Yulia Pavlova, Ph.D.
About Yulia Pavlova, Ph.D.
Yulia Pavlova, Ph.D., serves as the Director of Technology Innovation at Thomson Reuters in Toronto, Canada, where she focuses on high-value projects in Deep Learning and Computer Vision. She has a strong academic background in applied mathematics and computer science, complemented by extensive experience in research and data science across various institutions.
Work at Thomson Reuters
Yulia Pavlova serves as the Director of Technology Innovation at Thomson Reuters, a position she has held since 2022 in Toronto, Ontario, Canada. In this role, she focuses on delivering high-value projects that leverage advanced technologies in Deep Learning and Computer Vision. Prior to her current role, she worked as a Senior Data Scientist at Thomson Reuters from 2020 to 2022, where she contributed to data-driven solutions and innovations.
Education and Expertise
Yulia Pavlova has a strong academic background in applied mathematics and computer science. She earned her MSc from Saint Petersburg State University, where she studied Applied Mathematics and Computer Science from 2000 to 2005. She then pursued a Doctor of Philosophy (PhD) in Scientific Computing at the University of Jyväskylä from 2005 to 2008. Additionally, she holds a PhD in Discrete Mathematics and Cybernetics from the same university. Her educational foundation supports her expertise in machine learning and AI technologies.
Background
Yulia Pavlova has held various research and leadership positions throughout her career. She worked as a Visiting Researcher at the International Institute for Applied Systems Analysis (IIASA) in 2011 and later as a Research Scholar at IIASA in 2008. Her previous roles include serving as a Principal Research Scientist at the Natural Resources Institute Finland (Luke) from 2015 to 2019 and at MTT Agrifood Research Finland from 2009 to 2014. She also worked as a Senior Data Analyst at Stora Enso in 2019.
Achievements
Yulia Pavlova has made significant contributions to the field of technology innovation, particularly in machine learning and AI. She created a customized sequence-to-sequence model for picture captioning and facial recognition. She has designed complex AI architecture pipelines for video processing and multilingual speech transcription. Additionally, she manages a team of engineers and data scientists, focusing on enhancing internal workflows and improving consumer satisfaction on commercial platforms.