Kun Yang work email
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Kun Yang personal email
I am a research assistant and a PhD candidate in electrical and electronics engineering at the University of Virginia, where I work on reinforcement learning and its applications to various domains, such as network slicing, vehicle behavior prediction, and federated learning. My research aims to develop and improve state-of-the-art algorithms and models that can solve challenging and impactful problems in artificial intelligence.I have a strong background and hands-on experience in machine learning, data science, and deep neural networks, acquired through my master's degree from Texas A&M University, multiple internships at prestigious companies, such as Intel, XPENG, and Kneron, and several online courses and certifications. I have implemented, evaluated, and demonstrated various projects using Python and other tools, and have contributed to multiple publications and patents. I am passionate about learning new skills and technologies, collaborating with diverse and talented teams, and applying my knowledge to real-world scenarios. I am looking for opportunities to further enhance my research and professional skills, and to make a positive difference in the field of artificial intelligence.
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Machine Learning EngineerGoogleCupertino, Ca, Us
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Sr. Data Science EngineerJuniper Networks Aug 2024 - PresentSunnyvale, Ca, Us -
Research AssistantUniversity Of Virginia Aug 2020 - Oct 2024Charlottesville, Va, Us -
Research InternIntel Corporation May 2022 - Aug 2022Santa Clara, California, Us1. Implemented an interface enabling message transfer and remote control between python-based deep learning framework and NS3 network simulator.2. Enabled a reinforcement learning algorithm that can effectively handle a radio resource management problem in a network-slicing scenario for delay-SLA violation minimization. It improved the violation rate from 40% to 10%.3. Developed an API that enables the remote control between the openfl and the NS3, enabling federated learning with more realistic network simulation. -
Research InternXpeng May 2021 - Aug 2021Guangzhou, Guangdong, Cn◦ Re-implemented well-known vehicle behavior prediction models VectorNet and TNT on an in-house dataset and delivered simulator-based demo.◦ Investigated effectiveness of different feature encoding methods in a vehicle behavior prediction system◦ Designed a new scheme combining VectorNet and Residual network, reaching 80% of TNT’s performance using 60% of the parameters -
Research InternKneron Aug 2020 - Dec 2020San Diego, California, Us◦ Developed a toolbox that can automatically schedule the optimal quantization precision combination of different layers in a neural network.◦ Quantized popular deep learning models with the toolbox that achieved less than 2% of accuracy loss with aroughly 50% computational cost reduction.◦ Surveyed and summarized the most recent and popular neural network quantization and compression methods and schemes. -
FellowInsight Data Science Jan 2020 - Apr 2020San Francisco, Ca, Us◦Worked with a gaming analytics company, Mayhem, to build a robust monitoring stack.◦Deployed a clone of Mayhem’s server and the monitoring stack on to AWS with Terraform.◦Collected enhanced monitoring metrics from Mayhem’s RDSMysql cluster using Prometheus.◦Designed a dashboard withGrafanathat can accurately reflect resource allocation and usage of an RDS database as well as the error and slow query log flow.◦Created alarms for potential spike traffic and resource shortage for the database.◦Launched the whole system onto Mayhem’s real server system. -
Master Of ScienceTexas A&M University Aug 2017 - Jan 2020College Station, Tx, Us -
Teacher'S AssistantTexas A&M University Aug 2018 - Nov 2018College Station, Tx, UsDesigned course's coding homework and part of the final project.Guided the students for their final projects.Corrected and advised the students' coding homework
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Swe-InternshipXpeng Jun 2019 - Aug 2019Guangzhou, Guangdong, Cn◦Robot Operating System(ROS) based traffic simulator:∗a.: Developed a new feature that enabled external control from the outside agents using C++ and Python, used by the behavior planning teams in the company.∗b.: Built an API that allowed the ROS simulator log data with a particular frequency and dumped them in CSV files using python, used by our team for further training.◦Study on automatic ramp merging:∗a: Designed a new reward function for the reinforcement learning ramp merging that treats safety as apart of reward rather than a hard boundary.∗b: Built a DQN and DDPG agent-based on Keras using python, able to achieve a 0.24% collision rate with our reward function, comparable to current state-of-art method S-T graph.
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Data Science InternshipHuawei Technologies Beijing Research Center Jul 2016 - Sep 2016Collected a huge amount (over 100000 pieces per day) of data from HUAWEI’s own git.Performed Apriori and Multi-level Based Data Mining Algorithm on judging if an engineer is facing a problem based on the frequency and the quantity of code the uploaded.Applied Spring MVC as the frame of the websiteManaged between different types of Databases using Java, including SQLServer and MySQL.
Kun Yang Skills
Kun Yang Education Details
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University Of VirginiaElectrical And Electronics Engineering -
Texas A&M UniversityElectrical And Electronics Engineering
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Tsinghua UniversityElectrical And Electronics Engineering
Frequently Asked Questions about Kun Yang
What company does Kun Yang work for?
Kun Yang works for Google
What is Kun Yang's role at the current company?
Kun Yang's current role is Machine Learning Engineer.
What is Kun Yang's email address?
Kun Yang's email address is ku****@****amu.edu
What schools did Kun Yang attend?
Kun Yang attended University Of Virginia, Texas A&m University, Tsinghua University.
What skills is Kun Yang known for?
Kun Yang has skills like Prometheus, Pandas, Scikit Learn, 数据分析, Linux, C, Reinforcement Learning, Matlab, Tensorflow, Terraform, Signal Processing, Latex.
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