جستجوی استاد راهنمای دانشگاهی

George Britovsekمشاهده پروفایل

استاد

• Catalysis
• Sustainable Carbon Management
• Transition Metal Complexes
• +۳ مورد دیگر

Professor George Britovsek (FRSC) is a leading figure in catalysis and sustainable carbon management at Imperial College London . As Director of the MRes in Catalysis & Engineering and Head of Teaching in Inorganic Chemistry, he bridges academic leadership with cutting-edge research. His work focuses on transition metal complexes for converting ethylene , alkanes , biomass , and CO₂ into valuable chemicals and fuels through industrial collaborations. Education : M.Sc. (Technical University of Aachen, 1990), Ph.D. (Aachen, 1993) under Prof. W. Keim Postdoctoral Training : University of Tasmania (1994-1996), Imperial College London (1996-2000) His research interests span: Selective oxidation of alkanes using bio-inspired iron complexes Alkene conversions to functional polymers via novel catalysts CO₂ valorization into polymers and cyclic carbonates Biomass-derived feedstocks for chemical synthesis Recent catalysis trends highlight his work on: Designing Fe-N/C catalysts for epoxidation Developing PN3P pincer ligands for H₂ activation Creating degradable polyethylene via iron-catalyzed chain growth Modeling alternating α-olefin distributions in chromium systems Awards : Fellow of the Royal Society of Chemistry (FRSC) Students & Collaborators actively engage in: Photocatalytic polymer degradation Electrocatalytic CO₂ conversion Functionalized polymeric materials 3D-printed catalytic scaffolds His Britovsek Research Group operates at the Molecular Sciences Research Hub, White City Campus, advancing both homogeneous and heterogeneous catalysis through experimental and computational approaches.

Stefan Huberمشاهده پروفایل

استاد

• Organocatalysis
• Supramolecular Chemistry
• Halogen Bonding
• +۶ مورد دیگر

Prof. Dr. Stefan Huber is a Full Professor (W3) at the Faculty of Chemistry and Biochemistry , Ruhr-Universität Bochum , Germany. His research focuses on non-covalent interactions in organocatalysis , particularly halogen bonding , chalcogen bonding , and cyclopropenium derivatives for applications in molecular recognition , crystal engineering , and radical stabilization . Full Professor since 01/2022 Associate Professor (W2) 2014-2021 Independent Researcher at TU Munich 2009-2013 Research Interests include: Design of halogen/chalcogen bond donors for catalysis Supramolecular chemistry in solution and solid phases Quantum chemical modeling of transition states and binding strengths His work bridges experimental synthesis (NMR, X-ray, ITC) with computational methods , supported by the ERC Starting Grant (2015-2020) and collaborations within the RESOLV Cluster . Scientific Awards : Hoechst Dozentenpreis (2016) Robert-Sauer-Preis (2014) Hans-Fischer-Gedächtnispreis (2013) Ernst-Otto-Fischer-Lehrpreis (2012) Thieme Chemistry Journals Award (2010) Students : Over 20 Ph.D. and Master’s students, including Dominik Reinhard, Tim Steinke, Raffaella Papagna, and Julian Stoesser. The group maintains modern synthesis labs and collaborates with institutions like the University of Geneva and TU Munich .

Luca Fredianiمشاهده پروفایل

استاد

• Theoretical and Computational Chemistry
• Density Functional Theory (DFT)
• Multiwavelet Methods
• +۴ مورد دیگر

Luca Frediani is a Professor in Theoretical and Computational Chemistry at the Hylleraas Center, Department of Chemistry, UiT The Arctic University of Norway. His research focuses on advanced quantum chemistry methods, including density functional theory, multiwavelet basis sets, and solvation modeling. He actively develops computational tools like MRChem and VAMPyR for molecular electronic structure calculations. Current affiliation: UiT The Arctic University of Norway Research group: Theoretical and Computational Chemistry Teaching: KJE-2001 Theoretical Chemistry and Spectroscopy His work spans relativistic quantum chemistry, numerical methods for response properties, and benchmarking of basis set limits. Publications emphasize eliminating basis set errors, multiwavelet applications, and polarizable continuum models for solvation. He collaborates extensively on software development for quantum chemistry. Recent articles highlight multiwavelet-based DFT at the basis set limit, noise-tolerant force calculations, and relativistic effects in electronic structure. Sub-fields include scalar relativity, cavity-free solvation, and metal-ligand interaction accuracy.

• Digital signal processing
• Smart grids
• Measurement systems
• +۵ مورد دیگر

David Macii is Associate Professor at the Department of Industrial Engineering, University of Trento, Italy, where he teaches "Digital Signal Processing for Mechatronics" and co-leads the "Laboratory of Internet of Things." His core expertise lies in digital signal processing, measurement science, smart-grid instrumentation, indoor positioning and industrial IoT applications. Research interests revolve around four pillars: (i) advanced estimation algorithms for frequency, ROCOF and synchrophasors to enhance power-quality monitoring in future smart-grids with high PV and EV penetration; (ii) design and metrological characterisation of low-cost PMU and smart-meter solutions; (iii) radar- and RFID-based indoor localisation and tracking for robotics and assisted-living scenarios; and (iv) embedded, IoT-enabled measurement systems bridging DSP, mechatronics and industrial electronics. Recent publications (2023-2025) reveal a clear methodological trend: development of fast, uncertainty-aware DSP algorithms (interpolated DFT, Kalman filtering, harmonic whitening) validated against real-world noise, interference and contingency conditions, followed by their embedding into resource-constrained hardware platforms for EV charging coordination, grid-support converters and robotic navigation. Although the supplied text does not list specific grants or doctoral students, the steady stream of joint publications with European colleagues and his leading teaching role in two inter-departmental master courses indicate an active, well-integrated research and educational profile within the University of Trento.

Carolin Müllerمشاهده پروفایل

استادیار

• Computational Chemistry
• Molecular Dynamics
• Machine Learning
• +۷ مورد دیگر

Carolin Müller is a Juniorprofessor for the Theory of Electronically Excited States at the Friedrich-Alexander University Erlangen-Nuremberg since November 2023. Previously, she was a Feodor Lynen Postdoctoral Researcher at the University of Luxembourg (June 2022-October 2023) and a Postdoctoral Researcher at Friedrich Schiller University Jena (March 2021-May 2022). Dr. Müller received her B.Sc. (2016) and M.Sc. (2018) in Chemistry from Friedrich Schiller University Jena, followed by her Ph.D. (Dr. rer. nat) in 2021 from the same institution. Her doctoral research focused on "Towards Operando Spectroscopy of Supramolecular Photocatalysts – A Case Study on Ru-dppz-derived Systems" under the supervision of Prof. B. Dietzek-Ivanšić. Dr. Müller's research focuses on the theoretical understanding of photoinduced processes in molecules and materials. Her group (CPC Group) investigates electron transfer processes, isomerization reactions, and excited-state dynamics with the goal of controlling and optimizing light-driven processes for increased reactivity and efficiency. Her work combines computational chemistry, spectroscopy, and machine learning approaches, specifically utilizing methods like TD-DFT, CASSCF, molecular/quantum dynamics, and cheminformatics techniques including SVD, MCR, and global/target lifetime analysis. Her recent publications demonstrate a strong interdisciplinary approach spanning computational chemistry, spectroscopy, and machine learning. Key themes include nonadiabatic molecular dynamics, excited-state simulations, photoswitch design, photocatalysis, and the development of computational tools like KiMoPack for kinetic modeling. Her work often bridges theoretical predictions with experimental validation through close collaboration with spectroscopy research groups. Feodor Lynen Research Fellowship (Alexander von Humboldt Foundation) Thuringian Research Award 2023 for Applied Research Albert-Weller Award (German Chemical Society) Dissertation Award (Faculty of Chemistry and Earth Sciences) FCI Kekulé PhD fellowship As a Juniorprofessor, Dr. Müller leads the CPC Group at FAU, where she mentors students in computational chemistry research. She has developed expertise in combining spectroscopic techniques (resonance Raman, transient absorption, and time-resolved emission spectroscopy) with computational methods and cheminformatics approaches. She also actively contributes to the scientific community through service roles including co-organizing the ESTML 2023 Workshop and serving as an active member in the yPC organization of the German Bunsen Society. Dr. Müller is actively developing the CPC Group research program at the Computer Chemistry Center, focusing on light-induced physical processes and chemical reactions. Her group combines quantum chemistry, chemoinformatics, and experimental spectroscopy to reveal mechanisms behind photoinduced phenomena and optimize light-driven processes.

• Quantum Chemistry
• Computational Photochemistry
• Spectroscopy
• +۳ مورد دیگر

Prof. Tadeusz Andruniów serves as a full Professor at the Institute of Advanced Materials within the Faculty of Chemistry at Wrocław University of Science and Technology. His research program integrates quantum chemical methodologies with photobiological systems, focusing on light-induced processes in biological chromophores. With continuous publication output from 2004 to 2025, he maintains an active research trajectory evidenced by contributions to high-impact journals including the Journal of the American Chemical Society and Proceedings of the National Academy of Sciences. His core research interests encompass: Quantum Chemistry of Biological Systems Photoisomerization Dynamics in Rhodopsin Resonance Raman Spectroscopy Two-Photon Absorption Phenomena Protein-Chromophore Interactions Computational Photobiology These interests drive his investigations into excited-state behavior, energy storage mechanisms, and spectroscopic signatures of chromophores in complex biological environments. Analysis of his 2020-2025 publications reveals three dominant research thrusts: (1) Precision modeling of two-photon absorption in rhodopsin and fluorescent protein chromophores using high-level coupled-cluster methods; (2) Elucidation of protein environmental effects on spectroscopic properties through QM/MM simulations; and (3) Extension of computational frameworks to abiotic systems like sequence-defined polyurethanes. His work consistently demonstrates methodological innovation in handling excited-state dynamics and nonlinear optical properties. While specific grant details and student supervision records are not documented in available sources, his collaborative publication pattern involving international co-authors indicates active research networking. His technical contributions to computational protocols for artifact removal in polarizable embedding calculations and quantum region optimization represent significant methodological advances for the field.

• Computational Materials Science
• Machine Learning for Materials Predictions
• Metal-Organic Frameworks (MOFs)
• +۷ مورد دیگر

Felix Mayr is a researcher at the Technical University of Munich (TUM) under the Associate Professorship Simulation of Nanosystems for Energy Conversion in the TUM School of Computation, Information and Technology (SoCIT). His work focuses on computational materials science, particularly leveraging machine learning and density functional theory (DFT) for energy-related applications. Institution: Technical University of Munich Department: Simulation of Nanosystems for Energy Conversion Research Interests : Mayr investigates materials for solar cells, electrocatalysis, and gas adsorption using machine learning , DFT , and multiscale modeling . Key projects include optimizing MOF interfaces for PFAS removal and developing algorithms for adsorption site identification. Article Trends : His recent publications emphasize machine learning integration with materials science, targeting MOFs , perovskites , and electrocatalysts . Topics include PFAS remediation, charge prediction, and stability analysis. Projects & Collaborations : Mayr contributes to DFG e-Conversion Clusters (I-III), TUM Innovation Network ARTEMIS, EU Lion-Hearted, and BMWi ptj PrOperPhotoMiLe SOLAR.ERANET.

Federico Javier Hernándezمشاهده پروفایل

مدرس

• Computational Chemistry
• Photochemistry
• Photophysics
• +۵ مورد دیگر

Dr. Federico Javier Hernández serves as a Lecturer in Computational Chemistry at the Centre for Chemical Research within the School of Physical and Chemical Sciences at Queen Mary University of London. His expertise centers on computational photochemistry and photophysics, with emphasis on excited-state mechanisms in complex molecular environments including aggregates, organic crystals, and solution-phase systems. Hernández completed his undergraduate studies in Physical Chemistry at the University of Córdoba (UC), Argentina, followed by a hybrid experimental and theoretical-computational PhD in Chemistry jointly awarded by UC and the University of Quilmes under Professors Gustavo Pino and Juliana Palma. His doctoral research investigated photophysical and photochemical processes relevant to Atmospheric Chemistry and Biochemistry. His laboratory focuses on elucidating fundamental mechanisms behind phenomena such as aggregation-induced emission, radiative quenching, singlet fission, ultralong organic phosphorescence, charge/exciton transport, and thermally activated delayed fluorescence. These investigations employ advanced computational methodologies including plane-wave DFT, multiscale electronic structure methods (QM:QM' and QM:MM), nonadiabatic dynamics simulations (surface hopping and Ehrenfest dynamics), and machine learning integration for materials discovery. This work directly supports rational design of functional molecules for optoelectronic applications and energy storage/conversion technologies. Analysis of Hernández's 15 most recent publications (2022-2025) reveals consistent focus on nonadiabatic dynamics in condensed phases, excited-state mechanisms in molecular aggregates, and atmospheric reaction kinetics. Key trends include development of computational benchmarks for photochemical processes, application of machine learning to photodynamics, and investigation of polaritonic effects in vibrational spectroscopy. His work bridges theoretical chemistry with practical materials design for optoelectronics. No major scientific awards or fellowships are documented in the available information. While current PhD advisees are not listed, Hernández maintains an active research group within the Centre for Chemical Research. His collaborative network spans international institutions including University College London, University of Bristol, and University of Santiago de Chile. He contributes to academic instruction through CHE 209 – Introductory Programming for Chemists and leverages his ORCID profile (https://orcid.org/0000-0001-7497-9424) for scholarly identification. His research infrastructure integrates high-performance computing with data science approaches to tackle complex photochemical problems.

• Trustworthy computing
• Energy harvesting
• Intelligent system design
• +۷ مورد دیگر

Youhua Shi is a full Professor in the Faculty of Science and Engineering at Waseda University, Japan. He obtained his Doctor of Engineering from Waseda in 2005 and is an active member of IEICE, IPSJ, IEEE, and two Japanese academic societies. His research portfolio integrates trustworthy computing, hardware security of AI accelerators, energy-harvesting interface circuits for triboelectric nanogenerators, and low-power VLSI design-for-test methodologies. Education: Doctor of Engineering, Waseda University (2005) Graduate studies, Waseda University, Division of Engineering (completed 2005) Research Interests: Prof. Shi pursues trustworthy and secure silicon systems, spanning hardware Trojans in automated AI-accelerator flows, radiation-hardened latch design for soft-error resilience, and power-efficient CNN accelerators exploiting zero-gating and data-reuse techniques. Parallel work targets energy-autonomous IoT through advanced interface circuits for triboelectric nanogenerators, achieving record energy-per-cycle beyond the classical CMEO limit. Publication Trends: Recent articles (2024-2025) emphasize two thrusts: (i) security of AI/FPGA accelerators—proposing stealthy hardware-Trojan frameworks embedded within design-space-exploration flows that can misclassify up to 97% of inputs—and (ii) power electronics for triboelectric harvesters—introducing dual-output rectifiers and Bennet-doubler biasing that multiply output power >150× over conventional full-wave rectifiers, enabling battery-free IoT nodes. Scientific Awards: APCCAS Best Student Paper Award – 2020 IEEK Best Paper Award – 2012 Students & Collaboration: He has mentored numerous doctoral and master’s scholars, including Yirui Su, Chao Guo, Jinghao Ye, Lin Ye, Saki Tajima, and Masaru Oya, many of whom serve as first authors on his high-impact publications, indicating an active and productive advising role. Labs & Teams: While the text does not name a specific laboratory, his continued affiliation with Waseda University’s Faculty of Science and Engineering and his extensive project output imply he leads a research group focused on secure & energy-efficient VLSI systems, collaborating closely with colleagues such as Prof. Masao Yanagisawa and Prof. Nozomu Togawa.

Alex Whiteمشاهده پروفایل

مدرس ارشد

• Thermofluids
• Two-Phase Flow
• Thermodynamics
• +۶ مورد دیگر

Dr. Alex White is a Senior Lecturer in Thermofluids at the Department of Engineering, Cambridge University, and a Fellow and Director of Studies at Peterhouse. He earned his undergraduate and PhD degrees from King's College, Cambridge, and conducted postdoctoral research in Cambridge, Lyon, and Toulouse before returning to Cambridge in 2000 as part of the Energy Group. His research focuses on two-phase flow (vapour-droplet flows), thermodynamics of power generation, Computational Fluid Dynamics (CFD), and heat pumps. His work includes theoretical and numerical studies on warm dense matter, electron transport, and energy storage systems like pumped thermal and compressed air storage. Recent publications emphasize warm dense matter physics, inertial confinement fusion, and thermal energy storage innovations. His theoretical analyses and simulations span high-energy-density plasmas, nonlocal electron stopping power, and hybrid energy systems. While no scientific awards are documented, his contributions to thermofluids and extreme condition physics are significant.

Laura McKemmishمشاهده پروفایل

مدرس ارشد

• Quantum Chemistry
• Spectroscopy
• Astrochemistry
• +۷ مورد دیگر

Laura McKemmish is a Senior Lecturer at the School of Chemistry , University of New South Wales (UNSW), specializing in computational chemistry at the intersection of quantum chemistry , astrochemistry , and molecular spectroscopy . She leads the SciX Discovery program, which supports high school students in authentic research, and serves as Director of Research-Integrated and Work-Integrated Learning in UNSW Science, focusing on inclusive education and curriculum innovation. Education: PhD in Theoretical Chemistry, Australian National University (2015). Her research develops computational tools to model exoplanet atmospheres , molecular line lists , and quantum chemical calculations , with applications in astrophysics and terrestrial chemistry . She emphasizes scalable, sustainable models for embedding research and computational skills into education. Article Trends : McKemmish’s recent work focuses on exoplanetary molecular spectroscopy (e.g., VO, TiO, ZrO), quantum basis set optimization , and high-throughput computational chemistry to address challenges in atmospheric and astrochemical data. Scientific Awards : RACI Vicki Gardiner Advocacy Award (2024) RACI Chemical Education Citation (2024) NSW Young Tall Poppy Science Award (2022) UNSW Arc Science Research Supervisor Awards (2022, 2024) Marie Skłodowska-Curie Fellowship (2016–2018) She has secured significant grants, including the Australian Government Maker Projects Grant for regional STEM outreach and a Google Educators Grant for data science teacher training. Her teaching integrates Python, computational methods, and generative AI across undergraduate and honors levels.

Daniel R. Nascimentoمشاهده پروفایل

استادیار

• Theoretical Chemistry
• Computational Chemistry
• Quantum Chemistry
• +۸ مورد دیگر

Daniel R. Nascimento is an Assistant Professor and UMRF Research Professor in the Department of Chemistry at the University of Memphis. He received his PhD in Theoretical Physical Chemistry from Florida State University in 2017 and held postdoctoral positions at Georgia Tech and Pacific Northwest National Laboratory. BS in Chemistry, Federal University of Ouro Preto, Brazil (2013) MS in Chemistry, Florida State University (2015) PhD in Physical Chemistry, Florida State University (2017) His research focuses on quantum mechanical methods for light-matter interactions, particularly in X-ray spectroscopy , time-dependent DFT , and electronic structure theory . The group develops algorithms for core-level spectroscopies and confined environments like optical cavities. Recent publications (2024-2020) highlight his work on metal-ligand covalency , iSPECTRON software , and confined electric field modeling in transition metal complexes. Articles span TD-DFT benchmarks , resonant X-ray scattering , and nonlinear optical response . 2024 CAS Early Career Research Award The Nascimento Lab includes graduate students Sarah Pak, Muhammed Dada, and Nathaniel Gillispie. He has secured NSF CAREER and Collaborative grants for method development in Psi4 and NWChem software. His group collaborates with institutions like Stanford, University of Bologna, and SLAC National Accelerator Laboratory.

Bernd Meyerمشاهده پروفایل

استاد

• Computational Chemistry
• Materials Science
• Surface Chemistry
• +۶ مورد دیگر

Prof. Dr. Bernd Meyer is a Professor of Computational Chemistry at the Department of Chemistry and Pharmacy, Friedrich-Alexander University Erlangen-Nuremberg. His research bridges theoretical and experimental approaches to investigate nanomaterials, surface chemistry, and molecular dynamics. Computational Chemistry Materials Science Surface Stability Molecular Dynamics Nanomaterials Photovoltaics Organic-Inorganic Hybrids Recent publications focus on adsorption mechanisms of molecules on metal oxides, design of porphyrin-based hybrids with tunable optoelectronic properties, and algorithm optimizations for ab initio molecular dynamics. His work integrates first-principles simulations with experimental validation to address challenges in energy materials and surface engineering. Contact: bernd.meyer@fau.de | Room 2.308, Nägelsbachstraße 25, Erlangen | Phone: +49 9131 85-20403

• Computational Chemistry
• Quantum Chemistry
• Materials Science
• +۵ مورد دیگر

Robert O'Reilly is a Lecturer in Chemistry at the School of Science & Technology, University of New England. His research focuses on computational and theoretical chemistry, particularly in bond dissociation energies, quantum chemical modeling, and materials science for energy applications. Research Interests Computational Chemistry Quantum Chemistry Materials Science for Solar Energy Bond Dissociation Mechanisms Reaction Thermodynamics His work spans diverse areas such as homolytic bond dissociation, catalysis, and photovoltaic materials, with a strong emphasis on high-level quantum chemical studies and sustainable chemistry applications. Recent publications explore tailored composites for energy conversion and proton-coupled transfers in organic systems.

Ravindra Shindeمشاهده پروفایل

پژوهشگر

• Computational Materials Science
• Quantum Chemistry
• Exascale Scientific Computing
• +۵ مورد دیگر

Ravindra Shinde is a Research Scientist at the University of Twente , Netherlands, affiliated with the Computational Chemical Physics group under the Faculty of Science and Technology . He is also the founder of The Science Dev , a tech and research blog. Education : Ph.D. in Physics (2014) and M.Sc. in Physics (2009) from IIT Bombay, India. His research spans Exascale Scientific Computing , Quantum Chemistry , Time-Dependent DFT , and Topological Materials . He specializes in method development for quantum mechanical simulations and code modernization for high-performance computing . Recent publications focus on Exascale Computing challenges , Quantum Monte Carlo accuracy, and machine learning integration in force field modeling. Notable awards include SERB Postdoctoral Fellowship and multiple Best Presentation Awards . Scientific Awards : Best Poster Award, UC Riverside (2019) Best Presentation Awards, SERB 2018 & IISc 2018 National Postdoctoral Fellowship, India (2016-2018) All India GATE Physics Rank 73 (2009)