2023/11 | png | Chinthak | Murali | astronomy | 2 | 2023 | | Studies various astrophysical processes and signals such as gravitational waves, fast radio bursts and pulsar signals using the tools of Machine Learning and AI. | | | chinthak-murali-a54463255 | | | | |
2023/11 | jpg | Shuangqi | Li | systems engineering | 2 | 2023 | | Explores AI-enabled development of high-performance electrochemical energy storage systems for transportation electrification and decarbonization. | | | | 1QoN1ugAAAAJ | | | |
2023/11 | jpg | Yu | Zhou | integrative plant science | 1 | 2022 | | Investigates the response of terrestrial ecosystems to climate change across both time and space, as well as quantifying and predicting their role in the global carbon budget using process-based modeling, machine/deep learning, and data from field measurements and satellite imagery. | https://sites.google.com/view/yu-zhou | | | LUfxjnEAAAAJ | 0000-0002-5544-8342 | | Yu-Zhou-3 |
2023/11 | png | Chia-Hao | Lee | applied and engineering physics | 2 | 2023 | | Explores the fusion of AI with electron microscopy to achieve sub-angstrom resolution characterization of quantum and energy materials. | | | | Pv9sqLoAAAAJ | | | |
2023/11 | jpg | Feng | Tao | ecology and evolutionary biology | 2 | 2023 | | Studies process-informed AI and explores enhanced rock weathering to promote soil inorganic carbon as a scalable carbon dioxide removal method. | https://phxtao.github.io/ | | | | | | |
2023/11 | jpg | Ling-Wei | Kong | computational biology | 2 | 2023 | | Applies machine learning to the complex nonlinear dynamics in ecology and climate systems, and explores machine-learning-assisted modeling in animal behavior and neuropsychological processes. | https://sites.google.com/view/ling-wei-kong/home | | | | | | |
2023/11 | jpg | Imanol | Miqueleiz | natural resources and the environment | 2 | 2023 | | Studies global freshwater conservation patterns and threat patterns to optimize conservation measures, as well as historical and spatial patterns of freshwater diversity. | https://imiqueleiz.weebly.com/ | | | | | | |
2023/11 | jpg | Krishnanand | Mallayya | physics | 2 | 2023 | | Harnesses AI to bridge the gap between theory, experiments, and numerical simulations, in the areas of condensed matter physics, quantum materials, and quantum dynamics. | | | | T0SMs4IAAAAJ | | | |
2023/11 | jpg | Xin | Wang | chemistry | 1 | 2022 | | Studies physics-informed deep learning and computer vision for soft materials, inorganic crystals and small molecule design. | | | xin-wang-464aa4216 | NwEhwkcAAAAJ | | | |
2023/11 | jpeg | Bu | Zhao | civil and environmental engineering | 2 | 2023 | | Uses data-driven environmental system analysis to analyze and mitigate the environmental impacts of human activities in the context of climate change and carbon neutrality goals. | | | | kEr2qckAAAAJ | | | |
2023/11 | jpg | Vikram | Thapar | chemical and biomolecular engineering | 1 | 2022 | 2023 | Develops efficient methodologies using computer simulations to identify specific chemical compounds that can self-assemble into desirable, geometrically complex nanostructures. | | | | _pk1DmQAAAAJ | | | |
2023/11 | jpg | Eliot | Miller | ornithology | 1 | 2022 | | Explores the feasibility of using automated acoustic identifications to inform species distribution models. | https://eliotmiller.weebly.com/ | https://www.birds.cornell.edu/home/staff/eliot-miller/ | | | | | |
2023/11 | jpg | Zhongmou | Chao | chemical and biomolecular engineering | 2 | 2023 | | Uses synthetic biology, bioelectronics, and machine learning to make the next generation of AI sensors. | | | zhongmou-chao-8887517b | | | | |
2023/11 | jpeg | Sebastian | Heilpern | public and ecosystem health | 2 | 2023 | | Focuses on understanding the causes and consequences of biodiversity change on ecosystem functions and services, with a particular emphasis on aquatic biodiversity, energy and food systems. | https://sebheilpern.weebly.com/ | | | | | | |
2023/11 | jpg | Benjamin | Decardi-Nelson | systems engineering | 1 | 2022 | | Develops novel computational tools to improve the analysis, design and operation of complex systems and processes, with sustainability as the overarching goal. | https://decardinb.github.io | | decardinb | bM29EVMAAAAJ | | | |
2023/11 | png | Roy | Moyal | psychology | 2 | 2023 | | Studies sensory systems (olfaction and vision), neuromorphic computing, and spiking neural network algorithms. | | | roy-moyal | | | | |
2023/11 | jpg | Fan | Wu | applied and engineering physics | 2 | 2023 | | Focuses on comprehending and harnessing the inherent complexity within nonlinear multimode configurations and quantum systems. | | | | Fuwe_nEAAAAJ | | | |
2023/11 | jpg | Xin | Sun | chemical and biomolecular engineering | 2 | 2023 | | Uses AI to promote the sustainability of energy-climate-material sustainability, with a focus on the energy storage technology. | | | | n-fRvd8AAAAJ | | | |
2023/11 | jpg | Ralitsa | Todorova | neurobiology and behavior | 1 | 2022 | | Deploys machine learning methods to study mental imagery in mice, and decodes neuronal activity to uncover the neural coding underlying cognitive processes. | | | | zELQA00AAAAJ | | | |
2023/11 | jpg | Tianyu | Wang | applied and engineering physics | 1 | 2022 | 2023 | Studies how physical systems perform computing, especially for AI. | https://tyw-lab.github.io | | | lqIvJCgAAAAJ | | | |
2023/11 | jpg | Alexandros | Polyzois | chemistry | 1 | 2022 | 2023 | Studies complex microbial communities through untargeted metabolomics, and develops computational mass spectrometry approaches. | | | alexandros-polyzois | | | | |
2023/11 | jpg | Felipe | Pacheco | ecology and evolutionary biology | 1 | 2022 | | Harnesses AI to address sustainability challenges in the Water-Food-Energy Nexus. | https://felipespacheco.wixsite.com/fspacheco | | | 4hg4_SUAAAAJ | 0000-0003-2143-5225 | D-1712-2014 | Felipe-Pacheco-8 |
2023/11 | jpg | Itay | Griniasty | physics | 1 | 2022 | | Studies how programmable materials can be designed into microscopic machines, and how information geometry uncovers hidden relations and the generalizability of climate simulations of extreme precipitation. | | | | a3Uhp58AAAAJ | | | |