Find Academic Supervisors

• Carbon Nanotubes
• Graphene
• Two-Dimensional Materials
• +3 more

Professor Hui-Ming Cheng is a Vice Chancellor’s Fellow at the Advanced Technology Institute (ATI), Tsinghua University, and founding director of the Low-Dimensional Material and Device Laboratory at Tsinghua Shenzhen International Graduate School. He also leads the Advanced Carbon Research Division at the Shenyang National Laboratory for Materials Science, Chinese Academy of Sciences (IMR CAS). With a Ph.D. from IMR CAS (1992) and postdoctoral experience at Nagasaki University and MIT, he holds honorary professorships at the University of Queensland and UNSW. His research focuses on carbon nanotubes, graphene, 2D materials, energy storage, and photocatalytic materials. Over 770 publications, 150 patents, and awards like the State Natural Science Award (China) highlight his contributions. He has edited major journals and co-founded Energy Storage Materials. Recent work includes breakthroughs in battery recycling, high-performance photodetectors, and graphene-based catalysts. Education: B.Sc. (1984), Ph.D. (1992) from Hunan University and IMR CAS. Postdoctoral roles at Kyushu Institute of Technology (Japan), Nagasaki University, and MIT. Research interests span carbon materials, energy storage systems, and nanoelectronics. Notable achievements include ultra-stable battery cathodes, high-sensitivity phototransistors, and efficient hydrogen evolution catalysts. His work on lithium-sulfur batteries and MXene films addresses scalability and sustainability challenges. Publications emphasize 2D materials, photocatalysis, and energy storage technologies. Awards reflect his global impact in materials science. He advises on grants and leads international collaborations, advancing materials innovation for next-gen technologies.

Alberto DainottiView profile

Associate Professor

• Internet Measurement
• Cybersecurity
• Data Science
• +6 more

Alberto Dainotti is an Associate Professor at the School of Computer Science, College of Computing, Georgia Institute of Technology (Georgia Tech), and Director of the Internet Intelligence Lab. His research focuses on Internet measurement, data science, and cybersecurity, with a particular emphasis on infrastructure reliability and socio-political implications of cyber events. Before joining Georgia Tech in 2014, he served as an Associate Research Scientist and Principal Investigator at CAIDA (Center for Applied Internet Data Analysis) at UC San Diego. He holds a Ph.D. in Computer Engineering and Systems from the University of Napoli 'Federico II', Italy (2008). He teaches courses such as Internet Data Science (CS 8803), Computer Networking I (CS 3251), and Computer Networks/Networking II (CS 6250/4251). Current students include Feng Zhu, Iliana Xygkou, Olivier Bemba, Weili Wu, Zahra Yazdani, and Zhiyi Chen. Former advisees have transitioned to roles at Amazon AWS Research, Northeastern University, UC Davis, Microsoft Azure, and VMware, among others. Research Interests: Internet Connectivity Outages & Mitigation BGP Routing Security & Monitoring Cybersecurity in Political Contexts Address Space Utilization DDoS/Botnet Analysis Network Measurement Tools Scientific Contributions: Developed systems like IODA, BGPStream, and GRIP for real-time Internet monitoring Recipient of the IRTF Applied Networking Research Prize (2012, 2017) Awarded Best Dataset (PAM 2022) and Best Community Artifact (PAM 2023) Authored over 50 publications in top venues including SIGCOMM, IMC, and NSDI Grants & Funding: National Science Foundation (NSF) grants CNS-1705024 / 2202288 and CNS-1703592 US Department of Homeland Security Cisco Systems, Comcast, ISOC, Google, and Open Technology Fund Labs & Collaborations: Internet Intelligence Lab (Georgia Tech) CAIDA collaboration (UC San Diego) MAPKIT project with University of Wisconsin-Madison Contributor to OECD and BITAG reports on routing security

• Quantum Computing
• Quantum Gases
• Atomic Physics
• +4 more

Servaas Kokkelmans is a Full Professor and leader of the Coherence and Quantum Technology group in the Department of Applied Physics at Eindhoven University of Technology (TU/e). He is also the scientific director of the Center for Quantum Materials and Technology Eindhoven (QT/e) and co-founder of the Eindhoven Hendrik Casimir Institute. His research focuses on strongly-interacting quantum gases, neutral atom quantum computing, and ultracold atomic systems. He holds a PhD from TU/e (2000) after postdoctoral work at JILA (USA) and Laboratoire Kastler Brossel (France). Notable roles include coordinating action line 1 (Research & Innovation) at Quantum Delta NL and leading the KAT-1 project on Rydberg atom quantum computing. Awards include the NWO Vici (2015) and Vidi (2003) grants. Education: MSc (1996) and PhD (2000) in Physics from TU/e. Career progression: Assistant Professor (2004–2017), Associate Professor (2017–2023), Full Professor (2023–present). Key research areas include quantum computing architectures, ultracold collisions, Feshbach resonances, and Efimov physics. Active in teaching courses like Quantum Optics and Quantum Information, and Hybrid Quantum Computing. Research highlights include foundational work on quantum control via electric/magnetic fields and contributions to quantum simulation platforms. His work spans experimental and theoretical studies, with over 249 publications and 51 supervised works. Collaborations involve institutions globally. Media engagements include interviews on quantum technology advancements and leadership roles in national quantum initiatives.

• Materials Science
• Waste Management
• Resource Efficiency
• +3 more

Chris Cheeseman is a Professor of Materials Resources Engineering at the Department of Civil and Environmental Engineering, Imperial College London. He leads the Materials Section and directs the UKCRIC Centre for Infrastructure Materials, funded by EPSRC. His expertise lies in materials science applied to sustainability, including waste management, circular economy, and low-carbon materials. He holds affiliations with multiple interdisciplinary centers, including the Grantham Institute and the Marine and Coastal Environments Network. Chris earned his PhD in ceramics science from the University of Oxford, followed by industry experience as a Technical Manager. At Imperial since 1990, he has supervised over 120 graduate students and published 220+ papers. His research emphasizes innovation, spawning spin-off companies like Novacem (low-carbon cements) and Aeropowder (waste feather applications). Key research themes include carbon sequestration via olivine, magnesium-based cements, and recycling of industrial byproducts. His work bridges material science with environmental engineering, addressing global challenges like climate change and resource efficiency. Recent articles focus on novel cements, waste valorization (e.g., sewage sludge ash), and sustainable construction materials. Collaborative projects include EPSRC-funded infrastructure initiatives and collaborations with industry on permeable pavements and superhydrophobic surfaces. Chris has pioneered curricula in advanced materials for sustainable infrastructure and environmental engineering. His labs focus on material lifecycle analysis, industrial symbiosis, and scalable low-carbon solutions.

Bettina KemmeView profile

Professor

• Distributed Systems
• Cloud Computing
• Database Systems
• +5 more

Bettina Kemme is a Professor in the School of Computer Science at McGill University, Montreal, Canada. She leads the Distributed Information Systems Lab (DISL) and specializes in large-scale data management, distributed systems, and cloud computing. Her academic roles include teaching COMP 512 (Distributed Systems) and COMP 421 (Database Systems). Education: Diplom (M.Sc. equivalent) in Computer Science, Friedrich-Alexander University, Erlangen, Germany (1996) PhD in Computer Science, Swiss Federal Institute of Technology (ETH), Zurich, Switzerland (2000) Research Interests: Distributed systems, cloud-native data management, in-database analytics (AIDA project), monitoring-as-a-service frameworks, and scalable pub/sub systems for online games. Current projects focus on integrating machine learning with databases, cloud performance monitoring using SDN, and sustainable data systems for data science. Lab & Collaborations: Leads the Distributed Information Systems Lab (DISL) with active projects in distributed databases, cloud computing, and game systems. Collaborates on EU-Canada initiatives like the SustainSys program for sustainable data infrastructure. Advising: Supervises PhD and M.Sc. students in topics like monitoring frameworks (Mona ElSaadawy), in-database ML (Winnie He), and distributed systems (Maximilian Schiedermeier). Alumni include over 50 researchers from PhD candidates to undergraduate researchers.

Lorenzo SaniView profile

Researcher

• Federated Learning
• Edge Computing
• Privacy-Preserving Machine Learning
• +3 more

Lorenzo Sani is a PhD student in the Department of Computer Science and Technology at the University of Cambridge, supervised by Prof. Nicholas D. Lane and part of the CaMLSys research group. His work focuses on federated learning, edge computing, and privacy-preserving machine learning algorithms for large-scale distributed systems. Education: He holds a Bachelor's Degree in Physics from the University of Bologna (2019) and a Master's Degree in Applied Physics from the same institution (2021), with a thesis on unsupervised clustering of MDS data using federated learning. During his studies, he contributed to the GenoMed4All project and collaborated with the CaMLSys group on the Flower Framework. Research Interests: Sani's research emphasizes optimizing federated learning efficiency, privacy in distributed machine learning, and the application of federated techniques to large language models. His work addresses challenges in communication efficiency, client collaboration, and ethical data usage in decentralized systems. Teaching: He serves as a Teaching Assistant for the Principles of Machine Learning Systems (L46) and Federated Learning: Theory and Practice (L361) courses, and supervises students at Jesus College for Algorithm and Artificial Intelligence modules. Publications: His recent work includes innovations in federated optimization (DES-LOC, SparsyFed), LLM unlearning (LUNAR), and global federated training systems (Photon, Worldwide federated training). The 2020 Flower Framework paper established a foundational research tool for federated learning experimentation.

Alan EdelmanView profile

Professor

• Julia Programming
• High Performance Computing
• Linear Algebra
• +3 more

Alan Edelman is a Professor at the Massachusetts Institute of Technology (MIT), renowned for his work in high-performance computing, linear algebra, and random matrix theory. He is a co-creator of the Julia programming language, which emphasizes efficiency and versatility for scientific computing. His research integrates mathematics and computer science, focusing on numerical methods, parallel computing, and applications in fields like quantum control and climate modeling. Edelman leads projects such as Oceananigans.jl for geophysical fluid dynamics and Circuitscape for connectivity analysis in conservation biology. His academic contributions span theoretical advancements in matrix theory and practical implementations of computational tools. Edelman collaborates across disciplines, bridging scientific computing with machine learning and quantum physics. His work on differentiable programming frameworks and GPU acceleration has impacted both academic research and industry applications. Key Projects: Julia programming language, Oceananigans.jl, Circuitscape Research Themes: High-performance computing, numerical linear algebra, random matrices, scientific machine learning Affiliations: MIT’s Theory of Computation Community of Research, PI of multiple NSF-funded projects Edelman’s recent work emphasizes interdisciplinary applications, including climate policy modeling and automated materials discovery. His publications reflect a blend of foundational mathematics and cutting-edge computational techniques.

Guillaume A SARTORETTIView profile

Assistant Professor

• Robotics
• Multi-Agent/Multi-Robot Systems
• Distributed/Decentralized Control
• +4 more

Guillaume A SARTORETTI is an Assistant Professor in the Mechanical Engineering Department at the National University of Singapore (NUS), part of the College of Design and Engineering. He specializes in distributed/decentralized coordination of multi-agent systems, with a focus on robotics, stochastic modeling, and reinforcement learning. His work spans applications in multi-robot systems, articulated robots, and swarm intelligence. Joined NUS in 2019 after a postdoctoral fellowship at Carnegie Mellon University (CMU) and a PhD from EPFL. Education: PhD in Robotics (EPFL, 2016); MSc and BSc in Mathematics/Computer Science (University of Geneva). Research interests include: Multi-agent pathfinding Decentralized control policies Swarm intelligence Reinforcement learning applications in robotics Recent publications emphasize scalable solutions for multi-agent systems, traffic signal control, and safe robotic exploration. His 2018 MFI postdoctoral fellowship recognized work on distributed reinforcement learning for pathfinding. Current projects involve bio-inspired locomotion and collaborative learning frameworks for heterogeneous robots.

Helen N. SchwerdtView profile

Assistant Professor

• Neuroscience
• Bioengineering
• Materials Science
• +6 more

Helen N. Schwerdt is an Assistant Professor in the Department of Bioengineering at the University of Pittsburgh, affiliated with the Swanson School of Engineering and the Center for the Neural Basis of Cognition (CNBC). Her research focuses on developing implantable tools for probing electrical and chemical neural activity, with a particular emphasis on long-term monitoring in both rodents and primates. Key areas include dopamine signaling in Parkinson’s disease, neural interface design, and chronic neural recording systems. Her lab’s work spans interdisciplinary fields such as bioengineering, materials science, and neuroscience. Notable contributions include scalable carbon fiber electrode arrays for neurochemical monitoring and wireless passive neurorecording systems. Schwerdt’s team collaborates extensively, addressing challenges in neural prosthetics and translational neuroscience. Recent research highlights include the 2023 publication on rodent neurochemical arrays and 2020 studies on dopamine and motor control in primates. The lab actively recruits students and postdoctoral researchers across disciplines, emphasizing training in microfabrication, electrophysiology, and computational neuroscience.

Andrea SottorivaView profile

Professor

• Cancer Evolution
• Computational Biology
• Genomics
• +4 more

Andrea Sottoriva is the Head of the Computational Biology Research Centre at Human Technopole , Milan, Italy, and holds the title of Professor of Cancer Genomics and Evolution . His work bridges computational biology, evolutionary theory, and clinical oncology to predict cancer progression and design adaptive treatment strategies. University of Bologna – BSc in Computer Science (2006) University of Amsterdam – MSc in Computational Sciences (2008) University of Cambridge – PhD in Computational Biology (2012) Dr. Sottoriva's research focuses on cancer evolution , applying machine learning and population genetics to decode tumor heterogeneity through multi-omics data. His lab integrates patient-derived organoids and spatial genomics to understand how genetic and epigenetic factors drive cancer progression. The 15 most recent publications demonstrate a consistent emphasis on subclonal dynamics (7/15), computational methods (6/15), and evolutionary modeling (5/15). Key themes include adaptive mutability in colorectal cancer , immune editing in post-transplantation relapses, and deep learning applications for tumor heterogeneity. Scientific recognition includes: Cancer Research UK Future Leaders in Cancer Research Prize (2016) His lab currently trains PhD students and postdoctoral researchers in computational oncology, maintaining a living biobank of patient-derived models while pioneering AI-mechanistic hybrid models for clinical translation.

Manos KapritsosView profile

Associate Professor

• Distributed Systems
• Formal Verification
• Fault-Tolerant Replication
• +3 more

Manos Kapritsos is an Associate Professor in the Department of Computer Science & Engineering at the University of Michigan, Ann Arbor. His research focuses on increasing the reliability of distributed systems through formal verification, fault-tolerant replication, and automated proof techniques. He has contributed to projects such as Aegean (replication beyond client-server models), I4 (automated inductive invariant inference), and Armada (concurrent code verification). His work emphasizes practical applications of formal methods to ensure system correctness and performance. Education details are not explicitly provided in the text, but his career trajectory suggests advanced academic training in computer science. His research interests include distributed systems, formal verification of protocols, and high-performance systems. Notable awards include the NSF CAREER Award (2021), Google Faculty Award (2017), and Distinguished Paper Awards at PLDI 2020 and USENIX Security 2017. Teaching includes courses on formal verification, operating systems, and distributed systems, reflecting his expertise in systems software. He has advised students through his GLaDOS research group, though specific advisee names are not listed. Key grants include NSF FMitF and Large grants to advance verification techniques for distributed systems. Recent articles focus on automating proofs for undecidable protocols (Basilisk), efficient replication communication (Scrooge), and formal latency analysis (Performal). His work bridges theory and practice, aiming to simplify end-to-end verification of complex systems.

• Edge Computing
• Fog Computing
• Cloud Computing
• +7 more

Riccardo Lancellotti is an Associate Professor at the Department of Engineering 'Enzo Ferrari' of the University of Modena and Reggio Emilia. His research focuses on Edge/Fog/Cloud Computing, Cyber Security, and Resource Management in distributed systems. He has extensive contributions in optimizing infrastructure performance, load balancing, and energy efficiency in cloud and fog environments. His work often combines theoretical models with practical simulations, addressing challenges like stale information in edge systems and heterogeneous resource allocation in smart cities. Key research areas include: Fog/Edge computing infrastructure design and optimization Cloud resource provisioning and SLA compliance Security for Industry 4.0 and automotive systems Genetic algorithms for service placement Scalable VM clustering and resource allocation Publications highlight trends in cloud/fog integration, robust game theory for microservices, and distributed load balancing under dynamic conditions. His work emphasizes practical applications, such as pharmaceutical distribution routing and smart city sensor management. No awards are explicitly listed, but his extensive publication record reflects recognition in the field.

• Computer Operating Systems
• Computer Systems Analysis
• Distributed Systems
• +5 more

Liuba Shrira is a Professor of Computer Science at Brandeis University, affiliated with the Michtom School of Computer Science and the Benjamin and Mae Volen National Center for Complex Systems. Her research focuses on distributed systems, storage systems, blockchain technology, concurrent programming, and system architectures. She holds a Ph.D., M.S., and B.S. from the Technion – Israel Institute of Technology. Her work emphasizes reliable and highly available systems, including innovations in snapshot management, transactional memory, and adversarial cross-chain commerce. She has been recognized with awards such as the ACM Distinguished Scientist (2009), Lady Davis Fellowship (2010-2011), and a Best Paper Award (2020). Her research has been supported by grants from the National Science Foundation and other institutions. Recent publications highlight advancements in optimistic concurrency control, blockchain interoperability, and modular past-state systems. Shrira has also contributed to middleware design and distributed computing frameworks, with applications in both academic and industry settings.

Raja GhoshView profile

Professor

• Bioengineering
• Membrane Technology
• Biopharmaceutical Processing
• +3 more

Raja Ghosh is a Professor in the Department of Chemical Engineering at McMaster University's Faculty of Engineering. His research focuses on bioengineering and polymer materials, with specialization in membrane technology for biopharmaceutical applications. He is actively involved in the Health & Bio-innovation research cluster and teaches courses such as CHEM ENG 3BM3: Bioseparations Engineering and CHEM ENG 782: Biopharmaceuticals . Research Interests include membrane chromatography device design, bioseparations process development, membrane bioreactors for enzymatic and protein applications, and therapeutic protein stabilization. His work addresses scalable purification methods for monoclonal antibodies, PEGylated proteins, and viral vectors. Recent Publications highlight innovations in cuboid chromatography design, pH-modulated ion-exchange systems, and SARS-CoV-2 spike protein purification. He employs computational fluid dynamics (CFD) simulations to optimize device performance and reduce pressure drops in bioseparation processes. Contact Information : Email: rghosh@mcmaster.ca Office: JHE A408 Phone: 905-525-9140 ext. 27415

Wonbong ChoiView profile

Professor

• Materials Science
• Energy Storage
• Nanomaterials
• +3 more

Dr. Wonbong Choi is a University Distinguished Research Professor at the University of North Texas with joint appointments in the Department of Materials Science and Engineering and Mechanical Engineering. His research focuses on nanomaterials, energy storage systems (particularly lithium-sulfur and zinc-ion batteries), additive manufacturing of composites, and neuromorphic computing devices. He was elected Fellow of the National Academy of Inventors in 2024 for his contributions to materials innovation. Research interests span materials synthesis, electrochemical characterization, and device integration of 2D materials like MXenes and transition metal dichalcogenides. Key areas include: Nanomaterial design for batteries and supercapacitors 3D-printed sensors and structural composites Defect engineering for neuromorphic computing His recent publications highlight consistent themes in MXene synthesis optimization, advanced battery architectures, and multifunctional composites. Article trends show increasing focus on in situ characterization, scalable manufacturing of nanomaterials, and AI-driven materials design. Awards: Fellow, National Academy of Inventors (2024) Collaborates with research groups at Oak Ridge National Laboratory and leads projects on lightweight composites and energy storage systems.