Find Academic Supervisors

• MRI
• Diffusion MRI
• Perfusion MRI
• +6 more

Professor Fernando Calamante is a Professor of Biomedical Engineering at The University of Sydney and Director of Sydney Imaging Core Research Facility. He leads the National Imaging Facility node and focuses on advanced MRI methodologies, particularly Diffusion and Perfusion MRI, to study brain connectivity and neurological disorders. His work includes developing the MRtrix software, widely used in diffusion MRI analysis. He holds extensive funding (~$50M) and has been recognized with awards like ISMRM Fellowship and NHMRC grants. His research spans super-resolution imaging, brain connectomics, and clinical applications in stroke and tumors. Education: BSc (Physics, Argentina), PhD (Magnetic Resonance Imaging, University College London). Career highlights include leadership roles at The Florey Institute and ISMRM presidency (2021-2022). Research interests include: Novel MRI methods for brain connectivity and super-resolution imaging Applications of Diffusion and Perfusion MRI in neurology Integration of structural and functional connectomics Key achievements: Over 200 publications, software innovations, and leadership in global MRI societies.

Alessandro OttavianoView profile

Researcher

• Computer Architecture
• Embedded Systems
• Real-Time Systems
• +3 more

Dr. Alessandro Ottaviano is a Researcher affiliated with the Department of Digital Integrated Circuits and Systems at ETH Zürich. His work focuses on advanced computer architecture and embedded systems, particularly in the domains of RISC-V processors, real-time systems, and heterogeneous computing. He contributes to the design of time-predictable virtual memory solutions, mixed-criticality systems, and energy-efficient hardware-software interfaces. Key research areas include modular processor architectures, hardware monitoring for safety-critical applications, and power management in high-performance computing (HPC) systems. His recent projects involve developing controllers for 2.5D systems-in-package and creating open-source networking solutions for mixed-criticality environments. Ottaviano’s work often emphasizes open-source hardware design and scalable system-level approaches to address challenges in autonomous systems and edge computing. He collaborates on advancements in interrupt handling for virtualized systems, peripheral event linking for IoT devices, and FPGA-based thermal emulation for many-core processors. His research bridges theoretical computer architecture principles with practical implementations in embedded and real-time systems.

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).

Patrick ScholtenView profile

Professor

• Industrial Organization
• E-commerce Economics
• Applied Game Theory
• +2 more

Dr. Patrick Scholten is Professor of Economics at Bentley University, researching industrial organization, e-commerce economics, and applied game theory. His work analyzes firm behaviors in online markets using econometric methods. Education includes: PhD in Economics, Indiana State University MS in Student Affairs and Higher Education, Indiana State University Research examines price dispersion, network effects, ID verification impacts, and corporate social responsibility expectations. Recent publications focus on geo-cultural FDI determinants and business sustainability pressures.

Pierre BaldiView profile

Professor

• Artificial Intelligence
• Machine Learning
• Bioinformatics
• +7 more

Pierre Baldi is a Distinguished Professor of Computer Science and Director of the Institute for Genomics and Bioinformatics at the University of California, Irvine (UCI). He is affiliated with the Donald Bren School of Information and Computer Sciences. His research spans artificial intelligence, machine learning, bioinformatics, and communication networks, with notable projects in protein structure prediction, gene expression modeling, and neutrino physics collaborations like DUNE. Baldi’s work bridges theoretical foundations (e.g., neural network theory) and applied domains, including medical imaging and fusion technology. Key research interests include AI-driven biomedical applications, neural network theory, and interdisciplinary projects such as the DUNE neutrino experiment. His contributions to neural network engineering were recognized with the 2023 INNS Dennis Gabor Award, highlighting his paradigm-changing impact on computational neuroscience and physics. Baldi’s academic leadership includes directing UCI’s Institute for Genomics and Bioinformatics, fostering collaborations in computational biology and AI. His recent work explores AI’s role in healthcare, climate modeling (e.g., ClimSim-Online), and fundamental physics challenges like neutrino oscillation studies.

Maria ChikinaView profile

Assistant Professor

• Computational Biology
• Genomics
• Machine Learning
• +7 more

Maria Chikina is an Assistant Professor at the University of Pittsburgh School of Medicine's Department of Computational and Systems Biology. She holds a PhD in Molecular Biology from Princeton University. Her research focuses on developing computational methods to analyze large-scale genomic datasets, bridging statistical rigor with biological insights to overcome experimental biases. Key research areas include latent variable modeling (e.g., PLIER, CellCODE), interpretable neural networks for sequence-to-function modeling, evolutionary rate analysis (RERconverge), and applications in tumor immunology, exercise genomics, and infectious disease (e.g., SARS-CoV-2). Her lab has developed tools like InstaPrism, NIFA, and L0 segmentation for data-driven biological discovery. Her work spans collaborations with institutions like UPMC (on tumor microenvironment) and the Molecular Transducers of Physical Activity Consortium (MoTraPAC). Notable projects include analyzing convergent evolution in marine mammals and subterranean species, and developing epigenetic biomarkers for disease states through the ECHO program. Lab members include PhD students (Rezwan Hosseini, Tugrul Balci) and postdocs (Tina Subic, Anish Sevekari). Past students Wynn Meyer now leads a group at Lehigh University. Her group emphasizes open-source tools (GitHub repository ChikinaLab) and interdisciplinary approaches to systems biology challenges.

Heesung WooView profile

Assistant Professor

• Robotics in Forestry
• Sensor Integration
• Precision Forestry
• +4 more

Dr. Heesung Woo is an Assistant Professor of Advanced Forestry at the College of Forestry, Oregon State University , specializing in robotics, sensor integration, and precision forestry. His work focuses on autonomous forestry machinery, AI-driven forest management, and sustainable practices. He advises two graduate students and collaborates internationally through research projects. Research Interests: Autonomous Forest Machinery Development Sensor Integration & ICT Solutions Precision Forestry via Remote Sensing/LiDAR/GIS Machine Learning for Forest Inventory Advanced Forestry Practices for Sustainability Publications emphasize innovative applications of technology in forestry, including LIDAR integration, harvester data analytics, and carbon offset project modeling. His work bridges engineering, environmental science, and policy. Dr. Woo leads the Advanced Forestry Lab at Oregon State, focusing on real-world deployment of cutting-edge technologies to address challenges in forest operations, sustainability, and resource optimization.

Alyssa B. ApselView profile

Professor

• RF Mixed Signal Circuit Design
• Ultra-Low Power Radio
• Photonic Integration with VLSI
• +4 more

Alyssa B. Apsel is a Professor of Electrical and Computer Engineering at Cornell University since 2002 and a Visiting Professor at Imperial College London. She became the IBM Professor of Engineering in 2023 and Director of Electrical and Computer Engineering at Cornell in 2018. Education: B.S., Electrical Engineering, Swarthmore College (1995) M.S., Electrical Engineering, California Institute of Technology (1996) Ph.D., Electrical Engineering, Johns Hopkins University (2002) Research Focus: She specializes in power-aware mixed-signal circuits for scaled CMOS and modern systems. Her group explores cost-effective designs addressing device scaling challenges (variation, noise, reduced analog performance) through analog/mixed-signal innovation, particularly in IoT radios and reconfigurable multi-standard wireless systems. Key areas: RF circuits, VLSI integration, biomedical telemetry, and low-power design. Publication Trends: Her 2016 work spans RF transceiver design, thermometer DAC calibration, biomedical ICs with UWB telemetry, and jitter-measurement circuits. These reflect her expertise in low-power wireless systems, analog/mixed-signal design, and biomedical electronics. Awards: IEEE Fellow (2020) IEEE CAS Distinguished Lecturer (2018-2019) ISLPED Design Contest Second Place (2010) Multiple Student Paper Awards (2000, 1995) Fellowships: Abel Wolman (1997), Caltech Institute (1995) Grants & Leadership: She founded EchoICs, which received a $275,000 NSF STTR Phase I Award (2024) for flexible spectrum radios. Her lab focuses on RF interfaces for implantable electronics and photonic integration.

• Numerical Analysis
• Partial Differential Equations
• Finite Element Method
• +3 more

Dirk Praetorius is a Professor of Numerics of Partial Differential Equations (PDEs) at the Technische Universität Wien (TU Wien) , affiliated with the Institute for Analysis and Scientific Computing (ASC) within the Faculty of Mathematics and Geoinformation . He leads the research group on Numerics of PDEs and has held various leadership roles, including Institute Director (since 2020) and head of the Numerics research area. His work focuses on numerical methods for PDEs, including Finite Element Methods (FEM), Boundary Element Methods (BEM), adaptive algorithms, and computational micromagnetics. Education and Career: Praetorius earned his Diplom in Mathematics (2000) and PhD in Applied Mathematics (2003) from TU Wien, followed by a Habilitation in Numerical Analysis (2005). He has been a faculty member at TU Wien since 2005, progressing from Assistant Professor to full Professor in 2017. He has also held visiting positions at institutions such as the University of Jyväskylä and RICAM (Linz). Research Interests: His research spans numerical analysis, adaptive FEM/BEM, a-posteriori error estimation, matrix compression, and computational micromagnetics. He has contributed to modeling spin dynamics, magnetic skyrmions, and multiscale systems. His work emphasizes efficient algorithms for large-scale problems and optimal computational complexity. Awards and Editorial Roles: Praetorius received the TU Best Teacher Award (2021) and TU Best Lecture Award (2019). He serves as Senior Editor for Computational Methods in Applied Mathematics (CMAM) and on the editorial board of Applied Numerical Mathematics (APNUM) . He co-founded the outreach initiative TUForMath to promote mathematics education. Grants and Projects: He leads or co-leads several research projects funded by the Austrian Science Fund (FWF), including the collaborative SFB "Taming Complexity in Partial Differential Systems" (2017–2025) and international collaborations with Germany. His work addresses topics like functional error estimates, nonlinear PDEs, and computational design of magnetic devices. Labs and Teams: He contributes to the ASC Institute and coordinates interdisciplinary projects involving computational physics and engineering. His team develops software tools like MooAFEM and Commics for micromagnetic simulations.

Prithvi Ravi KantanView profile

Researcher

• Rehabilitation Technology
• Biofeedback Systems
• Sound Processing
• +6 more

Prithvi Ravi Kantan is a full-time Researcher at Aalborg University's Department of Architecture, Design and Media Technology within The Technical Faculty of IT and Design. His work focuses on developing sound-based and multimodal feedback systems for motor rehabilitation, integrating principles from music technology and biomedical engineering. Education: PhD in Embodied Sonification Design (2021-2023) M.Sc. in Sound and Music Computing (2018-2020) B.E. in Electronics and Telecommunications (2009-2013) Research interests include real-time auditory feedback systems for neurological rehabilitation, user-centered design of clinical technologies, and the application of generative music in data sonification. He actively contributes to projects like HearWalk (2023-2027), exploring sound-facilitated motor learning in cerebral palsy patients. Notable achievements include winning the Danish Sound Day Research Pitch Battle (2023) and receiving the Best Student Paper Award at ICAD 2024. His work aligns with UN SDG 3 (Good Health) and SDG 4 (Quality Education). Teaching responsibilities include coordinating bachelor and master-level courses in PBL-based learning, emphasizing interdisciplinary approaches. He has supervised multiple student projects and contributed to over 39 publications since 2013.

Kevin P. O'BrienView profile

Associate Professor

• Quantum Computing
• Superconducting Circuits
• Nonlinear Optics
• +3 more

Kevin P. O'Brien is an Associate Professor in the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT), affiliated with the Research Laboratory of Electronics (RLE). He leads the Quantum Coherent Electronics (QCE) group, focusing on advancing superconducting quantum computing, microwave quantum optics, and quantum metamaterials. His research explores nonlinear and quantum-mechanical light-matter interactions using superconducting circuits, aiming to improve quantum technologies like qubits and amplifiers. Education: B.S. in Physics from Purdue University, Ph.D. in Physics from UC Berkeley, and postdoctoral research at UC Berkeley developing superconducting quantum processors. His group collaborates with MIT Lincoln Laboratory and institutions nationwide. Research Interests: Quantum computing hardware, superconducting circuits, parametric amplifiers, qubit measurement systems, and metamaterials for quantum applications. His work emphasizes scalable architecture design, noise reduction, and novel device concepts. Key projects include directional qubit readout resonators, Floquet-mode amplifiers, and quarton couplers for ultrafast readout. The group actively engages in training graduate students and postdocs, emphasizing open collaboration and problem-solving in quantum technologies. Advising & Grants: Supervises a dynamic team of graduate students and postdocs. Students like Bright Ye and Kaidong Peng have contributed to award-winning projects. The group receives support through fellowships (e.g., Jin Au Kong, NSF GRFP) and industry partnerships. Labs/Teams: Quantum Coherent Electronics Group at MIT, collaborating on quantum device fabrication, theoretical modeling, and experimental validation of quantum systems.

Danny Poo Chiang ChoonView profile

Associate Professor

• Healthcare Informatics
• Data Science
• Business Analytics
• +6 more

Danny Poo Chiang Choon is a tenured Associate Professor at the School of Computing (SOC), National University of Singapore (NUS). As Curriculum Chair of the Department of Information Systems and Analytics, he plays a key role in designing and implementing Information Systems and Computer Science curriculum at NUS. Dr. Poo earned his BSc (Honours), MSc and PhD in Computation from the University of Manchester Institute of Science and Technology (UMIST), United Kingdom. His academic journey has established him as a leader in health informatics and information systems at NUS. His research spans multiple domains with strong focus on Healthcare Informatics , where he investigates mobile health interventions, health analytics, and systems for improving patient care. His work in Data Science & Business Analytics explores knowledge management, information sharing, and effective search strategies. In Intelligent Systems , he examines software engineering approaches, object-oriented systems, and knowledge classification frameworks. His recent publications demonstrate a clear trajectory toward mobile health applications, particularly in coronary heart disease prevention and diabetes management. Dr. Poo's work consistently bridges technical computing with practical healthcare applications, focusing on user-centered design and evidence-based interventions. His research shows strong interdisciplinary integration between computer science, healthcare systems, and behavioral science, with emphasis on practical implementation in Singapore's healthcare context. Dr. Poo has served in numerous leadership roles including as the founding Director of the Centre for Health Informatics at NUS (2012-2015) and as a member of the Steering Committee of the Asia Pacific Software Engineering Conference (APSEC) since 1994, serving as Vice-Chairman from 2003-2005. He has been invited to speak at international forums including the Japanese Government's "USA, Kyushu and Asia International Exchange Project" and as a keynote speaker at the 2009 Arabic Scripts Second Symposium in Abu Dhabi. His expertise is recognized through invitations to speak on knowledge management topics at conferences in Singapore. Dr. Poo has authored five books in the Information Technology area: "Enterprise JavaBeans for Students" (2014), "Object-Oriented Programming and Java" (1998, 2007), "Learn to Program Enterprise JavaBeans 3.0" (2009), "Learn to Program Java" (2009), and "Learn to Program Java User Interface".

• Human-Computer Interaction
• Responsible Innovation
• AI Ethics
• +8 more

Helena Webb is a Visiting Lecturer in the Department of Computer Science at the University of Oxford, where she contributes to research and teaching within the Human Centred Computing theme. Her work bridges social science and computer science, focusing on responsible innovation, AI ethics, and user interactions with digital technologies. PhD in Social Sciences, University of Nottingham Bachelor’s in Social and Political Sciences, University of Cambridge Former Senior Researcher, University of Oxford Department of Computer Science Researcher at Work, Interaction and Technology (WIT) Research Centre, King’s College London (2009–2014) Her research interests include human-computer interaction, algorithmic fairness, privacy in smart homes, and ethical design of social robots. She specializes in qualitative research methods and interdisciplinary collaboration to understand how technology shapes and is shaped by social practices. She has led and contributed to major projects such as Digital Wildfire , UnBias , ReEnTrust , and RoboTIPS , all focused on responsible governance and design of digital systems. Her recent publications span topics from algorithmic accountability to ethical black boxes in robotics, reflecting a strong trend toward integrating ethical considerations into the technical design of AI and interactive systems. These works emphasize participatory design, transparency, and societal impact. Scientific Awards and Recognition: Named one of the Brilliant Women working in AI Ethics She actively supervises and co-supervises students, contributes to ethics education, and is involved in outreach and diversity initiatives at Oxford. She has also served on the Departmental Equality and Diversity Committee and the Research Ethics Committee. Helena is a member of the advisory board for the ReEnTrust project and continues to develop the ethical hackathon model with colleagues. Her work exemplifies a deep commitment to interdisciplinary, socially responsible research in computing.

• Cybersecurity
• Electronic Identity
• Network Security
• +7 more

Antonio Lioy is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin. He serves as the Cyber Security Representative for the university in national and European government collaborations, is a member of the SmartData@PoliTO interdepartmental center, and acts as Scientific Advisor for the DRIVESEC partnership. His research is deeply rooted in cybersecurity, electronic identity, network and web security, and quantum-resistant systems. His research interests focus on cybersecurity , electronic identity , network security , web security , and quantum cryptography . He leads the TORSEC Security Group and conducts research in LAB 7, with a strong emphasis on trusted computing, post-quantum cryptography, IoT security, and secure network infrastructures. His work aligns with ERC sectors in computer systems and cryptology, and supports UN SDGs on innovation and sustainable cities. His recent publications show a strong trend toward post-quantum cryptography , remote attestation , trusted execution environments , and secure network virtualization . These works appear in top venues such as IEEE, ACM, and IFIP conferences, with a focus on securing future digital infrastructures against emerging threats. Themes include integrity management in softwarized networks, standard-based attestation, and quantum-resistant PKI strategies. He has supervised numerous PhD students, including Davide Colaiacomo, Francesco Vaccaro, Flavio Ciravegna, Grazia D'Onghia, Lorenzo Ferro, Francesco Settanni, Enrico Bravi, Silvia Sisinni, Luca Mannella, and Ignazio Pedone, whose research spans cybersecurity, quantum computing, and IoT. He leads multiple high-profile research projects such as Q-FENCE, QUBIP, SERICS, and FISHY, funded by Horizon Europe and national programs, demonstrating significant grant acquisition and leadership. He is actively involved in research labs and teams, primarily the TORSEC - Security Group (DAUIN) and LAB 7 - Research Laboratory (DAUIN) , which focus on applied cybersecurity research. His projects often involve collaboration with industry and government bodies, emphasizing real-world impact in secure digital identity, critical infrastructure protection, and quantum-safe transitions.

• Probabilistic Machine Learning
• Bayesian Models
• Statistical Inference
• +12 more

Luigi Acerbi is an Associate Professor in the Department of Computer Science at the University of Helsinki, where he leads the Machine and Human Intelligence research group. He is also an active member of the Finnish Center for Artificial Intelligence (FCAI) and ELLIS (European Laboratory for Learning and Intelligent Systems). His research focuses on probabilistic machine learning and computational neuroscience, particularly on developing efficient methods for statistical inference, Bayesian models of perception, and resource-constrained rationality. His work bridges machine learning and cognitive science, with applications in Bayesian optimization, simulation-based inference, and image completion. The recent publications highlight a strong trend toward unifying probabilistic conditioning across diverse tasks using transformer-based meta-learning frameworks like the Amortized Conditioning Engine (ACE). These works emphasize amortized inference, flexible latent variable modeling, and the integration of prior knowledge at runtime, enabling efficient and scalable Bayesian methods for complex problems. Scientific Affiliations: University of Helsinki, Department of Computer Science Finnish Center for Artificial Intelligence (FCAI) ELLIS (European Laboratory for Learning and Intelligent Systems) Education: PhD in Computational Neuroscience, Doctoral Training Centre, Edinburgh, UK Advisor: Sethu Vijayakumar and Daniel Wolpert Visiting work at Computational and Biological Learning Lab, Cambridge Postdoctoral Experience: Alex Pouget’s lab, University of Geneva, Switzerland Wei Ji Ma, New York University, USA Collaboration with the International Brain Laboratory Luigi Acerbi mentors PhD students including Daolang Huang and Nasrulloh Loka, and collaborates widely with researchers such as Samuel Kaski. He has contributed to open-source tools like PyVBMC and is involved in community initiatives such as the EurIPS conference. His work is supported by grants from the Research Council of Finland, Business Finland, and the UKRI Turing AI World-Leading Researcher Fellowship. He leads a research lab focused on amortized probabilistic inference, with ongoing projects including PriorGuide and Stacked VBMC, aiming to make Bayesian methods more practical and accessible for real-world scientific and engineering applications.