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The UBC Master of Data Science programs partner computer science and statistics experts, providing the foundation for a comprehensive approach, as these two disciplines are at the very core of the emerging field of Data Science. Through active and flexible learning techniques, students will be given the opportunity to put theory into practice and to work with real-world data.

Students learn from faculty working at the forefront of their fields. Internationally respected, these leading researchers collaborate with industries, governments and organizations to develop innovative solutions and make a tangible difference to our world. These thought leaders are passionate about their work, committed to student education and eager to share their knowledge.

Meet Some of Our Faculty and Staff

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Master of Data Science Okanagan  Shan Du

Shan Du, Assistant Professor, MDS Okanagan

"The MDS program equips students with comprehensive and intensive data science knowledge essential for entering data-related industries or academia after graduation. I am proud to be part of it.”

Shan Du is an assistant professor of Computer Science at UBC’s Okanagan Campus. She received the PhD degree from UBC Vancouver and the MSc degree from University of Calgary. Before joining UBC, she worked as an assistant professor with Lakehead University, Canada and as a Research Scientist/Software Engineer with IntelliView Technologies Inc., Canada. Shan is leading the Laboratory for Computational Vision and Intelligence at UBCO to investigate innovative technologies to address the most challenging issues in the field of image/video processing, computer vision/graphics, machine/deep learning, biometrics, and video surveillance systems. She has more than 15 years research and industrial development experience. Shan was recipient of many awards and grants, including NSERC-IRDF, NSERC-CGS D, AITF Industry r&D Associates Grant, ICASSP Best Paper Award, NSERC DG, CFI JELF, NFRF Exploration, etc. She is a senior member of IEEE, IEEE Signal Processing Society and IEEE Circuits and Systems Society. She is serving as an Associate Editor of IEEE Trans. on Circuits and Systems for Video Technology and IEEE Canadian Journal of Electrical and Computer Engineering, Area Chair of ICIP 2023, and served as Area/Session Chair of ICIP 2022, 2021, and 2019.

Learn more about Shan

Fatemeh Fard

Fatemeh Hendijani Fard, Assistant Professor, MDS Okanagan

"I am interested in the applications of data science and machine learning for software engineering. Specifically I am working on the detection and prediction of defect/anomalous behaviour in software. This also requires using big data analysis in practice."

Hendijani Fard obtained her PhD from the University of Calgary and her Master of Science from Amirkabir University. Fard's research interest includes mining Github repositories, natural language processing for software analytics, analyzing software defect databases, social media analysis in software analytics and analytics mobile applications. Currently, Hendijani Fard and her team are analyzing software energy bugs in mobile applications from two perspectives: Software and Users. They analyze massive sets of data from GitHub for a personalized recommender system for GitHub users.

Gittu George Master of Data Science Vancouver

Gittu George, Lecturer, MDS Vancouver

"MDS program is designed for students to be successful in the industry. You will be armed with techniques to combat enormous data flow."

Gittu started his academic journey back in 2009. Following his undergrad and master's in Computer Science, he started working in the biotechnology industry as an Engineer. During his industry career, he designed enterprise solutions and computational frameworks for large-scale genome and phenome data. Later his interest in the intersection of computer science and genomics lead him to do a Ph.D. in Bioinformatics from the University of Dundee, UK. During his PhD, he developed novel approaches to accelerate the computational time for genomic algorithms. He joined MDS program as a postdoctoral fellow in 2021.

Patricia Lasserre

Patricia Lasserre, Associate Professor, MDS Okanagan

"I love that the MDS program makes the students reflect on ethical issues associated with collecting and analyzing data. It is critical as data scientist that we recognize that we all have a role to play in protecting the ethics, privacy and security of the data we work with." 

Dr. P. Lasserre has completed her PhD on Vision for Autonomous Robots in Toulouse (France) in 1996. Since her appointment as Associate Professor at UBC Okanagan in July 2005, she has received the Teaching Excellence and Innovation award (2010), served on several administrative positions as associate dean, associate provost, and provost pro-term (2011-2019) where she participated in UBC wide Data Governance discussions. Her research interests include machine learning techniques in various applications, particularly deep learning in computer vision and OCR.

Master of Data Science Vancouver Vincent Liu

Vincent Liu, Postdoctoral Research and Teaching Fellow, MDS Vancouver

“There have been exciting advances in artificial intelligence driven by the growth in the size and complexity of data. The data science program equips student with the fundamental knowledge and cutting-edge techniques to analyze and leverage large amounts of data for real-world applications.”

Vincent joined UBC in March 2024 as a postdoctoral teaching and research fellow. He completed his PhD and MSc in Computing Science at the University of Alberta where his research focused on data-driven reinforcement learning. Prior to that, he graduated with a Bachelor of Business Administration from National Taiwan University. He is passionate about the use of foundation models for education and personalization.

Learn more about Vincent

Yves Lucet

Yves Lucet, Professor, MDS Okanagan

“Students in the MDS program learn not only the power but most importantly the common missteps one can make in data science. It is about critical thinking in a very complex environment that leverages powerful technologies: modeling, optimization, and data-based algorithms.”

Dr. Yves Lucet is a professor of computer science at the University of British Columbia. His research interests lie in optimization, computer-aided convex analysis, and efficient modeling that take advantage of problem structures. He is a co-recipient of the 2019 EURO Excellence in Practice Award for his work on using optimization to design safe roads at minimal cost. His latest interests are in the interactions between optimization and machine learning.

Master of Data Science Computational Linguistics Scott Mackie

Scott Mackie, Assistant Professor, MDS Computational Linguistics

"Language is a critical component of artificial intelligence. Solving the field's more challenging problems will require a combination of data science, machine learning, and linguistics. The traditional split between arts and sciences means that few people end up with this blend of skills. The MDS-CL program fills that gap, providing a cross-disciplinary education that helps graduates stand out in the job market."

Scott Mackie received his Ph.D in Linguistics from the University of British Columbia in 2017. He is interested in creating computational research tools, and was a founding member of the UBC Phonology Tools group, writing software for analyzing both spoken and signed languages. He spent 2018-2024 at Amazon, developing natural language understanding models for the Alexa voice assistant. He was also co-author on Amazon's M.A.S.S.I.V.E dataset, a parallel corpus of over 1M sentences spanning 51 languages. He returned to UBC in 2024 as an Assistant Professor in the MDS Computational Linguistics program. His current research focusses on using Retrieval Augmented Generation (RAG) techniques to improve the response quality of generative language models.

Master of Data Science Vancouver Payman

Payman Nickchi, Postdoctoral Research and Teaching Fellow, MDS Vancouver

"The UBC MDS program is designed to teach you techniques in the field of data science. It offers a balanced approach between theory and application, equipping you with the tools needed to apply your knowledge to real-world problems."

Payman began his role as a Postdoctoral Research and Teaching Fellow at UBC in September 2024. Earlier that year, in February, he completed his PhD in Statistics at Simon Fraser University, where his research focused on biostatistics and goodness-of-fit tests using empirical distribution functions. Before that, he earned a bachelor's degree in mathematical statistics and a master's degree in statistics from the University of Tehran. His passion for statistics, teaching, and data science brought him to this role. Outside of work, Payman enjoys swimming and capturing the night sky through astrophotography.

Joel Ostblom

Joel Östblom, Assistant Professor of Teaching, MDS Vancouver

"In addition to the core statistics and machine learning courses, MDS emphasizes the importance of data ethics, reproducibility, and open collaboration, which are crucial skills for a successful, sustainable data science career. Together with the diversity of educational backgrounds among students and instructors, this makes MDS an exciting place to both learn and teach!"

During his PhD, Joel developed a passion for data science and reproducibility through the development of quantitative image analysis pipelines for studying stem cell and developmental biology. He has since co-created or lead the development of several courses and workshops at the University of Toronto and the University of British Columbia. Joel cares deeply about spreading data literacy and excitement over programmatic data analysis, which is reflected in his contributions to open source projects and data science learning resources.
Learn more about Joel.

Jungyeul Park - MDS Computational Linguistics

Jungyeul Park, Lecturer, MDS Computational Linguistics

"UBC’s MDS Computational Linguistics is the study of data science and linguistics that empower students to be future ready with tools in computational linguistics. I’m excited to work with our students and explore the new era of natural language processing."  

Jungyeul Park received his Ph.D. in Linguistics from the Université Paris Diderot (Paris VII) in 2006. His interest in natural language processing motivated him to pursue Linguistics after initially studying Computer Science. His current research interests include machine learning approaches for morphology and syntax of natural language. He is currently a lecturer in the Department of Linguistics at the University of British Columbia (Vancouver, Canada) and an affiliate assistant professor in the Department of Linguistics at University of Washington (Seattle, USA). Before that he was a visiting assistant professor in the Department of Linguistics at the State University of New York at Buffalo during 2018-2019, a visiting assistant professor in the Department of Linguistics at the University of Arizona during 2016-2017, a research scientist at CEA (Commissariat à l'énergie atomique et aux énergies alternatives) during 2015-2016, and a lecturer (attaché temporaire d'enseignement et de recherche) in the Department of Computer Sciences at IUT de Lannion (Université de Rennes 1) during the academic year 2013-2014.