جست‌وجوی استاد و پژوهشگر

Mykola Tasinkevychمشاهده پروفایل

مدرس ارشد

• Soft Condensed Matter
• Liquid Crystals
• Active Colloids
• +۴ مورد دیگر

Dr. Mykola Tasinkevych is a Senior Lecturer at the School of Science & Technology, Nottingham Trent University (since 2021). Previously, he held research positions at the Max Planck Institute for Metals Research (Senior Scientist), University of Lisbon (FCT Fellow), and Northwestern University. He completed his PhD in 1999 and has since published 75+ peer-reviewed papers, secured €1M+ in competitive grants (FCT, DFG, EU), and supervised 15+ students/postdocs. His research centers on soft condensed matter , with expertise in: Liquid crystal-enabled nanoparticle self-assembly and topological defects Dynamics of active colloids and microswimmers Superhydrophobic surfaces and wetting phenomena Capillary interactions at fluid interfaces He collaborates internationally with groups at University of Colorado Boulder, University of Lisbon, and University of Hawaiʻi. His recent publications (2020–2025) focus on active matter control (e.g., microswimmers in ratchets), liquid crystal skyrmions under flow/topological constraints, and nanoparticle assembly in chiral environments. Machine learning applications for texture analysis also emerge in forthcoming work. Awards/Grants: FCT Postdoctoral Fellowship (1999–2003) FCT 5-year Principal Investigator Fellowship (2017; 10% success rate) DFG/EU FP7 Grants (2007–2016) FCT Major Grant PTDC/FIS-MAC/5689/2020 (6% success rate) He leads theoretical research groups on soft matter, advising projects in physics and securing funding for international collaborations. Current work explores dynamical phenomena in topological solitons and nanoparticle composites.

Hualu Zhouمشاهده پروفایل

استادیار

• Food Science
• Food Nanotechnology
• Emulsion Technologies
• +۷ مورد دیگر

Dr. Hualu Zhou is an Assistant Professor in the Department of Food Science & Technology at the University of Georgia's College of Agricultural & Environmental Sciences. She leads the Laboratory of Future Foods and Biomaterials at the UGA Griffin campus, where her research focuses on developing innovative plant-based food systems and sustainable biomaterials through advanced scientific principles. Dr. Zhou earned her undergraduate degree from Nanchang University (2010-2014), completed her Master's at Xiamen University (2014-2017), and obtained her Ph.D. from the University of Massachusetts Amherst (2017-2021), followed by postdoctoral research there (2021-2023) before joining UGA faculty in 2023. Her research program integrates experimental food science techniques including nanotechnologies, emulsion technologies, and INFOGEST in vitro digestion models with computational approaches such as molecular modeling and data analysis. Current projects focus on: (1) developing plant-based food alternatives using low-energy methods; (2) creating standardized assessment methods for plant-based foods; and (3) exploring food nanotechnology applications for enhanced bioactive compound delivery. Her work emphasizes sustainability, health benefits, and practical food system applications. Analysis of Dr. Zhou's recent publications reveals a strong emphasis on pH-driven processing technologies, plant protein functionality, and innovative delivery systems for bioactive compounds. Her research bridges fundamental food chemistry with practical applications, particularly in developing plant-based meat and dairy alternatives. She maintains extensive collaborations, especially with Dr. D.J. McClements, demonstrating an interdisciplinary approach to solving complex food science challenges. Dr. Zhou has served as a reviewer for numerous scientific journals and has contributed to over 50 reviewed papers in prestigious publications including Food Chemistry, Food Hydrocolloids, and Trends in Food Science & Technology. She also serves on the Early Career Advisory Board for the Journal of Agricultural and Food Chemistry and as an Editorial Board member for Grain & Oil Science and Technology. As an advisor, Dr. Zhou currently mentors Master's student Anthony Suryamiharja, Ph.D. student Minghe Wang, and collaborates with postdoctoral associate Xiping Gong. She has served on graduate committees and trained numerous undergraduate researchers. Her extension work through FoodPIC connects her research with industry partners developing plant-based products like pecan milk and polyphenol-enriched peanut butter. The recently renovated Laboratory of Future Foods and Biomaterials maintains state-of-the-art equipment for food chemistry analysis, including instrumentation for microscopy, HPLC, laser diffraction, and rheometry.

Wojciech Solowskiمشاهده پروفایل

دانشیار

• Geotechnical Engineering
• Computational Geomechanics
• Numerical Modeling of Soils
• +۷ مورد دیگر

Dr. Wojciech Solowski is an Associate Professor at Aalto University , specializing in computational simulations of soils and granular materials with a focus on numerical methods and constitutive modeling. His research spans geotechnical engineering, environmental geomechanics, and computational mechanics. Research Interests : Numerical modeling (FEM/MPM), THMC behavior of soils, unsaturated soil mechanics, soil improvement, frost susceptibility, ground vibrations, and laboratory testing. Scientific Contributions : Dr. Solowski has extensively advanced the Material Point Method (MPM) for large deformation problems in geotechnics and developed the in-house finite element code Thebes for THMC coupling simulations. His work addresses critical challenges in nuclear waste repositories, soft soil stabilization, and offshore sediment characterization. Publication Trends : Recent articles focus on MPM for marine clay analysis, THMC coupling in bentonite barriers, 3D shrinkage deformation measurements, and geophysical-geotechnical integration for offshore wind farms. His research emphasizes practical applications in energy transition and infrastructure resilience. Affiliations : Mineral Based Materials and Mechanics research group at Aalto University. Committee Roles : International Secretary of the Finnish Geotechnical Society; member of ISSMGE TC106 (unsaturated soils) and ERTC7 (numerical methods).

Xavier Décoretمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Real-time Rendering
• Visibility
• +۳ مورد دیگر

Xavier Décoret is a researcher at INRIA since October 2003, specializing in computer graphics with core expertise in real-time rendering, visibility algorithms, and level-of-detail techniques. He teaches courses at Grenoble (Master IVR program) and École Polytechnique, including Java programming, virtual image creation, and advanced image synthesis. His educational background includes: PhD in Computer Graphics under François Sillion Post-doctoral position at MIT under Frédo Durand Décoret's research spans non-photorealistic rendering, shadow computation, and GPU-accelerated algorithms. He develops practical graphics tools including XdkWRL (VRML parsing), Argstream (command-line arguments), and XdkBibTeX (BibTeX handling), emphasizing real-world implementation for interactive systems. His 2008 publications reveal trends toward efficient interactive rendering techniques, with contributions in dynamic stylization, label placement, soft shadows, and GPU voxelization—highlighting innovations in plausible visual effects for real-time applications. He is affiliated with the Artis research team at INRIA, focusing on virtual reality and computer graphics advancements.

Alice Haynesمشاهده پروفایل

پژوهشگر

• Human-Computer Interaction
• Soft Robotics
• E-Textiles
• +۶ مورد دیگر

Alice Haynes is a Digital Futures Postdoctoral Fellow at KTH Royal Institute of Technology, working on the Felt Connections project under the Division of Media Technology and Interaction Design . She collaborates with Prof. Kristina Höök and Associate Prof. Iolanda Leite to create shape-changing textile interfaces that foster meaningful bodily interactions for children and adults. Education PhD in Engineering Mathematics, University of Bristol (2022) Specialization in Soft Robotics and Haptic Interfaces Her research blends soft robotics, e-textiles, and soma design to develop tactile technologies that prioritize bodily engagement over traditional visual/auditory interfaces. Current work explores: first-person design for scoliosis, symmetry-asymmetry dynamics in bodily interactions, and soma-driven methods that emphasize felt experiences. Key article trends include shape-changing textiles (SMA-actuated smocking, machine embroidery), emotional/therapeutic applications (anxiety relief, social touch), and multisensory integration (audio-tactile mappings, biosignal interaction). Scientific Contributions Recipient of Digital Futures Postdoctoral Fellowship Co-design methodologies for child-centered technology Material-driven evaluation frameworks for e-textiles Embodied interaction paradigms through haptic cushions Alice teaches Human-Computer Interaction Research Seminars (DH2632) and Media Technology and Interaction Design (DM2601) , while actively seeking Master's students for collaborative thesis work.

• Top-quark physics
• Factorization and resummation
• Infrared properties of gauge theories
• +۱۲ مورد دیگر

Prof. Michal Czakon is a full-time University Professor at the Institute for Theoretical Particle Physics and Cosmology, RWTH Aachen University. His research group focuses on high-energy theoretical physics, particularly top-quark interactions, QCD corrections, and Higgs boson production mechanisms at particle colliders. Top-quark physics Factorization and resummation techniques Parton showers with quantum effects Subtraction schemes for real radiation Automation of higher-order calculations His recent publications analyze renormalization effects, interference contributions, and precision observables in collider experiments. The group develops tools like Top++ and HELAC-NLO for cross-section evaluations. Scientific Awards: Sofja-Kovalevskaja Award (2004) Heisenberg Professorship (2009) Current advisees include PhD candidates and Master's students such as Manal Alsairafi, Marco Bigazzi, and Felix Eschment. The group also collaborates on software projects for high-energy physics simulations.

Jon Heiselmanمشاهده پروفایل

استاد پژوهشی

• Biomedical Engineering
• Image-Guided Surgery
• Surgical Navigation
• +۳ مورد دیگر

Jon Heiselman is a Research Assistant Professor in the Department of Biomedical Engineering at Vanderbilt University School of Engineering. He serves as Associate Director of the Master of Engineering in Surgery and Intervention Program and leads research in image-guided surgical technologies. His work focuses on soft tissue deformation modeling, augmented reality applications, and computational frameworks for precision surgery. Education: PhD in Biomedical Engineering (Vanderbilt University, 2020) Advisor: Michael Miga, Harvie Branscomb Professor Research interests span image-guided surgical navigation, deformable registration algorithms, and digital twin modeling for therapeutic forecasting. Articles highlight advancements in soft tissue deformation correction, augmented reality integration, and machine learning approaches for real-time surgical guidance. Current affiliations include Vanderbilt's Biomedical Modeling Laboratory (BML) and the VISE Steering Committee. He contributes to NIH-funded training programs and has received recognition for his work in surgical data science and computational oncology.

• Quantum Many-Body Systems
• Rydberg Atoms
• Quantum Simulation
• +۷ مورد دیگر

Prof. Dr. Igor Lesanovsky is a leading researcher in quantum physics at the University of Tübingen, where he heads the Arbeitsgruppe (Research Group) Lesanovsky within the Institute of Theoretical Physics, part of the Faculty of Mathematics and Natural Sciences. His research focuses on quantum many-body systems, particularly utilizing Rydberg atoms for quantum simulation, quantum information processing, and exploring non-equilibrium phenomena. His research interests span quantum many-body physics, Rydberg atom systems, quantum simulation techniques, non-equilibrium quantum dynamics, quantum thermodynamics, and quantum soft-matter physics. His group investigates how highly excited Rydberg atoms can be used to simulate complex quantum processes, study phase transitions, and develop applications for quantum information processing. They're particularly interested in emergent phenomena such as time-crystals, quantum glassiness, and non-ergodic behavior in quantum systems. The publication record shows a consistent stream of high-impact research, primarily in Physical Review Letters, Physical Review A, and other top physics journals. The research trends indicate a strong focus on quantum simulation with Rydberg systems, quantum non-equilibrium dynamics, quantum information applications, and increasingly on the intersection of quantum physics with machine learning. Recent work explores quantum neural networks, quantum measurement theory, and the application of large-deviation methods to quantum trajectory ensembles. Prof. Lesanovsky's research is supported by multiple prestigious projects including the BMBF Quantum Technology project 'Neural quantum networks on NISQ quantum computers', the DFG Excellence Cluster 'Machine Learning: New Perspectives for Science', DFG Research Units on long-range interacting quantum spin systems and quantum thermalization, the EU EIC Pathfinder Project 'Brisk Rydberg Ions for Scalable Quantum Processors', the QuantERA Project CoQuaDis, and The Center for Integrated Quantum Science and Technology (IQST). The group maintains strong connections with experimental teams, particularly in the areas of quantum simulation of interacting many-body systems and the development of matter wave interferometers and collectively enhanced electric field sensors. They collaborate extensively across Germany and internationally, with publications showing co-authorship with researchers from multiple institutions worldwide.

Xiaoting Jiaمشاهده پروفایل

استاد

• Neural Interfacing
• Biomedical Engineering
• Optical Fibers
• +۵ مورد دیگر

Xiaoting Jia is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. Her research focuses on advanced functional fibers with applications in biomedical devices, optoelectronics, and neurotechnology. She holds affiliations including the Virginia Tech College of Engineering and maintains an active scholarly profile with collaborations in materials science and neural interfacing. Education : Ph.D., Massachusetts Institute of Technology (2011) M.S., Stony Brook University (2006) B.S., Fudan University (2004) Research Interests : Development of multifunctional fibers for neural recording and stimulation Optically and magnetically controlled power electronics Bio-inspired flexible materials and wearable sensors Neuropharmacological studies using fiber-based probes Her recent work emphasizes hybrid fiber systems combining electrical, optical, and chemical functionalities for biomedical applications. Over 150 peer-reviewed articles demonstrate contributions to neural interfaces, energy harvesting, and advanced fiber fabrication techniques. Awards and service roles are pending specific documentation. Grants & Labs : Led projects in National Science Foundation-funded neural engineering initiatives Collaborated with industry partners on fiber-optic sensor commercialization

Fosca Giannottiمشاهده پروفایل

استاد

• Mobility Data Mining
• Social Network Analysis
• Privacy-Preserving Data Mining
• +۶ مورد دیگر

Fosca Giannotti is a Full Professor at Scuola Normale Superiore in Pisa, Italy, and leads the Pisa KDD Lab - Knowledge Discovery and Data Mining Laboratory, a joint research initiative of the University of Pisa and ISTI-CNR. Founded in 1994, the Pisa KDD Lab is one of the earliest research labs focused on data mining. Giannotti is a pioneering scientist in mobility data mining, social network analysis, and privacy-preserving data mining. Her educational background includes a Master Degree in Computer Science from the University of Pisa (1982) with 110/100 cum laude. She has held numerous visiting positions including at MCC in Austin, CWI Amsterdam, UCLA, and the Barabasi Lab at Northeastern University. Giannotti's research focuses on social mining from big data, encompassing smart cities, human dynamics, social and economic networks, ethics and trust, and diffusion of innovations. She has authored more than 300 papers and coordinated tens of European projects and industrial collaborations. Her current work increasingly centers on Explainable AI (XAI), as evidenced by her prestigious ERC Advanced Grant for the XAI project focused on "Science and technology for the explanation of AI decision making." Her recent publications reveal a strong emphasis on trustworthy AI, with research spanning privacy-preserving techniques, fairness in machine learning, human-AI collaboration frameworks, and medical applications of explainable AI. The breadth of her work demonstrates how data mining principles are being applied across diverse domains from social sciences to healthcare. ERC Advanced Grant for XAI project Premio Internazionale Tecnovisionarie 2021 Intelligenza Artificiale Giannotti has coordinated numerous significant projects including SoBigData (the European research infrastructure on Big Data Analytics and Social Mining), XAI, TAILOR (Foundations of Trustworthy AI), HumanE-AI-Net, and AI4EU. As former coordinator of SoBigData, she led an ecosystem of ten cutting-edge European research centers providing an open platform for interdisciplinary data science. She leads the Pisa KDD Lab, which serves as a hub for research on knowledge discovery and data mining. The lab has been instrumental in developing techniques for mobility data analysis, social network mining, and privacy-preserving data analytics, with applications ranging from smart cities to pandemic response.

Federica Marone Welfordمشاهده پروفایل

پژوهشگر

• X-ray Tomography
• Seismology
• Tomographic Reconstruction
• +۷ مورد دیگر

Federica Marone Welford is a Beamline Scientist at the TOMCAT beamline of the Swiss Light Source (SLS) at the Paul Scherrer Institute (PSI) . She holds an Earth Sciences degree with a focus on seismology and a PhD in seismology from ETH Zurich , following a postdoctoral fellowship at the Berkeley Seismological Laboratory . Her work centers on advancing tomographic reconstruction algorithms, mitigating artifacts, and optimizing computational infrastructure for high-speed X-ray imaging at the TOMCAT beamline. Research Focus: X-ray tomography methodology, data compression, real-time reconstruction systems, and applications in paleontology, earth sciences, additive manufacturing, and energy research. Collaborations: Engages with global researchers and industry partners, particularly in battery/fuel cell analysis and laser powder bed fusion. Teaching: Lectures at ETH Zurich on X-ray imaging techniques. Publications highlight her contributions to X-ray scattering tensor tomography, dynamic process visualization, and computational advancements in imaging systems.

Lonneke van der Plasمشاهده پروفایل

دانشیار

• Cross-lingual NLP
• Computational Semantics
• Computational Creativity
• +۴ مورد دیگر

Prof. Lonneke van der Plas is an Associate Professor in Natural Language Processing (NLP) at the University of Lugano (USI) since October 2024. She leads the Computation, Cognition & Language group at Idiap Research Institute (since 2021) and holds adjunct roles in USI's Faculty of Informatics. Previously, she was an Associate Professor at the University of Malta (2014–2020) and Junior Professor at the University of Stuttgart (SFB 732). She earned her PhD in Humanities Computing from the University of Groningen and an M.Phil in Computer Speech and Language Processing from the University of Cambridge. Her research focuses on cross-lingual NLP, computational creativity, and low-resource languages. Key projects include the NCCR Evolving Language (Swiss National Science Foundation, 2024–2028), C-LING (computational models of creativity), and SEM24 (multilingual skill extraction for HR). She has supervised multiple PhD students and postdocs, including notable advisees such as Molly Petersen and Mete Ismayilzada. Her work spans theoretical linguistics and applied NLP, with collaborations in cognitive science, finance, and healthcare. Awards include the ELSI Best Paper Award (2020) for work on societal impacts of AI ethics. Current initiatives include open PhD positions in NLP for cognitive modeling and mental health applications. Education: PhD (University of Groningen), M.Phil (University of Cambridge) Key Projects: NCCR Evolving Language, C-LING, SEM24, LT-BRIDGE Grants: SNSF, Innosuisse, Hasler Foundation Lab/Team: Computation, Cognition & Language Group at Idiap

Vaibhav Srivastavaمشاهده پروفایل

دانشیار

• Cyber Physical Human Systems
• Networked Multi-Agent Systems
• Mathematical Neuroscience
• +۳ مورد دیگر

Vaibhav Srivastava is an Associate Professor in the Electrical and Computer Engineering Department at Michigan State University (MSU), with affiliations in Mechanical Engineering and the Cognitive Science Program. He holds a Ph.D. and M.A. from the University of California, Santa Barbara, and a BTech from the Indian Institute of Technology Bombay. His research focuses on Cyber-Physical Human Systems, including networked multi-agent systems, mathematical neuroscience, and autonomous robotics. He has held leadership roles in conferences like the American Control Conference and serves as an Associate Editor for the ASME Journal of Dynamical Systems and IEEE Open Journal of Control Systems. Education: Ph.D. in Mechanical Engineering, University of California, Santa Barbara (2012) M.A. in Statistics, University of California, Santa Barbara (2012) M.S. in Mechanical Engineering, University of California, Santa Barbara (2011) BTech in Mechanical Engineering, Indian Institute of Technology Bombay (2007) Research Interests: Prof. Srivastava’s work bridges human decision-making with engineering systems, emphasizing mixed human-robot teams, networked systems, and mathematical models of neural processes. His projects address challenges in autonomous vehicles, surveillance strategies, and collaborative robotics, supported by grants from NSF, ONR, and the Army Research Office. Recent Trends in Articles: His publications explore adaptive control strategies for UAVs, trust-aware autonomy, and multi-fidelity models for human-robot collaboration. Key themes include robust trajectory estimation, impedance tuning, and epidemic modeling in networked environments. Awards: Best Student Paper Award (coauthor), European Control Conference 2014 Grants & Advising: He has secured funding for projects on data-driven control and human-in-the-loop systems. His advising includes contributions to robotics and control theory, with a focus on interdisciplinary approaches combining cognitive science and engineering. Labs/Teams: Engaged in collaborative efforts across MSU’s College of Engineering, focusing on soft robotics, decision-making algorithms, and autonomy in dynamic environments.

Ghislaine M.E. Vantommeمشاهده پروفایل

استادیار

• Supramolecular Chemistry
• Materials Science
• Organic Synthesis
• +۶ مورد دیگر

Ghislaine M.E. Vantomme is an Assistant Professor at Eindhoven University of Technology, leading the Supramolecular Chemistry and Materials group within the Department of Chemical Engineering and Chemistry. Her research focuses on developing adaptive, self-learning supramolecular materials inspired by living systems, integrating organic synthesis, systems chemistry, and materials science. Key areas include molecular computing, bio-(opto)electronics, and sustainable materials design. Academically, she holds a PhD from Strasbourg University (2014) under Prof. Jean-Marie Lehn, and postdoctoral experience at TU Eindhoven with Prof. Bert Meijer. Notable grants include the NWO Veni (2017) and VIDI (2024), alongside the 2026 New Horizons Solvay Lectureship. She teaches advanced organic chemistry courses for engineering and premaster students. Her work contributes to UN Sustainable Development Goals through eco-friendly material innovations. Research highlights include self-regulating hydrogels, chiral semiconductor films, and phase-separated nanomaterials. She collaborates internationally, with recent media coverage on molecular computing and optoelectronic material breakthroughs. Education: PhD in Supramolecular Chemistry, Strasbourg University (2014) MSc, Sorbonne University (Paris) BSc, École Normale Supérieure (Cachan) Research Themes: Biomimetic materials, adaptive systems, molecular self-assembly, chiral optoelectronics. Grants & Awards: NWO Veni (2017) NWO VIDI (2024) Solvay Lectureship (2026) Teaching: Organic Chemistry 1/2, Advanced Molecular Chemistry.

Chase Broederszمشاهده پروفایل

دانشیار

• Cell Migration
• Chromosome Organization
• Biopolymer Mechanics
• +۳ مورد دیگر

Chase Broedersz is an Associate Professor at Vrije Universiteit Amsterdam, affiliated with the Faculty of Science's Physics of Living Systems department and the LaserLaB - Energy research group. He leads interdisciplinary research on cell migration, chromosome mechanics, and active matter, combining experimental and theoretical approaches. His work contributes to UN Sustainable Development Goals related to health and innovation. Research Interests: Focus on cell migration dynamics , chromosome organization , biopolymer mechanics , and nonlinear elasticity . Recent studies explore bacterial chromosome topology, metastasis prevention mechanisms, and 3D nuclear deformation during cell movement. His methods include Hi-C data analysis, single-molecule tweezers, and computational modeling. Publications Trends: Recent work emphasizes chromosome condensation mechanics , active matter dynamics , and nonlinear elasticity in biopolymers . Key 2024-2025 studies include ion-mediated mitotic chromosome mechanics and metastasis suppression by miR-200c. Awards: None explicitly listed. Grants/Advising: Supervised one PhD thesis and contributes to datasets like biopolymer matrix nonlinear elasticity studies. Labs/Teams: Active in LaserLaB and collaborates internationally on cell migration and chromosome physics.