Find Academic Supervisors

Santiago FigueiraView profile

Professor

• Theoretical computer science
• Computability theory
• Algorithmic randomness
• +8 more

Santiago Figueira is a Professor at the Department of Computer Science, Faculty of Exact and Natural Sciences, University of Buenos Aires, and a Researcher at the Institute of Computer Science (ICC), CONICET (Argentine National Council for Scientific and Technical Research) in Buenos Aires, Argentina. He leads the Logic, Language and Computability Research Group (GLyC) and co-directs the Argentinian-French Laboratory SINFIN, a collaborative initiative between Université Paris-CNRS and Universidad de Buenos Aires-CONICET. Additionally, he is a researcher in the Quantum Information, Computation, and Communication team (QuICC). Dr. Figueira's research spans theoretical computer science with a strong emphasis on computability theory, algorithmic randomness, Kolmogorov complexity, and mathematical logic. His work extends to applications in database theory, quantum information, and cognitive modeling. He has made significant contributions to modal logics, model theory, and the theory of databases, particularly in the context of data trees and XPath query languages. His interdisciplinary approach bridges formal methods with practical applications in quantum computing and human cognition. His publication record demonstrates a consistent trajectory of high-impact research, with recent work focusing on modal logic extensions, quantum information theory, cognitive modeling of concept learning, and database query languages. His collaborations span international institutions, particularly with French researchers through the SINFIN laboratory, and with cognitive scientists studying human memory and concept formation. Dr. Figueira has supervised numerous PhD students and postdoctoral researchers, including Gabriel Goren-Roig, Santiago Cifuentes, Edwin Pin Baque, Sergio Romano, Gabriel Senno, and Sergio Abriola. His former postdocs and CONICET researchers include Guido Bellomo, María Emilia Descotte, and Ariel Bendersky, indicating an active and productive research group. He has developed lecture notes in Spanish on Logic and Computability (2020) and Computability Theory (2021), contributing to academic education in his field. His research group GLyC serves as a hub for theoretical computer science research in Argentina, fostering collaborations between Argentine and international researchers.

• Computational Physics
• Density Functional Theory (DFT)
• Atomistic Simulations
• +9 more

Jaakko Akola is a Professor in the Department of Physics at the Norwegian University of Science and Technology (NTNU). His research focuses on computational materials science, particularly density functional theory (DFT) and atomistic simulations of materials, nanoparticles, molecules, and interfaces. He leads significant projects such as "SIDI" (inoculation in cast iron), "Infinity-RETIS" (chemical rare events), and "AllDesign" (rational alloy design), alongside coordinating EU-funded initiatives like "CritCat" for catalyst development. The Materials Theory group under Akola employs DFT, molecular mechanics, and Monte Carlo methods to explore atomic-scale structures and functions in technological applications. Key research areas include platinum-free catalysts for hydrogen energy, amorphous semiconductors for memory devices, noble metal nanoparticles in biological environments, and alloy design for cast iron and aluminum. Recent work integrates machine learning to advance theory-driven material design, reducing reliance on experimental trial-and-error. Akola's publications highlight advancements in hydrogen evolution catalysis, phase-change memory materials, and alloy precipitation. His projects often involve interdisciplinary collaborations with experimental teams. He teaches Quantum Physics 1 (FY2045) and Computational Physics (TFY4235) at NTNU, reflecting his commitment to education alongside research.

Koray AydinView profile

Associate Professor

• Nanophotonics
• Optical Metamaterials
• Plasmonics
• +6 more

Koray Aydin is an Associate Professor in the Electrical and Computer Engineering department at Northwestern University 's McCormick School of Engineering. His research focuses on nanophotonics , optical metamaterials , and inverse design of photonic devices. PhD in Physics, Bilkent University MS and BS in Physics, Bilkent University The Metamaterials and Nanophotonic Devices Lab (MNDL) explores light-matter interactions at the nanoscale. Key research areas include: Plasmonic materials and devices for absorption engineering Metasurfaces for subwavelength light control Two-dimensional materials in optoelectronics 3D printing of millimeter-wave and optical metadevices Hybrid and tunable nanophotonic systems Dynamic metamaterials via self-assembly His publications highlight inverse design methodologies, DNA-assembled metasurfaces , and active nanophotonic materials . Collaborations with Chad Mirkin, Vinayak Dravid, and Prem Kumar have led to breakthroughs in scalable photonic systems and programmable metamaterials. Current efforts in MNDL aim to integrate machine learning with nanophotonic device design, enabling non-intuitive geometries and ultra-compact optical components with applications in telecommunications, defense, and consumer electronics.

Johanna UllrichView profile

Professor

• Network Security
• Critical Infrastructure Security
• IPv6 Security
• +4 more

Johanna Ullrich is a Professor at the University of Vienna's Faculty of Computer Science and a Key Researcher at SBA Research in Vienna. She leads the Research Group Communication Technologies and serves as Head of the Networks and Critical Infrastructures Security Group at SBA Research. Her academic journey includes positions as Principal Investigator & Manager of Third Party Funded Projects at the University of Vienna and Post-Doctoral Researcher at the Christian Doppler Laboratory for Security and Quality Improvement in the Production System Lifecycle. Her educational background includes a PhD sub auspiciis praesidentis in Computer Science from TU Wien (2013-2016), an MSc in Automation Engineering from TU Wien (2010-2013), and a BSc in Electrical Engineering from TU Wien (2007-2010). She also holds a Venia Docendi for Computer Engineering from the University of Vienna. Ullrich's research focuses on the intersection of computer science and classical engineering, with particular emphasis on network security, IPv6 measurement experiments, and critical infrastructure protection. Her groundbreaking work demonstrated vulnerabilities in the IPv6 Privacy Extension that led to modifications in major client operating systems, protecting millions of users. She is renowned for her research on cyber-physical attacks against power grids, showing how coordinated load attacks can destabilize electrical infrastructure. Her work spans both theoretical security frameworks and practical implementations with significant real-world impact. Her publication record reveals a consistent trajectory from fundamental network security research toward increasingly complex interdisciplinary investigations at the boundary of computer science and physical infrastructure. Recent work emphasizes AI/ML applications for network security, power grid resilience, and socio-technical approaches to cybersecurity. Her research demonstrates a progression from protocol-level security (IPv6) to system-level security (cloud, IoT) and now to infrastructure-level security (power grids, critical national infrastructure). 2nd in the Faculty of Computer Science's Best-of-the-Best Ranking 2024 Category Third Party Funding Nomination for the Hedy Lamarr Prize 2019 and 2020 Scholarship of Excellence 2018 Research Prize of the Dr. Maria Schaumayer Foundation 2018 Promotio Sub Auspiciis Praesidentis 2017 Diploma Thesis Award of the City of Vienna 2013 Ullrich actively contributes to the academic community through extensive grant acquisition and service. She has secured numerous research projects including SPyCoDe (Semantic and Cryptographic Foundations of Security and Privacy by Compositional Design), DynAISEC (Adaptive AI/ML for Dynamic Cybersecurity Systems), and Q-Crit (Quantum-Safe Critical Infrastructure for Austria). Her leadership extends to committee roles including Program Committee Member of IEEE Symposium on Security and Privacy (S&P) 2024 and Technical Program Chair of Network Traffic Measurement and Analysis Conference (TMA) 2023. At SBA Research, she leads the Networks and Critical Infrastructures Security Group, which investigates security challenges at the intersection of digital networks and physical infrastructure. The group conducts both theoretical research on security frameworks and practical measurements of real-world systems. Their work combines network measurement techniques with power systems engineering to develop comprehensive security approaches for critical infrastructure.

• Wireless Communications
• MIMO Systems
• Neuromorphic Computing
• +4 more

Dr. Juan Carlos De Luna Ducoing is a Research Fellow at the University of Surrey, specializing in advanced wireless communication systems with a focus on MIMO (Multiple-Input Multiple-Output) technologies. His work integrates neuromorphic computing, quantum annealing, and non-linear processing to enhance the efficiency and scalability of next-generation wireless networks. Research Interests: MU-MIMO detection and precoding Neuromorphic computing applications Quantum computing in wireless systems 6G network architectures Non-linear signal processing Hardware-software co-design (e.g., SWORD platform) Key Publications: His recent work includes NeuroMIMO (2024), which explores neuromorphic principles for power-efficient MU-MIMO detection, and Scalable MU-MIMO User Scheduling (2023), addressing resource allocation in dense networks. He also contributed to quantum annealing-based detection (2022) and Gyre Precoding (2021), achieving significant SNR gains. Collaborations: Works closely with Konstantinos Nikitopoulos and the SWORD research team to develop open-source platforms for rapid prototyping of advanced communication systems.

Alex AlvaradoView profile

Professor

• Optical Communications
• Wireless Communications
• Information Theory
• +3 more

Alex Alvarado is a Full Professor in the Signal Processing Systems department at Eindhoven University of Technology (TU/e), leading the Information and Communication Theory Lab (ICT Lab). He is also affiliated with TU/e's Center for Wireless Technology in Eindhoven. His academic career includes roles as a Senior Research Associate at University College London (2014–2016), Marie Curie Intra-European Fellow (2012–2014), and Newton International Fellow (2011–2012) at the University of Cambridge. Alvarado is a Senior Member of the IEEE and has held editorial and committee positions in major conferences like OFC and ECOC. Alvarado holds an Electronics Engineer degree (2003) and MSc (2005) from Universidad Técnica Federico Santa María, Chile, followed by a Licentiate of Engineering (2008) and PhD (2011) from Chalmers University of Technology, Sweden. His research focuses on high-speed secure data transmission in optical and wireless systems, emphasizing energy-efficient algorithms and theoretical limits of telecommunication systems. Key areas include communication theory, information theory, optical fiber systems, and nonlinear interference mitigation. His recent articles explore advanced modulation formats, machine learning applications for channel estimation and decoding, and innovations in free-space optics and MIMO systems. This work contributes to UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and responsible consumption through energy-efficient communication solutions. Scientific Awards: ERC Starting Grant (2018) NWO VIDI Grant (2016) 2015 Journal of Lightwave Technology Best Paper Award 2015 IEEE Exemplary Reviewer Award 2018 and 2023 Asia Communications and Photonics Conference Best Paper Awards 2019 Optoelectronics and Communications Conference Best Paper Award Alvarado's advising contributions include supervising 12 research works. His grants include NWO VIDI and ERC Starting funding. He leads projects like NESTOR (Next-gen optical networks) and LaiQa (Quantum Key Distribution). His lab, the ICT Lab, drives theoretical and applied research in communication systems.

• Power Systems
• Smart Grids
• Renewable Energy Integration
• +3 more

Prof. Ferdinanda Ponci is a Professor at RWTH Aachen University, leading the Department of Monitoring and Distributed Control for Energy Systems. Her work focuses on smart grid technologies, renewable energy integration, and control systems for modern power networks. She actively contributes to advancing grid resilience, EV charging infrastructure, and cybersecurity in energy systems. Key research interests include hybrid AC-DC grids, distributed energy resources coordination, and application of AI in grid management. She has pioneered frameworks like datafev for EV charging management and SMU platforms for synchronized measurements. Her interdisciplinary approach also addresses diversity in engineering and societal impacts of energy systems. Prof. Ponci’s laboratory activities involve hardware-in-the-loop testing, blockchain-based grid solutions, and development of educational toolboxes for emerging technologies. She collaborates on projects such as submarine transmission systems and grid interoperability testing, contributing to both academic and industrial advancements in power systems engineering.

Stefano MartinianiView profile

Assistant Professor

• Computational and Statistical Physics
• Materials Science
• Artificial Intelligence for Science
• +5 more

Stefano Martiniani is an Assistant Professor of Physics, Chemistry, Mathematics, and Neuroscience at New York University, affiliated with the Center for Soft Matter Research and the Simons Center for Computational Physical Chemistry. His interdisciplinary research explores computational physics of complex systems, including neural circuit theories, non-equilibrium statistical mechanics, and AI-driven materials discovery. He has pioneered methods for analyzing high-dimensional energy landscapes and received prestigious awards like the NSF CAREER Award (2024) and IUPAP Early Career Prize (2023). Education: PhD in Physics (2017), University of Cambridge MPhil in Physics (2013), University of Cambridge BSc in Physics (2012), Imperial College London Research Interests: His work bridges statistical physics and artificial intelligence, focusing on: Engineering disordered materials with tailored spectral properties Quantifying entropy production in active matter Developing open science frameworks like ColabFit for machine learning interatomic potentials Neural circuit models for cortical communication Grants & Collaborations: Funded by NSF, NIH, Chan Zuckerberg Initiative, and Simons Foundation. Leads interdisciplinary teams in computational physics, AI, and materials science. Labs/Initiatives: Core member of NYU's Center for Soft Matter Research; develops software tools like FReSCo and KLIFF-Torch for computational materials science.

Alison RodgerView profile

Professor

• Biophysical Chemistry
• Physical Chemistry
• Analytical Science
• +3 more

Prof Alison Rodger is a Professor in the Research School of Chemistry at The Australian National University, where she leads research in biophysical spectroscopy. Formerly at Macquarie University (2017–2024) and the University of Warwick (1990s–2017), she specializes in developing advanced spectroscopic techniques for biomacromolecule analysis. Her work integrates circular dichroism, linear dichroism, and Raman methods to study nucleic acids, proteins, and membrane systems. She co-directs the ARC-funded Industrial Transformation Training Centre in Facilitated Advancement of Australia’s Bioactives (FAAB) and runs an open-access biophysical spectroscopy lab. Key awards include Fellowships from the Australian Academy of Science (2021) and Royal Society of Chemistry (2000), and recognition in the Analytical Science Power List (2015). Education: BSc, PhD, DSc (Sydney University) MA (Oxford) DSc (Warwick) BA (Chester) Research Interests: Development of polarized-light spectroscopies for biomacromolecule analysis, including electronic/circular dichroism, Raman spectroscopy, and hybrid techniques. Applications span protein-DNA interactions, membrane biophysics, and biopharmaceutical characterization. She invented five spectroscopic techniques, including micro-volume Couette flow linear dichroism and fluorescence-detected linear dichroism. Awards & Roles: Fellow of the Australian Academy of Science Fellow of the Royal Society of Chemistry Emeritus Professor (University of Warwick) Recipient of Science Teachers of NSW Dedicated Service Award Consultant to European Science Foundation CASPER project Advising & Grants: Supervises PhD students in interdisciplinary biophysical chemistry. Led the EPSRC-funded Molecular Organisation and Assembly in Cells DTC at Warwick. Currently co-directs the ARC FAAB Centre, focusing on bioactive product characterization. Labs & Collaborations: Operates an open-access biophysical spectroscopy lab supporting academic and commercial users. Collaborations span mathematics, medicine, and engineering, with projects on DNA knotting, antimicrobial peptides, and nanomaterials for biosensing.

Tommaso CalarcoView profile

Professor

• Quantum Optimal Control
• Quantum Computing
• Quantum Technologies
• +3 more

Tommaso Calarco serves as Director of the Institute for Quantum Control (PGI-8) at Jülich Research Centre, leading cutting-edge research in quantum optimal control methodologies for next-generation quantum technologies. His work focuses on developing transformative computational frameworks applicable to natural sciences, logistics, and high-performance computing through advanced quantum device engineering. His research spans quantum optimal control for computation and many-body systems, emphasizing physical model development, model reduction techniques, and machine learning integration for scalable quantum hardware. Key focus areas include spin-qubit optimization, diamond quantum register engineering, and error suppression in gate operations, with significant contributions to ultracold atom systems and semiconductor-based quantum platforms. Analysis of his 2024-2025 publications reveals concentrated efforts on hardware-specific challenges across multiple quantum modalities: spin shuttling fidelity in semiconductor systems, gate optimization for nitrogen-vacancy centers, and photon-spin interface engineering. This work demonstrates a unifying thread of optimal control solutions tailored to platform-specific decoherence mechanisms and scalability constraints. As Director of PGI-8 within the Peter Grünberg Institut, Calarco oversees a dedicated research team advancing quantum control theory and applications, contributing substantially to European quantum technology roadmaps including the Quantum Flagship initiative and strategic European Commission reports.

Himanshu JainView profile

Professor

• Glass Science and Technology
• Photonics
• Nanomaterials
• +5 more

Dr. Himanshu Jain is the T.L. Diamond Distinguished Chair in Engineering and Applied Science and a Professor of Materials Science & Engineering at Lehigh University. He leads the International Materials Institute for New Functionality in Glass and previously directed the Institute for Functional Materials and Devices (I-FMD). His research focuses on advancing glass science through innovations in photonics, bioactive materials, crystal engineering, and laser processing. Education: D.Eng.Sc., Materials Science, Columbia University M.Tech., Indian Institute of Technology (India) M.S., Banaras Hindu University (India) B.S., Kanpur University (India) Research Interests: Laser-induced single-crystal architectures in glass Optical and electronic functionalities in glass Biomedical applications of bioactive glass (e.g., bone scaffolds) Thermal and radiation effects on glass properties Machine learning for crystal growth modeling Awards: Recipient of Otto Schott Research Prize for atomic fluctuation models Zachariasen Award for lithium transport discovery Morey Award for defining new glass science horizons Fulbright and Humboldt Fellowships Advising & Grants: Has supervised numerous students and secured grants for interdisciplinary projects. Active in collaborative initiatives like the Lehigh-NC A&T flood damage mapping partnership. Labs/Teams: Oversees Lehigh's advanced materials facilities, including Sinclair Lab 120A. Coordinates global networks for glass science education and research.

Chunming QiaoView profile

Professor

• Cyber-Physical Systems
• Optical Networks
• Wireless Networks
• +6 more

Dr. Chunming Qiao is a SUNY Distinguished Professor and Chair of the Department of Computer Science and Engineering at the University at Buffalo (SUNY) , leading the Lab for Advanced Network Design, Evaluation and Research (LANDR) since 1993. His work spans cyber-physical systems , optical networks , and Internet of Things (IoT) , with a focus on safety, reliability, and protocol design. Education: PhD in Computer Science from the University of Pittsburgh (1993) BS in Computer Science and Engineering from the University of Science and Technology of China (1985) Dr. Qiao’s research interests combine theoretical and applied network design, including autonomous vehicles , quantum computing , and cloud services . He pioneered optical burst switching (OBS) and iCAR systems for wireless convergence, cited in BusinessWeek and Wireless Europe . His recent publications emphasize quantum networking , federated learning , and autonomous driving security , with projects on entanglement routing , edge inference optimization , and LiDAR adversarial attacks . Articles span IEEE and ACM venues , and include best paper awards . Scientific Awards: TC-CSR Distinguished Technical Achievement Award (2015) SUNY Chancellor's Award for Excellence (2013) IEEE Fellow (2009) UB Exceptional Scholar-Sustained Achievement Award (2005) Dr. Qiao has secured over two dozen NSF grants and collaborations with Google , Cisco , and NEC Labs . His 7 US patents and consulting experience highlight his industry impact, while his editorial roles and conference leadership underscore academic influence. He actively contributes to multi-disciplinary research through the New York State Center of Excellence in Bioinformatics and Life Sciences and CEDAR , advancing high-performance computing and document analysis .

Domenico CiuonzoView profile

Assistant Professor

• Information Fusion
• Statistical Signal Processing
• Wireless Sensor Networks
• +9 more

Dr. Domenico Ciuonzo is an Assistant Professor at the University of Naples Federico II , Department of Electrical Engineering and Information Technologies. His research focuses on Information Fusion , Statistical Signal Processing , Wireless Sensor Networks , Network Analytics , Artificial Intelligence , and Wireless Communications . He actively explores applications in deep learning , encrypted traffic classification , and IoT security . His recent work emphasizes explainable AI , quantum machine learning , and class incremental learning for network intrusion detection. Over 30+ publications span topics like decision fusion in MIMO systems , mobile app traffic analysis , and cybersecurity for IoT . He is also involved in dataset development (e.g., MIRAGE-APP× ACT-2024) and algorithmic frameworks for encrypted traffic classification . Key research trends include: Optimizing holographic communication systems and reconfigurable intelligent surfaces for wireless networks Developing attack-adaptive intrusion detection systems resilient to emerging threats Advancing quantum computing applications in network monitoring and prediction His research integrates statistical signal processing with modern AI techniques , addressing challenges in data privacy , network security , and resource-constrained environments .

• Materials Science
• Corrosion Engineering
• Electrochemistry
• +5 more

Prof. Robert Meißner is a Professor at the Department of Surface Physics and Technology at TUHH. His research focuses on molecular simulation techniques applied to corrosion processes, energy storage systems, and nanomaterials. He develops computational tools like ELECTRODE and i-PI for electrochemical and advanced molecular dynamics simulations. His work addresses challenges in magnesium battery performance, structural health monitoring of composite materials, and interfacial phenomena in nanoscale systems. Education details are not explicitly provided in the text, but his professional trajectory reflects extensive academic and industrial experience in materials science. Research interests span from fundamental studies (e.g., water imbibition in nanopores, magnetite oxidation dynamics) to applied innovations (e.g., corrosion protection via layered double hydroxides, data-driven electrolyte design). His recent publications highlight trends in data-driven materials discovery, structural health monitoring via vibro-acoustic methods, and computational prediction of corrosion inhibitors. He collaborates on projects involving graphene-based supercapacitors, epoxy resin curing dynamics, and peptide-surface interactions. Advising and grants: While student names are not listed, his research group actively explores corrosion engineering, battery technology, and nanomaterials. Projects include EU-funded initiatives and industry partnerships. Technical expertise includes ATR-FTIR spectroscopy, molecular dynamics, and machine learning for sparse data scenarios. He leads teams focused on surface science and energy storage, maintaining lab facilities for in situ electrochemical analysis and advanced computational modeling. His work bridges theoretical insights with practical applications in materials durability and energy systems.

• Cybersecurity
• Internet of Things (IoT)
• Blockchain Technology
• +3 more

Yuan Liu is a faculty member affiliated with Guangzhou University's Cyberspace Institute of Advanced Technology. Their research focuses on cybersecurity, blockchain technology, federated learning, and IoT systems. They have held roles at multiple institutions, including Northeastern University (Software College) and Nanyang Technological University (PhD in Computer Engineering). Liu's work emphasizes secure communication, edge computing, and distributed systems, with contributions to protocols like blockchain-based redactable systems and quantum federated learning frameworks. They have collaborated extensively on projects addressing IoT security, smart healthcare, and privacy-preserving technologies. Key research trends include leveraging AI for enhanced security (e.g., watermarking frameworks, attack detection) and optimizing resource allocation in edge computing environments. Their publications span journals like IEEE Communications Surveys & Tutorials and conferences such as GLOBECOM.