Daniel KIM, PhD

Daniel KIM, PhD has a wealth of experience in the data science field. Daniel began their career in 2008 as an Internship Fellow at CYRAM. From 2012 to 2015, they were a Research Assistant at Samsung Economics Research Institute and a Post-doctoral researcher at Natural Science Research Institute, KAIST. In 2013, they were a Graduate Fellow at Santa Fe Institute, where they conducted web crawling and large-scale network analysis. Daniel also had two stints as a Visiting Research Assistant at Institute for New Economic Thinking at the Oxford Martin School, University of Oxford in 2013 and 2016. During their time there, they conducted large-scale network analysis and interactive data visualization using d3.js and processing.js. In 2016, they became a Data Scientist / Senior Consultant at Samsung SDS, where they were responsible for understanding client problems, project execution, management, allocation of resources, design and implementation of the solution. Daniel also acted as a thought leader on technical topics such as deep learning and was one of the main contributors on the core algorithms of Samsung IT FAIR 2021 Winner. From 2019 to 2020, they were a Lead Data Scientist and Senior Data Scientist at MSD, where they led a data science team and projects for many in-house clients. Daniel was responsible for end-to-end project execution, understanding the client problems, management, allocation of resources, design and implementation of the solution. Daniel'sachievements included increased revenue, cost savings, task acceleration, and awards. In 2020, they took on the role of Principal Data Scientist at MakinaRocks.

Daniel KIM obtained their Bachelor of Science (BS) in Physics from the Korea Advanced Institute of Science and Technology (KAIST) between 2004 and 2008. Daniel then went on to pursue a Doctor of Philosophy (PhD) in Physics at KAIST, which they completed in 2015. Prior to this, they attended the Jeonbuk Science High School between 2002 and 2004. In 2019, they also obtained a certification in Fundamentals of Deep Learning for Natural Language Processing from the NVIDIA Deep Learning Institute.