nolen-Hoeksema Postdoctoral Fellow (Yale University) Research focuses on how cultural contexts and early adversity shape emotional development, with particular attention to racial-ethnic minorities and immigrant families . His work applies findings to social policy reform and health equity initiatives. Recent publications analyze neighborhood socioeconomic impacts on brain development , discrimination effects in bilingual adolescents , and cortisol dynamics in immigrant families . Key journals include Biological Psychiatry and Developmental Psychology . APA Editor’s Choice Article (2024) Yale Health Equity Research Finalist (2022) Accepting PhD students for Fall 2026. Collaborates with teams in neuroimaging , cross-cultural research , and pediatric biomarker studies .

• Corporate Governance
• Gender and Finance
• Corporate Culture
• +4 more

Dr. Kai Li serves as Professor of Finance at the University of British Columbia's Sauder School of Business, holding the Canada Research Chair in Corporate Governance and W. Maurice Young Endowed Chair in Finance. Elected Fellow of the Royal Society of Canada (2022), she is Managing Editor of the Journal of Financial and Quantitative Analysis and previously served on editorial boards of Review of Financial Studies, Management Science, and Journal of Finance. Her academic foundation includes a BSc from Jiaotong University, MA from Concordia University, and PhD from the University of Toronto. Dr. Li's research examines corporate governance through three interconnected lenses: gender dynamics in finance (board diversity, analyst performance), corporate culture quantification (using generative AI and machine learning), and green innovation (environmental governance). Her methodology pioneers computational approaches to analyze textual data from corporate disclosures, bridging finance, computer science, and social sciences. Analysis of her recent publications reveals a distinct trajectory toward interdisciplinary research, increasingly integrating artificial intelligence with traditional finance to study culture and sustainability. This shift demonstrates growing emphasis on empirical measurement of intangible governance factors through NLP and generative models. Her accolades include: Fellow of the Royal Society of Canada (2022) UBC Killam Research Award Sauder Research Excellence Award (junior/senior) Barclays Global Investors Canada Research Award John L. Weinberg/IRRCi Best Paper Award (2024) Best Paper Award at 2024 China International Conference in Finance While the provided materials confirm her editorial leadership and research impact, specific details regarding graduate student supervision and grant funding portfolios were not disclosed. Dr. Li maintains affiliations with the Asian Bureau of Finance and Economic Research (Senior Fellow), European Corporate Governance Institute (Research Member), and FinTech at Cornell Initiative (Research Fellow).

Lifeng ZhouView profile

Assistant Professor

• Robotics
• Algorithms
• Combinatorial Optimization
• +4 more

Lifeng Zhou is an Assistant Professor in the Department of Electrical and Computer Engineering at Drexel University, where he leads the Zhou Lab focused on advancing robustness and reliability in multi-robot systems through integration of foundation models. His research addresses real-world challenges in environmental monitoring, disaster response, and urban mobility. Education PhD, Electrical and Computer Engineering, Virginia Tech, 2020 MS, Control Science and Engineering, Shanghai Jiao Tong University, 2016 BS, Automation, Huazhong University of Science and Technology, 2013 Research Focus Dr. Zhou's work integrates robotics, algorithms, game theory and machine learning to develop secure and scalable autonomous systems. Primary research thrusts include: Resilient multi-robot coordination in adversarial environments Large language model integration for robotic decision-making Game-theoretic resource allocation strategies Risk-aware planning for autonomous vehicles Publication Trends Recent work (2024-2025) demonstrates strong focus on large language model applications in multi-robot systems, with 12/15 articles exploring LLM integration for flocking, scene segmentation, and decision-making. Additional emphasis includes adversarial robustness in target tracking (5 articles) and autonomous driving applications (4 articles). Awards and Recognition Best Paper Award, WACV 2025 LLVM-AD Workshop Professional Service Associate Editor, ICRA Conference Editorial Board Laboratory Focus The Zhou Lab develops foundational algorithms for secure and scalable multi-robot systems, with current projects spanning environmental monitoring drones, disaster response coordination, and autonomous vehicle perception systems.

Siwei LyuView profile

Professor

• Digital Media Forensics
• Computer Vision
• Machine Learning
• +4 more

Dr. Siwei Lyu is a SUNY Distinguished Professor and SUNY Empire Innovation Professor in the Department of Computer Science and Engineering at the University at Buffalo. He serves as Co-Director of the Center for Information Integrity (CII) and Director of the UB Media Forensic Lab (UB MDFL). His research focuses on digital media forensics, computer vision, and machine learning, with significant contributions to counter-deepfake technologies. Education includes a PhD in Computer Science from Dartmouth College (2005), MS from Peking University (2000), and BS in Information Science from Peking University (1997). He has held academic positions at the University at Albany and New York University. His work spans media forensics, adversarial machine learning, and AI security. Notable achievements include developing the Celeb-DF dataset, leading NSF-funded projects, and testifying before U.S. and NYS legislative bodies on disinformation threats. Over $11.3M in grants have supported his research on AI-generated media detection, including a $5M NSF Convergence Accelerator grant. Key awards include IEEE and IAPR Fellowships, Google Faculty Award, and SUNY Chancellor's Research Award. He has authored 230+ papers, 4 patents, and serves on editorial boards of top journals and conferences (e.g., CVPR, ICCV).

Frank E. GarceaView profile

Academic

• Cognitive Neuroscience
• Neuroimaging
• Neurology
• +4 more

Frank E. Garcea, Ph.D., is a Research Assistant Professor in the Department of Neurosurgery and Neuroscience at the University of Rochester School of Medicine and Dentistry. His research focuses on the cognitive and neural mechanisms underlying tool use, apraxia, and stroke recovery. He employs neuropsychological testing, fMRI, and lesion-symptom mapping to study brain injury effects on functional connectivity and action knowledge. Education: Bachelor of Science in Psychology, St. John Fisher College (2006–2010) PhD in Brain and Cognitive Sciences, University of Rochester (2012–2017) Research Interests: Dr. Garcea investigates how brain regions like the parietal cortex and dorsal/ventral streams mediate object manipulation and tool use. His work explores stroke-related disconnection syndromes, motor speech coordination networks, and translational brain mapping to preserve neural function during surgery. He collaborates on projects involving epilepsy patients undergoing electrocorticography to study action-related neural pathways. Labs & Affiliations: Principal Investigator of the Garcea Lab at URMC, focusing on tool use deficits in brain tumor/stroke survivors. Affiliated with the Del Monte Institute for Neuroscience and the Neurobiology & Anatomy Program. His lab integrates neuroimaging, lesion analysis, and clinical care to advance personalized brain mapping strategies.

Mahesh TripunitaraView profile

Professor

• Information Security
• Authorization and Access Control
• Cryptographic Key Transport
• +7 more

Dr. Mahesh Tripunitara is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, serving as Associate Chair for Undergraduate Studies. He holds a PhD (2005) and Master's (1995) in Computer Science from Purdue University, along with a BSc (1993) in Computer Science from Dalhousie University. His research focuses on information security, authorization mechanisms, cryptographic key management, and hardware security, with industry experience at Motorola's R&D labs and Silicon Valley. His work spans theoretical advancements like access control policy analysis and practical applications such as secure payments systems and IoT device reliability. Notable awards include the Best Student Paper at Usenix Security 2013 and Best Paper at ACM SACMAT 2013. He actively serves on program committees for major security conferences including CCS, CODASPY, and SACMAT. Recent publications highlight innovations in cellular security (SUCI-Catchers defense), role-mining optimization, and blockchain smart contract auditing. Teaching includes advanced algorithm design courses (ECE 406/606) and digital computation (BME 121). His research emphasizes balancing security rigor with usability in authorization systems and hardware protection mechanisms.

Alfred ChongView profile

Associate Professor

• Actuarial Science
• Financial Mathematics
• Quantitative Risk Management
• +5 more

Dr. Alfred Chong is an Associate Professor in the Department of Actuarial Mathematics and Statistics at Heriot-Watt University (HWU). Previously, he served as an Assistant Professor at the University of Illinois at Urbana-Champaign (UIUC) and co-founded the Illinois Risk Lab. His research focuses on Actuarial Science, Financial Mathematics, and Quantitative Risk Management, addressing emerging risks like cyber, pandemic, and climate risks, leveraging machine learning, optimization, and stochastic control. He holds a PhD from The University of Hong Kong and King's College London, and is an Associate of the Society of Actuaries. Chong actively contributes to academic governance, including roles in the EPSRC Mathematical Sciences Early Career Forum and the Maxwell Institute's Data and Decisions research theme. Education: PhD in Actuarial Science, University of Hong Kong & King's College London Research Interests: Chong explores risk sharing mechanisms, forward preferences in insurance, and mitigation strategies for large-scale risks. His work integrates data analytics and machine learning to solve decision-making challenges, such as cybersecurity risk assessment, pandemic resource allocation, and climate risk modeling. Recent projects include incident-specific cyber insurance design and delegated investment strategies for retirement savings. Awards: Michael V. Colla Prize for Mathematics Related to Medicine (2022) Best of 2020 in the Annual Meeting of the Casualty Actuarial Society (2021) Advising & Grants: Chong supervises PhD students in holistic risk management, forward preferences, and reinforcement learning applications. He has secured grants supporting interdisciplinary research in risk modeling and insurance innovation. Labs & Teams: Co-founder of the Illinois Risk Lab (UIUC), now leading research at HWU's Actuarial Mathematics & Statistics department. Engaged with the International Centre for Mathematical Sciences for knowledge exchange initiatives.

Shannon M BellView profile

Professor

• Political Theory
• Cyber Politics
• Aesthetics and Politics
• +3 more

Shannon Bell is a Professor in Political Science at York University, working as a performance philosopher who integrates digital video technology with political theory. Her research examines intersections of cyberpolitics, aesthetics, and power through projects like 'Shooting Theory', which visualizes philosophical concepts through film. She has authored books including 'Fast Feminism' and 'Reading, Writing and Rewriting the Prostitute Body'. Current SSHRC-funded projects explore bioart and robotic art extremes, with residencies at Symbiotica (UWA) and international exhibitions. She teaches courses on modern political thought, technopolitics, and aesthetics. Educational background includes a PhD in Political Science from York University. Professional leadership includes directing the Resource Centre for Public Sociology.

Manolis SavvaView profile

Associate Professor

• Computer Graphics
• Computer Vision
• 3D Scene Analysis
• +4 more

Manolis Savva is an Associate Professor in the School of Computing Science at Simon Fraser University and holds the Canada Research Chair in Computer Graphics. He specializes in 3D scene analysis, generative methods for 3D content, and computer graphics for AI. His research bridges computer graphics, vision, and robotics. Education: Ph.D. (Computer Science, Stanford University, 2016), MS (Computer Science, Stanford, 2012), B.A. (Physics & Computer Science, Cornell, 2009). Research Interests: Human-centric 3D scene analysis, generative 3D content creation, AI-driven rendering, and applications in robotics. Key projects include Habitat (Embodied AI platform), ScanNet , and ShapeNet datasets. Recent Articles: Focus on articulated object modeling, 3D scene synthesis, and AI-driven visualization. Notable work includes SceneMotifCoder (generating object arrangements) and R3DS (panoramic scene understanding). Awards: CHCCS Early Career Award (2022), ICLR 2023 Outstanding Paper Award, ICCV 2019 Best Paper Nomination, and SGP 2020 Dataset Award (ScanNet). Lab/Teams: Leads research groups in 3DLG (3D Learning and Graphics) and GrUVi (Graphics and Vision). Collaborates on projects like AI Habitat and HomeRobot .

• Parallel Computing
• Optimization Techniques
• High-Performance Computing (HPC)
• +5 more

Pascal BOUVRY is a full Professor of parallel computing and optimization techniques at the University of Luxembourg's Department of Computer Science , within the Faculty of Science, Technology and Medicine (FSTM) . He currently serves as the Dean of the FSTM and leads the Parallel Computing and Optimisation group . Additionally, he oversees the University's High Performance Computing (HPC) infrastructure. His research focuses on parallel computing, optimization algorithms, distributed systems, and their applications in bioinformatics and distributed environments. Prof. BOUVRY holds a Ph.D. in Computer Science from the University of Grenoble (France) and has extensive industry experience, including roles as CEO/CTO of tech firms and leadership in telecom and financial services sectors. He has pioneered initiatives like the Master in High-Performance Computing and Technopreneurship programs at the University of Luxembourg. His research interests span GPU programming paradigms , federated learning , distributed optimization , and trustworthy AI . Recent work includes advancements in HPC education frameworks, federated learning frameworks (e.g., FedPref), and quantum circuit optimization. He contributes to editorial boards of journals like IEEE Transactions on Sustainable Computing and IEEE Cloud Computing Magazine. Prof. BOUVRY has held international leadership roles, including as Honorary Chair of conferences and active participation in technical committees. His educational efforts emphasize bridging academic research with industrial applications, particularly in HPC and AI.

Simon RazniewskiView profile

Professor

• Knowledge-based Artificial Intelligence
• Natural Language Processing
• Data Science
• +3 more

Simon Razniewski is a Professor of Knowledge-based Artificial Intelligence at TU Dresden and ScaDS.AI, focusing on integrating language models and knowledge bases. He previously held roles at Bosch Center for AI (2023–2024), Max Planck Institute for Informatics (2017–2021), and Free University of Bozen-Bolzano (2014–2017). His research spans knowledge extraction, computational logic, and data science applications. He holds a PhD (2014) and Diplom (MSc, 2010) from Free University of Bozen-Bolzano and TU Dresden, respectively. Research interests include large language models (LLMs), knowledge graph construction, and uncertainty quantification in natural language processing. His work bridges AI theory and practice, with publications at top venues like ACL and EMNLP. He teaches courses on LLMs and knowledge-aware AI, and has advised numerous collaborative projects across academia and industry. Prominent contributions include frameworks like GPTKB for LLM knowledge materialization and QUITE for Bayesian reasoning in NLP. His prior roles at Siemens IT and Globalfoundries inform his applied research focus. The International Center for Computational Logic (ICCL) at TU Dresden is his primary research hub, emphasizing interdisciplinary computational logic and AI advancements.

Zhendong SuView profile

Professor

• Programming Languages
• Compilers
• Software Engineering
• +3 more

Zhendong Su is a full professor in the Department of Computer Science at ETH Zurich since August 2018. Previously, he held a full professorship at UC Davis from 2003 until June 2019. He earned his Ph.D. in Computer Science from UC Berkeley and dual Bachelor’s degrees in Computer Science and Mathematics from UT Austin in 1995. Affiliations: ETH Zurich: Full Professor (since 2018) UC Davis: Full Professor and Chancellor’s Fellow (2003–2019) IEEE Fellow, ACM Fellow, and Member of Academia Europaea His research focuses on programming languages, compilers, software engineering, computer security, and education technologies . Key contributions include compiler validation (e.g., Project Yin-Yang for SMT solvers and DBMS testing), testing tools like SQLancer, and educational innovations such as the Algot visual programming language. Recent work emphasizes secure AI (e.g., CipherSteal for TEE-shielded models) and compiler reliability (e.g., Artemis/Apollo for JIT validation). He has pioneered techniques like metamorphic testing and equivalence modulo inputs (EMI) for compiler validation, uncovering thousands of bugs in GCC/LLVM and SMT solvers. Awards: ICSE MIP Award (2022), ACM SIGSOFT Impact Paper (2018), NSF CAREER Award, and multiple industrial awards. His students have won IEEE TCSE Rising Star and SIGSOFT Impact Paper awards, securing roles at top universities and companies like Google and NVIDIA. Service: Steering committee member of ISSTA and ESEC/FSE, ACM Distinguished Speaker, and Associate Editor for ACM TOSEM. Program chaired ISSTA 2012 and co-chaired FSE 2016. Labs/Teams: Leads research groups on compiler validation, secure AI, and education technologies. Projects include Yin-Yang (SMT testing), SQLancer (DBMS fuzzing), and Algot (visual programming for education).

Lucy HedermanView profile

Associate Professor

• Health Informatics
• Clinical Decision Support Systems
• Healthcare Data Integration
• +3 more

Dr. Lucy Hederman is an Associate Professor in Computer Science at Trinity College Dublin (TCD), affiliated with the O'Reilly Institute. Her research focuses on leveraging data and documents to support clinical decision-making, particularly in healthcare knowledge work. She has led interdisciplinary projects addressing data integration for rare diseases (e.g., ANCA-vasculitis, MND) and socio-technical challenges in adopting patient-generated health data (PGHD) into clinical practice. Dr. Hederman has secured over €xxxk in research funding and leads the Heterogeneity and Interoperability (H&I) challenge in the SFI-funded ADAPT 2 Centre. Her educational background includes advanced studies in computer science and healthcare informatics, though specific degree details are not explicitly stated in the text. She has supervised 4 PhDs, 2 research MScs, and co-supervised 6 PhDs, while currently mentoring 8 graduate students. Her career includes founding TCD spinouts PBOC and BIOLOGIT, which align with her research in health informatics and technology. Key research interests include: Interdisciplinary collaboration between clinicians, researchers, and technologists Data harmonization for multi-national clinical studies (e.g., FAIRVASC, Precision-ALS) Development of clinical decision support systems (CDSS) Design of mobile health (mHealth) tools for underserved populations Recent work emphasizes FAIR principles for healthcare data and socio-technical factors influencing PGHD adoption. She has contributed to over 70 peer-reviewed publications and actively participates in initiatives like the EU-funded TRANSFORM project and HRB Primary Care Research Centre. Dr. Hederman’s professional memberships include the Irish Computer Society, ACM, and Healthcare Informatics Society of Ireland. Her research has impacted healthcare practices in Ireland, with many MSc student projects influencing local health services.