Bojan Tunguz

Bojan Tunguz is a distinguished data scientist, renowned for his expertise in artificial intelligence (AI) and machine learning (ML). With a robust background in data science, Bojan specialises in areas such as predictive modelling, natural language processing, deep learning, and big data. His technical and quantitative prowess has made him a leading voice in the field, sought after as a keynote speaker at conferences on AI and machine learning. His ability to distill complex topics into accessible insights has earned him a reputation as an influential thought leader in the data science community.

Bojan moved to the United States in 1993 to pursue his academic journey at Stanford University, where he earned a B.S. in Physics and an M.S. in Applied Physics. He later completed a Ph.D. in Physics at the University of Illinois at Urbana-Champaign. His diverse academic and professional experiences have spanned various institutions, including Rhodes College and DePauw University, where he has shared his knowledge and passion for physics and data science. His career includes roles such as Senior Systems Software Engineer at NVIDIA, Data Scientist at H20.ai & Figure, and Machine Learning Modeler at ZestFinance.

Bojan’s background in physics laid the foundation for his transition into data science and AI. His curiosity and analytical mindset led him to create naboj.com, a platform that aggregates article abstracts from the arXiv preprint repository, providing real-time evaluation of scientific papers. This initiative reflects his deep commitment to advancing scientific discourse and leveraging technology to enhance research visibility. Furthermore, his work as a Visiting Scholar at Stanford’s High-Energy Physics Lab (HEPL) underscores his ongoing contribution to cutting-edge research in both physics and AI. He is also the author of “Non-local Gauge Field Theory”.

In addition to his technical contributions, Tunguz is the creator of Interedupedia, a wiki-like resource aimed at supporting international students navigating the U.S. education system. His personal experience as an international student has driven his desire to provide valuable information that can help others in similar situations. Through his efforts, he has not only advanced the field of data science but has also made significant strides in education and mentoring, solidifying his role as a leading figure in both academia and the data science industry.