Jianlan Luo
About Jianlan Luo
Jianlan Luo is a Software Engineer with a strong background in machine learning and robotics. He has worked at notable companies such as Siemens, DeepMind, and Google, and holds a PhD in Robotics from the University of California, Berkeley.
Work at Intrinsic
Jianlan Luo has been employed at Intrinsic, an Alphabet company, as a Software Engineer since 2021. Located in Mountain View, California, Jianlan contributes to the development of advanced software solutions. Intrinsic focuses on applying artificial intelligence to robotics, aligning with Jianlan's expertise and interests in large-scale machine learning applications.
Current Role at Google
In addition to his role at Intrinsic, Jianlan Luo has been working at Google X, known as the moonshot factory, as a Machine Learning Engineer since 2020. This position also takes place in Mountain View, California. Jianlan's work involves exploring innovative machine learning technologies to address complex challenges, further enhancing his experience in the field.
Previous Experience at Siemens and DeepMind
Prior to his current positions, Jianlan Luo served as a Research Intern at Siemens from 2017 to 2018. He also gained experience as a Research Scientist Intern at DeepMind in 2020, where he worked for 11 months. Additionally, Jianlan interned at X, the moonshot factory, as an AI Intern in 2019 for 11 months, contributing to various projects that leveraged artificial intelligence.
Education and Expertise
Jianlan Luo earned a Doctor of Philosophy (PhD) in Robotics from the University of California, Berkeley, completing his studies from 2015 to 2020. He also holds a Master of Science (MS) degree in Computer Science from the same institution. His academic background provides a strong foundation for his research interests, which include deep reinforcement learning and deep unsupervised learning for robotic skill acquisition.
Research Publications and Contributions
Jianlan Luo maintains a personal homepage that details his research and publications. His work is accessible through his Google Scholar profile, which showcases his academic citations and contributions to the field of machine learning and robotics. This platform highlights his commitment to advancing knowledge in deep learning methodologies.