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Master/Ph.D. openings for Artificial Intelligence and Applications
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Multiple Master's and Ph.D. positions with full RA/TA support are available in Hongyu An's research group. Our group currently focuses on Artificial Intelligence, Neuromorphic Computing, and their applications: 1. Robot Learning: Energy-Efficient Online learning through Spiking Neural Networks and Neuromorphic computing • collaborating with ETH Zurich on mobile robotics (https://www.ini.uzh.ch/en.html) 2. Neuromorphic computing on medical applications • Real-time Deep Brain Stimulation signal control using neuromorphic chips or edge computing platforms for Parkinson’s disease treatment 3. Learning Algorithms for Spiking Neural Networks and associative memory learning 4. Energy-efficient Neuromorphic Electronic Circuit Design for Artificial Neural Networks and Deep learning Hongyu is an assistant professor at the Electrical and Computer Engineering Department of Michigan Tech. His research interest mainly focuses on Neuromorphic Computing, Neuromorphic Electronic Circuits Design using Emerging Devices, Spiking Neural Networks, Intelligent Robotics, and Medical Applications. Neuromorphic computing is an emerging research topic that realizes artificial intelligence by mimicking and recreating the human brain, including neurons, synapses, and neural networks. This approach involves both hardware design and algorithm development, such as circuit design and neural network algorithms. Our group closely collaborates with top research groups/institutes, including Intel neuromorphic research lab (Loihi chips), Sandia National Labs, Oak Ridge National Labs, institute of neuroinformatic of ETH Zurich, on robotics, spiking neural networks, and medical applications. The group also has multiple ClearPath mobile robotics and Deep Brain Stimulation systems for our medical applications. Moreover, the group, as a neuromorphic community of intel labs, has the access to the Intel Loihi neuromorphic chips, which are the top-tier neuromorphic computing platform in the market. The PI processes the Dynamic Neuromorphic Asynchronous Processor (DYNAP) and the development kit. The DYNAP CNN development kit is a scalable, fully configurable digital event-driven neuromorphic processor with 1M ReLU spiking neurons per chip for implementing Spiking Convolutional Neural Networks (SCNN). This technology is ideal for always-on, ultra-low power, and ultra-low latency event-driven sensory processing applications. Our lab also has Clearpath Jackal mobile robot equipped with numerous sensors and computing platforms, such as Lidar Velodyne VLP-16, 1 Camera Stereolab Zed 2 Stereo, Nvidia Jetson Tk1, etc. Michigan Tech has both indoor and outdoor intelligent robot research testing environments. The Department of Electrical and Computer at Michigan Tech has two indoor robot research labs, which are 834 and 978 square feet. The indoor intelligent robot labs can conduct real-time testing on decision making, traffic light recognition, and navigation, etc. Additionally, the Keweenaw Research Center (KRC) at Michigan Tech is a multidisciplinary research center for autonomous vehicle and robotics research. KRC maintains more than 900 acres of the testing area, proving grounds, specifically developed for the evaluation of ground vehicle systems, such as different soil types for terrain assessment research. KRC test areas include a variety of maintained terrain courses including a “wadi” rock ditch, gravel side slopes, sand, etc. The projects will be assigned based on the student's background. Desired Skills: • Basic understanding of deep learning, neural networks • Programming experience in one or more of the following languages: Python, C++, Java, etc. • Programming experience on deep learning platforms: Pytorch, TensorFlow, etc. • Ability to communicate effectively (both verbal and written) • ROS system • Computational Neuroscience background is a big plus If interested, please send me your CV, transcript(s), TOEFL (international applicants only), and sample publications if applicable to email address: hongyua@mtu.edu |
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