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Lu ZhangView profile

Assistant Professor

• Numerical Analysis of Partial Differential Equations (PDEs)
• Discontinuous Galerkin Methods
• Computational Mathematics
• +5 more

Lu Zhang is an Assistant Professor in the Department of Computational Applied Mathematics and Operations Research at Rice University. She joined Rice in 2023 after serving as the Ju Tang Chu and Wu Ping Chu Assistant Professor at Columbia University's Department of Applied Physics and Applied Mathematics. Zhang holds a Ph.D. in computational and applied mathematics from Southern Methodist University (2020) and has conducted summer research at Argonne National Laboratory (2018) and Lawrence Livermore National Laboratory (2019). Her research focuses on numerical and theoretical analysis of partial differential equations (PDEs), particularly developing high-order discontinuous Galerkin methods for PDEs with physical and biological applications. Key areas include advective wave equations, seismic imaging, chemotaxis models, population dynamics, and inverse problems. Her work emphasizes energy-stable, computationally efficient algorithms and their theoretical underpinnings. Zhang's recent publications (2021–2024) explore advanced numerical methods for wave equations, electromagnetic systems, and elastic media, with applications in geophysics, structural mechanics, and crime modeling. Her methods address challenges in high-order accuracy, stability, and computational efficiency across diverse scientific domains. No scientific awards or grants are explicitly mentioned in the provided text. She currently advises no listed students but has extensive experience in collaborative research through national laboratory partnerships.

Jakob ZechView profile

Professor

• Uncertainty Quantification
• High-Dimensional Approximation
• Sparse-Grid Techniques
• +4 more

Jakob Zech is a Professor at the Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg University since April 2020. Before this, he held postdoctoral positions at MIT (2019-2020) and ETH Zürich (2018-2019). He earned his PhD in Mathematics from ETH Zürich in 2018, focusing on Sparse-Grid Approximation of High-Dimensional Parametric PDEs, followed by a Master’s (2014) and Bachelor’s (2012) in Applied Mathematics from ETH Zürich and TU Wien, respectively. Research Interests : Zech’s work bridges Uncertainty Quantification (UQ), high-dimensional approximation, and computational mathematics. Key areas include sparse-grid techniques, neural networks, transport methods, Bayesian inverse problems, and the theoretical foundations of deep learning. His research emphasizes developing algorithms for stochastic modeling and analyzing their mathematical properties. Teaching : He has taught advanced courses such as High Dimensional Approximation, Theory of Deep Learning, and Numerical Methods for Bayesian Inverse Problems at Heidelberg University. He also served as a teaching assistant for numerous courses at ETH Zürich, covering numerical analysis, partial differential equations, and linear algebra. Publications : His recent work explores quantum computing applications in polynomial chaos expansions, statistical learning theory for neural operators, and multilevel optimization strategies. His articles reflect a strong focus on combining classical numerical methods with modern machine learning techniques. Labs/Teams : While no specific lab is mentioned, his research group is active in computational UQ and deep learning, collaborating internationally with institutions like MIT and ETH Zürich.

Ping LamView profile

Professor

• Quantum Communication
• Quantum Memory
• Laser Levitation
• +3 more

Prof. Ping Lam is a Professor in the Department of Quantum Science & Technology at Australian National University (ANU), serving as an ARC Laureate Fellow (2015). His research focuses on quantum communication, quantum memory, laser levitation, squeezed light, quantum sensing, and metrology. He holds a BSc from the University of Auckland and MSc/PhD from ANU. His work spans theoretical and experimental quantum technologies, with contributions to quantum key distribution protocols, entanglement purification, and quantum state manipulation. Notable projects include the ARC Centre of Excellence for Quantum Computation and Communication Technology and collaborations on optical levitation systems and photothermal effects in resonators. Research Interests: Quantum communication, quantum memory, laser levitation, squeezed light, quantum sensing, and metrology. Awards: ARC Laureate Fellow (2015). Key Projects: Includes quantum levitation of macroscopic systems, cryogenic imaging facilities, and satellite-based quantum communication. Recent articles emphasize advancements in quantum metrology, continuous variable systems, and machine learning applications in quantum optics. His work bridges fundamental quantum physics with practical applications in secure communication and precision measurement.

Chaohao ChenView profile

Research Fellow

• Nanophotonics
• Biophotonics
• Optical Super-resolution Imaging
• +5 more

Dr. Chaohao Chen is a Research Fellow in the Department of Electronic Materials Engineering at The Australian National University (ANU), within the ANU College of Science. His research focuses on nanophotonics, biophotonics, and super-resolution microscopy, with a particular emphasis on developing optical nonlinear nanomaterials and on-chip sensing technologies. He holds a PhD in Applied Physics from the University of Technology Sydney (2020) and has led research groups in nanophotonics, contributing over 20 peer-reviewed publications in top journals such as Nature Communications and Advanced Materials. Education: PhD in Applied Physics, University of Technology Sydney (2020); Prior qualifications unspecified. Research Interests: Dr. Chen specializes in advancing super-resolution imaging techniques, including laser-free on-chip microscopy and THz sensors for skin cancer diagnosis. His work integrates nanomaterials engineering, optical systems design, and biomedical applications. Recent projects include multiplexed biosensors, quantum emitter stability, and ghost imaging with UV light. Awards: None explicitly listed. Advising & Grants: No students listed; his research is supported by projects such as the ANU-led super-resolution microscopy initiative under Prof. Lan Fu. Collaborations span institutions like UTS and international partners in quantum materials research. Labs & Teams: Active in the ANU Research School of Physics and former leadership of UTS’s nanophotonics research group. Current projects include developing single-pixel imaging systems and THz biomedical diagnostics.

Alessandro ScagliottiView profile

Researcher

• Optimal Control
• Machine Learning
• Deep Learning
• +3 more

Alessandro Scagliotti is a Researcher at the Department of Mathematics, Technical University of Munich (TUM), affiliated with the School of Computation, Information and Technology. His research focuses on Optimal Control with applications to Machine Learning, particularly exploring dynamical models for Residual Neural Networks and large-scale training dataset analysis, alongside accelerated convex optimization methods. His academic contributions span theoretical advancements in control systems applied to neural networks, quantum state transfers, and biomedical applications like drug resistance management in cancer therapies. His work bridges mathematical rigor with practical machine learning challenges, emphasizing robustness and scalability. Recent publications highlight innovative approaches in neural ODEs, minimax optimization, and ensemble control systems, reflecting a strong interdisciplinary orientation. Collaborations are evident through topics like quantum dynamics and biomedical modeling. Email: scag@ma.tum.de | Office: 02.08.033 | Phone: +49 (89) 289-17467

• Photonics
• Nanophotonics
• Biosensors
• +3 more

Aleksandrs Leitis is a former researcher at the School of Life Sciences (École Polytechnique Fédérale de Lausanne) with expertise in photonics, nanophotonics, and biosensing. His work focuses on dielectric metasurfaces, mid-infrared photonics, and MEMS-based optical systems. Leitis has contributed to advancements in programmable Huygens' metasurfaces, wafer-scale functional metasurfaces, and AI-enhanced biosensing technologies. His research integrates MEMS fabrication with optical engineering to create innovative platforms for spectroscopy and molecular detection. Key research interests include optical wavefront manipulation, broadband sensing, and vibrational light-matter coupling. Leitis collaborates with institutions like the European Research Council and National Yang Ming Chiao Tung University on projects involving mid-IR photonics and surface-enhanced spectroscopy. Notable achievements include developing angle-multiplexed metasurfaces for molecular fingerprinting and gradient high-Q resonators for infrared absorption spectroscopy. His articles highlight trends in MEMS-optical hybrid systems, programmable phase control, and AI-driven sensor optimization. Leitis has pioneered wafer-scale fabrication techniques for functional metasurfaces, enabling scalable mid-IR photonics applications. Earlier work explored cold atom optical pumping effects in sodium and cesium beams.

Isabel Nha Minh LeView profile

Researcher

• Quantum Algorithms
• Quantum Chemistry
• Tensor Network Methods
• +3 more

Isabel Nha Minh Le is a Researcher and doctoral candidate in the Quantum Computing Group under Prof. Mendl at the Technische Universität München (TUM). She holds a B.Sc. and M.Sc. in Physics from RWTH Aachen University, specializing in Quantum Technologies. Her research focuses on quantum algorithms for quantum chemistry, tensor network methods, and quantum machine learning. She teaches tutorials and seminars on quantum computing and ethics. Her work includes advancements in Riemannian quantum circuit optimization and symmetry-invariant quantum ML force fields, presented at conferences such as ICFO-IMPRS Joint Workshop and APS Global Summit. She is affiliated with the Department of Computer Science at TUM School of CIT, with an office at SAP Labs Munich. Education: B.Sc. in Physics, RWTH Aachen University M.Sc. in Physics, RWTH Aachen University Research Interests: Development of quantum algorithms for simulating complex quantum systems Integration of tensor networks and machine learning for quantum simulation Optimization techniques for quantum circuits Teaching Roles: Tutorial Leader: Introduction to Quantum Computing (2023–2025) Seminar Leader: Advanced Topics of Quantum Computing (2023–2025) Seminar Leader: Science & Ethics (2024–2025) Labs/Teams: Member of the Quantum Computing Group at TUM, collaborating with Prof. Mendl's team on quantum algorithms and applications.

Kirill KovnirView profile

Professor

• Solid-state chemistry
• Materials chemistry
• Thermoelectric materials
• +5 more

Kirill Kovnir is a Professor of Chemistry at Iowa State University (ISU), affiliated with the U.S. DOE Ames Laboratory. He holds a Ph.D. in solid-state chemistry, with postdoctoral research at the Max Planck Institutes and Florida State University. His career includes roles at UC Davis before moving to ISU in 2017, where he was promoted to Professor in 2022. Research Focus: Synthesis and characterization of energy materials, including thermoelectrics, superconductors, magnetic materials, and catalytic systems. Emphasis on structure-property relationships in novel compounds. Key Contributions: Developed methods for synthesizing clathrate frameworks, pioneered studies on Zintl phases, and advanced predictive synthesis approaches. Notable for work on Ba-Cu-P clathrates and selenium activation chemistry. Awards: Fellow of the Royal Society of Chemistry (2017), ISU Mid-Career Achievement in Research Award (2022), and numerous grants from NSF and DOE. His lab integrates computational modeling with experimental synthesis, collaborating widely on projects such as machine learning-guided materials discovery and nanocrystal synthesis.

Jenny Y YangView profile

Professor

• Inorganic Chemistry
• Organometallic Chemistry
• Electrochemistry
• +5 more

Jenny Y. Yang is a Professor at the University of California, Irvine (UCI) , Department of Chemistry, with a research focus on Inorganic, Organometallic, and CO2 Reduction Chemistry . As a Chancellor's Fellow and Associate Editor of the Journal of the American Chemical Society , she leads cutting-edge research in electrochemical carbon capture, hydrogen evolution, and sustainable catalysis. Director of the $10.35M DOE-funded Center for Closing the Carbon Cycle (4C) Co-authored ChemBioChem and Chemical Reviews publications on electrochemical CO2 capture Her work explores transition metal hydrides , proton coupled electron transfer , and steric effects on catalytic selectivity , with applications in renewable energy and climate solutions. Notable Scientific Awards: Sloan Research Fellow (2018) Camille Dreyfus Teacher-Scholar Award (2019) NSF CAREER award (2015) DOE Early Career Research Award (2014) She mentors a diverse team of PhD students , postdoctoral scholars , and undergraduate researchers , with trainees receiving NSF GRFP , DOE SCGSR , and UC Presidential Postdoctoral Fellowships .

Claire GmachlView profile

Professor

• Quantum Cascade Lasers
• Optics
• Semiconductor Engineering
• +3 more

Claire Gmachl is the Eugene Higgins Professor of Electrical Engineering at Princeton University, serving as the Associate Chair of the Department of Electrical and Computer Engineering and Head of Whitman College. She is affiliated with the High Meadows Environmental Institute (HMEI) as an Associated Faculty member and contributes to the Grand Challenges Program. Her roles emphasize leadership in both academic administration and cutting-edge research. Her research interests focus on quantum cascade lasers, optics, semiconductor engineering, and their applications in optical sensors for environmental and health monitoring. Notably, she explores hyperuniform semiconductor metamaterials, wireless power systems for lasers, and machine learning-driven approaches to optimize laser design. Recent work highlights advancements in mid-infrared spectroscopy for non-invasive glucose sensing and novel cavity geometries for laser stability and efficiency. Her research outputs demonstrate a strong emphasis on interdisciplinary innovation, particularly at the intersection of machine learning and optoelectronics. Articles from 2022-2025 reveal trends in developing robust quantum cascade laser systems and exploring their use in precision applications like medical diagnostics and environmental sensing. While no scientific awards are listed, her contributions to the field are evident through collaborations with HMEI and Whitman College. Her advising and grant activities are not explicitly detailed in the text. She leads research in labs focused on metamaterials, semiconductor lasers, and sensor technologies, contributing to both the School of Engineering and the broader university community through her administrative roles.

Mamoun AlazabView profile

Professor

• Cyber Security
• Data Analytics
• Digital Forensics
• +7 more

Professor Mamoun Alazab is a full Professor and Inaugural Director of the NT Academic Centre for Cyber Security and Innovation (ACCI) at Charles Darwin University. His expertise spans cyber security, data analytics, and digital forensics with a focus on AI-driven solutions for cybercrime detection and privacy preservation. Research Interests: Malware authorship attribution, adversarial AI, access control systems in CPS/IoT, cyber criminology, and privacy-preserving machine learning. He has secured ~A$16.7M in research funding and published over 300 top-tier papers (90% in top 10% journals), 11 books, and holds 3 patents. Editorial Roles: IEEE Transactions on Computational Social Systems, ACM Digital Threats: Research and Practice Professional Activities: Founding Chair of IEEE NT Subsection, convened 200+ conferences Awards: Clarivate Highly Cited Researcher (2022), Top 2% Global Scientists (2020–2022), and multiple IEEE leadership awards. Labs/Teams: Leads ACCI, collaborates on projects like Cyber Territory Skills Hub and CVE: Countering Violent Extremism Research.

William K. EstesView profile

Professor

• Mathematical Psychology
• Learning Theory
• Cognitive Science
• +3 more

William K. Estes was a distinguished Professor and Distinguished Scholar of Psychology and Cognitive Science at Indiana University. He was a foundational figure in mathematical psychology, known for the Stimulus Sampling Theory and contributions to learning and memory research. Estes held academic positions at Indiana University, Stanford, Rockefeller University, and Harvard before becoming a Professor Emeritus at Indiana University. His work emphasized statistical and computational approaches to understanding psychological phenomena. Estes' research focused on mathematical psychology, learning theory, and cognitive science. He pioneered statistical models to explain learning processes, such as stimulus-response associations. His theories bridged behaviorist and cognitive approaches, influencing fields like neuroscience and educational research. Awardees of the National Medal of Science (1997), Warren Medal (1963), and the APA Gold Medal (1992), Estes' legacy includes the William K. and Katherine W. Estes Fund, supporting quantitative and computational research in psychology. His work remains central to understanding human cognition and learning mechanisms.

• Quantum Physics
• Theoretical Physics
• Quantum Simulation
• +4 more

Prof. Dr. Hendrik Weimer is a Group Leader at the Institute of Theoretical Physics within the Faculty of Mathematics and Physics at Leibniz University Hannover. His research focuses on quantum simulation, entanglement, and topological quantum phenomena. Position: Professor Institution: Leibniz University Hannover Department: Institute of Theoretical Physics His work explores quantum phase transitions , multipartite entanglement , and topological order in driven-dissipative systems. Recent studies emphasize error correction for quantum simulations and dissipative state preparation using Rydberg atoms. Key trends in his publications include quantum computing , topological materials , and non-equilibrium quantum dynamics . His research often bridges quantum information theory with condensed matter physics .

Hari Priya RavindranView profile

Assistant Professor

• Mathematical Biology
• Optimal Control Theory
• Computational Biology
• +6 more

Hari Priya Ravindran is an Assistant Professor in the Department of Mathematical Sciences at Middle Tennessee State University (MTSU). She holds a doctoral student status at the École Polytechnique Fédérale de Lausanne (EPFL) in Materials Science and Engineering. Her research focuses on mathematical biology, optimal control theory, computational biology, and applications in epidemiology, oncology, and quantum computing. She leads the NSF-funded REU Site on Computational Modeling and has organized interdisciplinary conferences such as the SIMIODE EXPO and CUGH satellite sessions on AI ethics in global health. Her educational background includes advanced studies in mathematical modeling and systems biology. She has received grants from the NSF and MTSU for projects like the ADVANCE IT-Catalyst initiative to promote women in STEM. Her work integrates machine learning, differential equations, and quantum computing to address challenges in healthcare, environmental management, and disease control. Ravindran’s research spans topics such as malaria control, tumor growth modeling, and AI-driven ASD classification. She collaborates internationally, including with institutions in China and Canada, and has published widely in journals like AIMS Mathematics and Journal of Biological Dynamics .

Philip KimView profile

Professor

• Condensed Matter Physics
• Quantum Engineering
• Nanoscale Materials
• +7 more

Philip Kim is a Professor of Physics and Applied Physics at Harvard University's School of Engineering and Applied Sciences (SEAS). His research focuses on experimental condensed matter physics, emphasizing nanoscale low-dimensional materials and their applications. Key areas include superconductivity, quantum engineering, graphene, and two-dimensional materials. His work explores electronic transport phenomena, thermoelectric properties, and quantum phase transitions in systems like twisted graphene heterostructures, van der Waals materials, and topological insulators. Recent studies investigate superfluidity, charge density waves, and spintronics in low-dimensional systems. Notable research trends include the manipulation of moiré lattices for novel electronic phases, machine learning-driven material characterization, and device engineering for quantum technologies. His lab develops advanced fabrication techniques for wafer-scale 2D materials and interfaces with applications in energy storage and optoelectronics. Awards and grants are not explicitly listed here, but his group's work has been featured in prominent journals and news outlets like the Harvard Gazette and EurekAlert. Ongoing projects include exploring heavy fermion behavior in van der Waals metals and tunable superconductivity in layered systems.