hannibalwanglecter / large-scale-machine-learning-with-python

Code repository for Large Scale Machine Learning with Python, published by Packt

Thanks for Visiting my Pages! 👋

I'm Hao Wang 🇨🇳 !

• 🎓 Hao Wang, M.E. Candidate, is the postgraduate student of Computer Applied Technology. He is with the State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research at Beijing Normal University. Wang holds a B.E. in Computer Science and Engineering from Anhui Normal University (2014-2018), and has been on postgraduate student at Beijing Normal University since then.

• Wang is a member of Li's BCI Lab (Brain-Computer-Interface), which aim to help restore lost motor function to people with paralysis. Our research focus on Brain-computer interface technology and related neuroscience issues, including real-time decoding algorithms for motor cortex neural signals. In our lab, we use Plexon Omniplex to record Macaque's neural signal and decode its motor intention(mouse cursor) on the computer screen.

• 😃💡 Research Interests: Data Mining, Artificial Intelligence , Machine Learning, Neural Computation ,Control theory

• 👀🔭 Future goals: 1️⃣ Decoding: Explore how motor cortex encodes motor information by means of electrophysiology data or other modal data. :two: Combine Cognitive Neuroscience & Computer Science: Explore the similar or different representations and connections between biological brain and Artificial Intelligence models(interdisciplinary of cognitive neuroscience & computer science/control theory). :three: Neuromodulation: Using neuroscience methhods to enhance human being's cognitive ability.

• 📧 If you have any question about my projects, you can email me: [email protected]

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Research

• Motor Cortical Spikes Decoding on Matlab: Motor Cortex Decoding based on MATLAB (including Spikes and Local Field Potentials). Wang is a member of Li’s BCI Lab (Brain-Computer-Interface) at Beijing Normal University, where his group conducts neuroscience and neuroengineering research to better understand how the brain controls movement and to design medical systems to assist those with movement disabilities. His neuroscience research investigates the neural basis of movement preparation and generation using a combination of electrophysiological, behavioral, computational and theoretical techniques. His neuroengineering research investigates the design of high-performance neural prosthetic systems, which are also known as brain-computer interfaces and brain-machine interfaces. These systems translate neural activity from the brain into control signals for prosthetic devices, which assist people with paralysis by restoring lost function. This work includes statistical-signal processing, machine learning, low-power circuits and real-time system modeling and implementation.

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Skills and Tools

• Programming Language: MATLAB, C++, Python, LATEX, HTML, R

• Modeling and Analysis: TensorFlow, Keras, Caffe, Pytorch, Scikit-learn

• Software/System: Linux, Git, MATLAB parallel computing cluster, Docker

• Surgical Technique: Primate Electrode Implantation Surgery

• Neurobiological Techniques: Monkey Training, Electrophysiology Experiment, MRI Experimenter

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