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Jonathan T. BarronView profile

Researcher

• Computer Vision
• Deep Learning
• Generative AI
• +3 more

Jonathan T. Barron is a Researcher at Google DeepMind in San Francisco, specializing in Computer Vision , Neural Rendering , and 3D Scene Reconstruction . He earned his PhD at UC Berkeley under Jitendra Malik and has pioneered advancements in NeRF (Neural Radiance Fields) and diffusion-based 3D generation. Research Interests : Computer Vision, Deep Learning, Generative AI, Image Processing, and 3D Reconstruction via Radiance Fields. His work includes Bolt3D for rapid 3D scene generation, CAT3D/CAT4D for text-to-3D/4D, and Zip-NeRF for anti-aliased radiance fields. He has also developed real-time rendering frameworks like SMERF and NeRF-Casting for reflections. Scientific awards: PAMI Young Researcher Award He has served as Area Chair for CVPR, ICCV, and NeurIPS, and his research is widely adopted in applications like Google's Lens Blur , Portrait Mode , and Jump VR .

Edward H. AdelsonView profile

Professor

• Computer Vision
• Artificial Touch Sensing
• Neuroscience of Vision
• +4 more

Edward H. Adelson is the John and Dorothy Wilson Professor of Vision Science at MIT, affiliated with the Department of Brain and Cognitive Sciences and the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research spans computer vision, human vision science, and robotics, with a focus on artificial touch sensing and tactile robotics. He has pioneered technologies like the GelSight tactile sensor, enabling high-resolution touch sensing for robots surpassing human skin sensitivity. Adelson holds a PhD in Experimental Psychology from the University of Michigan (1979) and a BA in Physics and Philosophy from Yale University (1974). His career includes roles at MIT since 1987, progressing from Associate Professor to Professor and later the Wilson Chair. He contributed to early vision theories, including the plenoptic function and motion energy models, and has been recognized with prestigious awards like the Helmholtz Prize (2013) and Rank Prize (1992). His research interests include material perception, optical sensing, and the integration of vision and touch. Key innovations include the plenoptic camera, layered representation techniques for motion analysis, and tactile sensors for robotics. Adelson has authored over 300 publications and holds numerous patents in imaging, vision, and robotics. Awards and honors include membership in the National Academy of Sciences and the American Academy of Arts and Sciences. His work bridges neuroscience and engineering, advancing both fundamental understanding and practical applications in robotics and computer vision.

Reed MaxwellView profile

Professor

• Hydrology
• Water Resources
• Groundwater Modeling
• +8 more

Reed Maxwell is the William and Edna Macaleer Professor of Engineering and Applied Science in the Department of Civil and Environmental Engineering and the High Meadows Environmental Institute at Princeton University. He serves as Director of the Integrated Groundwater Modeling Center (IGWMC) and leads a research group comprising graduate students, postdoctoral researchers, and staff. His academic appointments include concurrent roles in both the School of Engineering and Applied Science and the High Meadows Environmental Institute. Maxwell's research focuses on understanding connections within the hydrologic cycle and how they relate to water quantity and quality under anthropogenic stresses. His work centers on hard problems in hydrology including groundwater, evapotranspiration and snow. His research group uses integrated hydrologic modeling, field observations, and remote sensing products to study terrestrial freshwater systems. Key research areas include surface water and the terrestrial hydrologic cycle; interactions of the land-surface, surface water and groundwater; and human health risk assessment. Maxwell has authored more than 185 peer-reviewed journal articles with an H-Index of 66 and over 19,000 citations. His recent work emphasizes machine learning applications in hydrology, continental-scale modeling, and physically rigorous scenario generation through projects like HydroFrame and HydroGEN. He teaches courses including CEE 306/ENV 318 Hydrology: Water and Climate and CEE 586/ENV 586 Physical Hydrology. 2020 Distinguished Henry Darcy Lecturer American Geophysical Union Fellow (2019) 2018 Boussinesq Lecturer Belle van Zuylen Chair (visiting), University of Utrecht 2017 School of Mines Research Award recipient Maxwell has mentored 17 PhD students and 20 MS thesis students throughout his career. His current research group includes multiple postdocs, research software engineers, and graduate students working on projects spanning continental-scale hydrologic modeling, groundwater-stream interactions, and machine learning applications in hydrology. The IGWMC maintains an active education and outreach program including STEM fairs, school visits, and digital educational tools like the HydroFrame Education Team's virtual sandtank aquifer model.

Richard SimonView profile

Associate Professor

• Rock Mechanics
• Mining Engineering
• Geotechnics
• +4 more

Richard Simon is an Associate Professor in the Department of Civil, Geological and Mining Engineering at Polytechnique Montréal. He holds leadership roles as Publications Director of his department and Administrative Director of the Institute for Research in Mining and Environment (IRME) UQAT-Polytechnique. His educational background includes a B.Eng. and M.Sc.A. from Polytechnique Montréal and a Ph.D. from McGill University. Dr. Simon teaches courses including Introduction to Mine Operations, Underground Mining, and Rock Mechanics I. His research focuses on rock mechanics, numerical modeling, mining engineering, and geotechnical applications in mining environments. His extensive publication record demonstrates consistent focus on numerical modeling of rock behavior, mine stability analysis, and backfill mechanics. Recent work emphasizes computational geomechanics applications in mining operations, including stress analysis in backfilled stopes, slope stability in open pits, and optimization of mining layouts. Environmental aspects of mining, particularly contaminant transport in fractured rock, also feature prominently. Dr. Simon has supervised 6 doctoral and 8 master's students working on topics ranging from numerical seismic assessment in mines to rock fracture mechanics. He secured significant research funding including $900,000 (2017) for a metals circular economy project and led three new IRME research initiatives (2015). He directs research activities at IRME UQAT-Polytechnique and collaborates extensively within the mining geomechanics research community. His expertise is regularly featured in media outlets including La Presse+ and Les Affaires.

Aleksander KubicaView profile

Assistant Professor

• Quantum Information Science
• Quantum Error Correction
• Fault Tolerance
• +3 more

Aleksander Kubica is an Assistant Professor of Applied Physics at Yale University, specializing in quantum information science with a focus on quantum error correction and fault tolerance. His research bridges quantum many-body physics and topological codes, particularly exploring applications in superconducting circuits and quantum architectures. He holds a Ph.D. from the California Institute of Technology and a B.S. from the University of Warsaw. Dr. Kubica's work addresses foundational challenges in scalable quantum computing, including optimizing error correction protocols, developing fault-tolerant architectures, and analyzing the intersection of quantum metrology with error mitigation. Recent contributions include advancements in erasure qubits, correlated noise decoding, and topological code adaptations. His research often involves interdisciplinary approaches, combining theoretical physics with algorithm design and hardware-efficient solutions. Key themes in his publications include improving error correction thresholds, designing low-overhead quantum architectures, and exploring novel decoding strategies for topological codes. While no specific awards are listed, his active research trajectory and contributions to quantum computing indicate significant scholarly engagement in the field.

Andreas MortensenView profile

Professor

• Metal Matrix Composites
• Mechanical Properties of Materials
• Metallurgy
• +7 more

Andreas Mortensen is a full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland, where he leads research at the Mechanical Metallurgy Laboratory (LMM) within the School of Engineering. His office is located in building MXD at EPFL's main campus in Lausanne. Institution: École Polytechnique Fédérale de Lausanne (EPFL) School: School of Engineering (STI) Department: Mechanical Metallurgy Laboratory (LMM) Position: Professor Professor Mortensen's research focuses on the mechanical properties of materials, particularly metal matrix composites, microcellular materials, and the fundamental aspects of metallurgy. His work spans from theoretical modeling to practical applications in materials processing and characterization. He has made significant contributions to understanding infiltration processes, fracture mechanics, and the behavior of materials at micro and nano scales. Analysis of Professor Mortensen's recent publications (2022-2025) reveals a continued focus on advanced materials characterization techniques, particularly nanoindentation and micro-scale mechanical testing. His research shows increasing attention to additive manufacturing processes, multi-scale material behavior, and the development of novel composite structures. The work spans fundamental investigations of dislocation dynamics and slip phenomena to applied research on brazing technologies and investment casting methods. Throughout his extensive career, Professor Mortensen has supervised numerous students and collaborated with researchers worldwide, contributing to the advancement of materials science and engineering. His laboratory has been instrumental in developing methodologies for characterizing material behavior across multiple length scales, from nano to macro.

• Sustainable Machining Processes
• Tool Wear Monitoring
• Surface Roughness Optimization
• +3 more

Doç. Dr. Muhammed Aras is an Associate Professor in the Department of Mechanical Engineering at Baskent University (Başkent Üniversitesi), with a research focus on sustainable machining processes, tool wear monitoring, and surface roughness optimization. His work spans advanced manufacturing technologies, energy storage systems, and biomedical device design. PhD in Manufacturing Engineering (2018), Gazi Üniversitesi MSc in Mechanical Education (2013), Gazi Üniversitesi BSc in Mechanical Engineering (2010), Tabriz Islamic Azad University Research interests include sustainable machining (dry/hard turning, cooling-lubrication strategies), tool wear analysis (CBN, ceramic and coated inserts), and surface integrity optimization using AI-based methods (firefly algorithm, TOPSIS, Grey Relational Analysis). His 15 most recent articles (2017-2024) examine topics like: Surface roughness prediction in dry hard turning Energy storage technology viability assessments Cutting parameter optimization for various steels Acoustic/vibration monitoring in machining He has received scientific awards including the Teşvik Ödülü (Encouragement Award, 2015). His patent on an automatic orthognathic surgery articulator and book chapters on tool monitoring systems demonstrate his multidisciplinary impact.

Khaled GiasinView profile

Senior Lecturer

• Machining Aerospace Materials
• Finite Element Modeling
• Additive Manufacturing
• +3 more

Khaled Giasin is a Senior Lecturer in Mechanical Engineering at the University of Portsmouth, part of the School of Electrical and Mechanical Engineering and affiliated with the Portsmouth Centre for Advanced Materials and Manufacturing. He joined the university in 2019, bringing expertise in machining aerospace materials through experimental and numerical techniques. Prior to this, he worked at Cardiff University on the ASTUTE2020 project, focusing on applied research for advanced manufacturing challenges in Wales. His research interests span machining of metals, composites, and fiber metal laminates, finite element modeling of machining processes, and additive manufacturing of metallic alloys. He collaborates internationally with institutions in France, Turkey, China, and Australia, emphasizing industry-academia partnerships. Dr. Giasin currently supervises PhD projects on topics such as GLARE fiber metal laminate machining and ultrasonic-assisted drilling, reflecting his focus on advanced materials and manufacturing solutions. He teaches modules including Engineering Materials and Design, Advanced Materials, and Metrology. Over 137 research outputs highlight his contributions to machining methodologies, material characterization, and sustainable manufacturing techniques. His work bridges theoretical modeling and industrial applications, addressing challenges in aerospace and advanced manufacturing sectors.

Ron PeledView profile

Professor

• Probability Theory
• Statistical Physics
• Mathematical Physics
• +7 more

Ron Peled is a Full Professor in the School of Mathematical Sciences at Tel Aviv University , currently on leave to serve as the Brin Professor in the Department of Mathematics at the University of Maryland starting summer 2024. During 2022–2024 he was a Member at Princeton University and the Institute for Advanced Study . Education & Career: While explicit degrees are not listed, his trajectory shows appointments at NYU (2009–2010), UC Berkeley and Tel Aviv University as a teaching assistant, followed by faculty positions culminating in full professorship. Research Interests: His work lies at the intersection of probability theory, statistical physics, and combinatorics . Key themes include: Disordered systems and random environments (random-field Ising, spin glasses) First-passage percolation and random metrics Random surfaces and height functions Loop models and critical phenomena Random matrices and band matrices Geometric probability and allocation problems Publications & Impact: With over 70 papers in top journals such as Annals of Mathematics , Annals of Probability , Inventiones Mathematicae , and Communications in Mathematical Physics , his recent work explores minimal surfaces in random environments, localization in random band matrices, and quantitative disorder effects in low-dimensional spin systems. Grants & Awards: Research has been continuously funded by: Israel Science Foundation (grants 1048/11, 861/15, 1971/19, 2340/23) ERC Starting Grant LocalOrder ERC Consolidator Grant Transitions Marie Skłodowska-Curie International Reintegration Grant SPTRF Teaching & Mentoring: Prof. Peled has taught a broad spectrum of courses at Tel Aviv University (Brownian motion, probability, percolation, random matrices, stochastic calculus) and NYU (combinatorics, discrete mathematics). He has supervised 13 post-doctoral fellows and 8 graduate students (PhD & MSc) to date. Service & Outreach: He co-organizes the Joint Israeli Probability Seminar and has organized numerous international workshops and conferences including at Oberwolfach, Technion, and Tel Aviv University.

John D. CresslerView profile

Professor

• Silicon-Germanium Heterojunction Bipolar Transistors (SiGe HBT)
• Mixed-Signal Semiconductor Devices
• RF and Microwave Circuit Design
• +5 more

Professor John D. Cressler is a tenured faculty member at the Georgia Institute of Technology, holding a position within the School of Electrical and Computer Engineering in the College of Engineering. His research focuses on cutting-edge semiconductor technologies, particularly silicon-germanium heterojunction bipolar transistors (SiGe HBTs) for mixed-signal applications spanning RF, microwave, mm-wave, analog, and digital domains. His research interests center on atomic-scale bandgap engineering for next-generation semiconductor devices, with emphasis on SiGe HBT technology development, radiation-hardened circuits for space applications, cryogenic electronics, and device-circuit interactions. His team explores fundamental device theory, broadband noise analysis, profile optimization, 2-D/3-D simulation, compact modeling, and radiation effects. Current projects include Europa-surface mission electronics, D-band/sub-THz systems, and radiation-tolerant receiver designs. Analysis of his 15 most recent publications (2024-2025) reveals a dominant focus on radiation-hardened electronics for space applications (40% of works), millimeter-wave circuit design (30%), and SiGe HBT reliability optimization (30%). Key trends include Europa mission electronics development, D-band/sub-THz circuit innovation, and advanced radiation mitigation techniques using SiGe BiCMOS technology. Professor Cressler teaches multiple courses including ECE 3040 (Microelectronic Circuits), ECE 3450 (Semiconductor Devices), ECE 6444 (Silicon-Based Heterostructure Devices and Circuits), and the interdisciplinary IAC 2002 course on Science, Engineering and Religion. His research is supported by industrial collaborations and Georgia Tech facilities including the Georgia Electronic Design Center (GEDC), NanoTECH, and C-STAR.

• Climate Change Mitigation
• Ecological Economics
• Technology Innovation
• +5 more

Professor Jing Meng is a leading academic at University College London's Bartlett School of Sustainable Construction, holding the position since 2023 after progressing from Lecturer (2019-2021) to Associate Professor (2021-2023). She concurrently serves as a fellow at the Cambridge Centre for Environment, Energy and Natural Resource Governance and maintains active editorial roles as Executive Editor of the Journal of Cleaner Production and Associate Editor for Journal of Geophysical Research: Atmospheres. Her research spans three interconnected domains: Energy Transitions and Technology Innovation (examining cost forecasts and structural emission declines in China), Climate Change Policies (analyzing South-South trade effects and multinational enterprise emissions), and Emission-Health-Socioeconomics Nexus (assessing air pollution impacts and integrated co-mitigation strategies). This interdisciplinary approach is reflected in her publication record across Nature family journals and PNAS. Analysis of her recent publications reveals a consistent focus on global carbon accounting methodologies, with increasing attention to subnational (city-level) analyses, health co-benefits of climate policies, and technological innovation pathways for hard-to-abate sectors. Her work frequently employs multi-regional input-output modeling to trace emissions through complex supply chains. AGU Global Environmental Change Early Career Award (2023) MIT Technology Review Innovators Under 35 Asia Pacific (2022) Clarivate Highly Cited Researcher (2020-2024) Nature Communications Top 50 Earth Sciences Article (2018) MDPI Emerging Sustainability Leader Award (2020) Environmental Research Letters Best Early Career Article (2017) Professor Meng has secured substantial funding from diverse sources including NERC, the British Council, Quadrature Climate Foundation, The Royal Society, and UCL internal grants. She leads an interdisciplinary research group focused on technology innovation and climate policy, with particular emphasis on China's role in global emissions systems. Her work directly supports Sustainable Development Goal 13 (Climate Action) through actionable policy insights.

Judy HartView profile

Associate Professor

• Renewable Energy Materials
• Photocatalysis
• Solar Cells
• +5 more

Associate Professor Judy Hart is a materials scientist at the School of Materials Science & Engineering, UNSW Sydney , specializing in the development of semiconducting materials for renewable energy applications. Her work integrates computational (DFT) and experimental approaches to understand composition-property relationships in systems like solid solutions , heterostructures , and doped materials for photocatalysis and solar cells . She leads projects funded by ARC Discovery and Linkage grants , including work on photo-electro-catalysis systems and stabilizing ceramic materials . Education: PhD in Materials Engineering (Monash University, 2007), BEng (Materials) (Monash, 2002) Professional Experience: Senior Lecturer (UNSW, 2017–), Lecturer (UNSW, 2013–2017), University of Bristol (2007–2012) Research Interests Her research focuses on designing materials for renewable energy , particularly photoelectrochemical water splitting and organic oxidation reactions . Key areas include Density Functional Theory (DFT) , defect engineering , band gap tuning , and nanostructured materials . She investigates ferroelectric polarization effects , metal oxide heterostructures , and stability of battery components , with applications in hydrogen production , CO2 conversion , and advanced battery materials . Scientific Awards Ramsay Memorial Fellowship (University of Bristol, 2007–2009) Teaching Contributions She is co-author of the 1st Australian & New Zealand edition of "Materials Science and Engineering: An Introduction" , and teaches courses on computational materials science , corrosion-resistant surfaces , mechanical behavior of metals , and materials design .

Beata GorczycaView profile

Professor

• Environmental Engineering
• Water and Wastewater Treatment
• Solid/Liquid Separation
• +5 more

Dr. Beata Gorczyca is a Professor in the Department of Civil Engineering at the University of Manitoba, affiliated with the Price Faculty of Engineering. Her research focuses on potable water treatment, with expertise in solid/liquid separation, chlorine disinfection by-products control, and fractal analysis of materials. She leads a research group collaborating with Canadian water utilities like Portage la Prairie and Pembina Valley Water Co-op. Education: PhD in Chemical Engineering (2000, University of Toronto), M.Sc. in Civil Engineering (1992, University of Toronto), B.Sc. in Geological Engineering (1986, AGH University, Poland). Active roles: Member of the Particle Specialist Group at the International Water Association, keynote speaker at conferences. Research interests include water purification processes, membrane filtration, and bioremediation. Her work addresses challenges in high-DOC and high-hardness water treatment, with contributions to nanofiltration fouling mechanisms and microbial remediation solutions. She has supervised numerous graduate students and is involved in advancing water treatment technologies through interdisciplinary collaborations.

Stefan KrastanovView profile

Assistant Professor

• Quantum Hardware Design and Control
• Resilient Noisy Quantum Circuits
• Entanglement and Quantum Networking
• +3 more

Stefan Krastanov is an Assistant Professor at the University of Massachusetts Amherst, focusing on quantum hardware design, control, and optimization across multiple layers of quantum computing and networking technologies. His work bridges physical hardware descriptions with logical circuit compilation, emphasizing resilience in noisy quantum systems. Research Interests include Quantum Hardware Design, Entanglement-Based Networking, Quantum Error Correction, and Modeling Software for Quantum Systems. His primary lab is the Quantum Information Lab , with affiliations to the Advanced Classical and Quantum Information Research Lab. Recent work trends highlight advancements in quantum repeater networks, error-corrected compilation, and photonic neural networks. His publications span topics like non-Markovian dynamics simulation, NP-hard optimization in quantum dot arrays, and scalable spin quantum memory control. Labs and Teams: Quantum Information Lab (leading experimental/theoretical work) and collaborations through the Advanced Classical and Quantum Information Research Lab.

Martin BerggrenView profile

Professor

• Computational Design Optimization
• Numerical Optimization Algorithms
• Gradient-Based Algorithms
• +8 more

Martin Berggren is a Professor at the Department of Computing Science , Umeå University , Sweden. His work focuses on Computational Design Optimization , combining computer simulations and numerical optimization to enhance engineering designs for devices like antennas, microwave components, and loudspeakers. Berggren is also active in mathematical modeling of physical phenomena, particularly wave propagation and fluid mechanics, with a strong emphasis on finite-element methods . His research addresses large-scale conceptual design problems using thousands to millions of design variables, relying on gradient-based algorithms and adjoint-based computations of design sensitivities—similar to back-propagation in deep learning. Key application areas include acoustic and electromagnetic devices, where he investigates damping mechanisms, boundary conditions, and material distribution. Other interests, though less active, involve flow control and unsteady fluid–structure interaction . Berggren collaborates extensively on projects such as Structured Regularization , Topology Optimization of Acoustic Black Holes , and Design of Microstrip-to-Waveguide Transitions . His publications span journals like Journal of Computational Physics , Pattern Analysis and Applications , and IEEE Transactions on Antennas and Propagation , often co-authored with researchers like Linus Hägg , Eddie Wadbro , and Disi Lin .