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Field
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on futuristic technologies in the field of machine learning and computer vision. Hence, we investigate and develop an innovative computation-in-memory (CIM) solution for artificial intelligence accelerator design
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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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studying how wireless sensing and AI interact in real systems. The work will be carried out in close collaboration with researchers in wireless communications, sensing, machine learning, and robotics, with
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multidisciplinary environments Curiosity-driven and self-motivated working attitude Knowledge of biomechanical modeling, anatomy, vision-based motion capture, machine learning, control systems Keep in mind
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studying how wireless sensing and AI interact in real systems. The work will be carried out in close collaboration with researchers in wireless communications, sensing, machine learning, and robotics, with
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Design and build flow setups using 3D printer, pumps, valves operated by a computer and the corresponding software. Develop flow cells to connect various spectroscopic tools to the setup. Create and
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WDM switches and the fast control to enable novel low latency highly scalable and flat interconnect AI compute clusters. Machine learning clusters and artificial intelligence (AI) training have become
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professors, two postdocs, and five PhD-students. The group focus on high-quality applied research. The current topics of interest in the group include student learning, transitions and career, teacher
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influencing factors and improve the accuracy, robustness and energy efficiency of intelligent sensing systems. Apply AI as an engineering tool: Use signal processing, statistical methods and machine learning
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flat interconnect AI compute clusters. Machine learning clusters and artificial intelligence (AI) training have become increasingly popular in recent years. The recent introduction of OpenAI’s ChatGPT