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.
"Our Data Science program offers a solid academic program with courses that were designed specifically for our students, with their needs and skills in mind. Moreover, our curriculum is revised and updated regularly, and our academic staff and students are in close communication with industry (e.g. preparing and delivering capstone projects). The result is that our students learn the conceptual foundations of data science and the latest tools used in industry in a program created and delivered exclusively for them, and they do it in a collegial, diverse and inclusive environment."
Matías Salibián-Barrera joined UBC as a faculty member in 2004, and is currently a Professor in the Department of Statistics. In 2015 he received the CRM-SSC Prize in Statistics, which recognizes research accomplishments during the the first fifteen years after receiving a PhD. His research interests revolve around the problem of extracting reliable information from data sets that may not be completely trustworthy. Early on in his career he worked in the statistical software industry, and his contributions are being widely used. At UBC, he created the Statistics Department course on Statistical Learning, and participated in the creation of UBC's first undergraduate Data Science course (DSCI 100), which now attracts over 1000 students per year across all faculties.
Jeff Andrews, Principal Co-Director and Associate Professor, MDS Okanagan
“The MDS program has been a shining example of inter-disciplinary and inter-campus collaboration, culminating in a professional degree that employers, alumni, instructors, and current students all value. I am proud to be a part of it."
Jeff Andrews is an associate professor of statistics and leads the Statistical Machine Learning Laboratory at UBC’s Okanagan Campus. His research primarily focuses on unsupervised machine learning with mixture models, including model development, implementation, and optimization. He has been a recipient of two international awards for his research in this field: the 2017 Chikio Hayashi Award for Young Researchers from the International Federation of Classification Societies, and the 2013 Distinguished Dissertation Award from the Classification Society. He has attracted more than $200k in research funding as a primary investigator since joining UBC in 2015, and more than triple that as co-investigator on several collaborative and interdisciplinary projects—such as the Medical Physics and Data Analytics Cluster. Beyond his academic research, he has consulting experience from a diverse range of industries --- including sport management, food product evaluation, workplace safety, biomedical instruments, heavy machinery, and the financial sector.
Khalad Hasan, Co-Director and Assistant Professor, MDS Okanagan
"The MDS program is an exciting journey for the students as it provides them the opportunity to build a strong understanding of data science subject matters and use this knowledge out in the wild."
Khalad Hasan is an assistant professor of computer science at UBC’s Okanagan campus. His research interest is in human-computer interaction, with a focus on developing and studying novel interactions with mobile and wearable devices. More specifically, he is interested in exploring users’ needs and making an impact in their lives, specifically when it concerns interacting with large data on small devices. Before joining UBC Okanagan, Khalad worked as an NSERC postdoctoral fellow at the University of Waterloo.
Varada Kolhatkar, Co-Director and Assistant Professor of Teaching, MDS Vancouver
"With a large amount of data available in different disciplines and powerful technology at our fingertips, it is tempting to throw data and technology at problems without deeper understanding of them. This way we easily end up with misleading interpretations of the data. This program teaches you how to interpret your data responsibly and answer data-related questions in a principled way, without ignoring the limitations of the technology or the data."
Varada Kolhatkar was born and raised in Pune, India, where she completed her undergraduate degree in Computer Science. After working in industry for two years in India, she pursued her Master’s degree from the University of Minnesota Duluth and a Ph.D. degree from the University of Toronto, both in Computer Science, specializing in Computational Linguistics. Before moving to UBC, Varada spent two years at Simon Fraser University as a post-doctoral fellow, where she developed datasets and computational tools that will help keep online communities engaged in constructive discussions. Varada has diverse experience of working in industry as well as in academia with different universities, countries, and cultures. She joined MDS in October 2018 as a teaching and research postdoctoral fellow. For Varada, learning and sharing knowledge are deeply satisfying practices, expressions of who we are and what we can achieve as human beings and her goal as a teacher is to instill this satisfaction in learning and sharing knowledge by encouraging learners to challenge, to discover, to try out new things, and to think about something in a way they had never thought before.
Garrett Nicolai, Director and Assistant Professor of Teaching, MDS Computational Linguistics
"It's a really exciting time to be working in NLP. The field has been revolutionized multiple times in the past decade, and we are seeing great progress solving problems that were unfathomable in the past. I'm thrilled to be working with the MDS-CL as we prepare students to process, analyse, and model data that is increasing at an unprecedented rate."
Garrett Nicolai joined the MDS Computational Linguistics program in 2020 as a post-doctoral researcher and Capstone mentor, before becoming an Assistant Professor of Teaching. Garrett completed his MSc. in Artificial Intelligence at the University of Regina before obtaining a PhD in NLP at the University of Alberta, completing a BA in Linguistics along the way. Before coming to Vancouver, Garrett was a post-doctoral researcher at Johns Hopkins University's Center for Language and Speech Processing, working on low-resource computational morphology. His research interests lie in improving the quality of computational tools for under-resourced languages, including the construction of computational corpora for such purposes.
Tiffany Timbers, Co-Director and Assistant Professor of Teaching, MDS Vancouver
"We teach cutting-edge tools and techniques that are used by data scientists out in the wild."
Tiffany Timbers received her Bachelor of Science in Biology from Carleton University in 2001, following which she completed a doctorate in neuroscience at the University of British Columbia in 2012, which focused on the genetic basis of learning and memory. After obtaining her doctorate, Tiffany carried out data-intensive postdoctoral research in behavioural and neural genomics at Simon Fraser University (published in PLoS Genetics). During this time, she also gained valuable experience teaching computational skills to students and scientists through her work with Data and Software Carpentry, the SFU scientific programming study group, and teaching a course in computation in Physical Sciences at Quest University. Tiffany began her teaching role in the MDS program at UBC in the summer of 2016.
"The MDS program is designed to give students the relevant ‘hands on’ skills they need to succeed as data scientists. The strengths of the program include the diversity of the instructors and the evolving curriculum to meet current industry needs and standards."
Ifeoma Adaji is an assistant professor of computer science at UBC's Okanagan campus. She completed her Master's degree from the University of Aberdeen in Scotland, UK and her Ph.D. from the University of Saskatchewan in Canada. She briefly worked in industry as a data scientist after her Ph.D. in lieu of a postdoc. Her research interests include the development of tailored persuasive technologies for social good and the use of user generated data online to understand and predict the behaviour of online users. She is also interested in Fairness, Accountability, Transparency & Ethics in AI (FATE).
Katie Burak, Assistant Professor of Teaching, MDS Vancouver
“The MDS program provides students the tools they need to tackle real-world problems in a variety of industries. Focusing on both theoretical and applied aspects of data science, the faculty at MDS strive to prepare students to be successful outside of the classroom.”
Katie completed her PhD in Statistics at the University of Alberta where her academic work focused on increasing the computational efficiency of nonparametric approaches such as bootstrapping using concentration of measure. Prior to that, she completed her undergraduate and master’s degrees in Mathematics and Statistics, respectively. Katie has a passion for statistical outreach and education and has organized a variety of outreach events in her community. Additionally, she is interested in investigating modern pedagogical methods and best teaching practices in the field of data science.
Daniel Chen, Postdoctoral Research and Teaching Fellow, MDS Vancouver
"The MDS faculty puts a tremendous amount of effort on the education and pedagogy of learning real-world data science skills. The courses are constantly adapting to new tools and gives the opportunity to practice the skills used in the workplace. During the capstone project, each learner consolidates all the skills into a specific domain in a collaborative team environment."
Daniel received their Bachelor of Arts in Psychology and Behavioral Neuroscience from Macaulay Honors College at CUNY Hunter College and their Master of Public Health in Epidemiology from Columbia University Mailman School of Public Health. Their PhD work was on data science education in the biomedical sciences from Virginia Tech where they looked at the process of creating and assessing the effectiveness of domain-specific data science materials with learner personas. They have also been involved with The Carpentries since 2014 where has has been an instructor, instructor trainer, and community maintainer lead. Daniel is a Data Science Educator at RStudio, PBC and joined the MDS faculty in March of 2022.
"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.
"Our Data Science program offers a solid academic program with courses that were designed specifically for our students, with their needs and skills in mind. Moreover, our curriculum is revised and updated regularly, and our academic staff and students are in close communication with industry (e.g. preparing and delivering capstone projects). The result is that our students learn the conceptual foundations of data science and the latest tools used in industry in a program created and delivered exclusively for them, and they do it in a collegial, diverse and inclusive environment."
Matías Salibián-Barrera joined UBC as a faculty member in 2004, and is currently a Professor in the Department of Statistics. In 2015 he received the CRM-SSC Prize in Statistics, which recognizes research accomplishments during the the first fifteen years after receiving a PhD. His research interests revolve around the problem of extracting reliable information from data sets that may not be completely trustworthy. Early on in his career he worked in the statistical software industry, and his contributions are being widely used. At UBC, he created the Statistics Department course on Statistical Learning, and participated in the creation of UBC's first undergraduate Data Science course (DSCI 100), which now attracts over 1000 students per year across all faculties.
Varada Kolhatkar, Co-Director and Assistant Professor of Teaching, MDS Vancouver
"With a large amount of data available in different disciplines and powerful technology at our fingertips, it is tempting to throw data and technology at problems without deeper understanding of them. This way we easily end up with misleading interpretations of the data. This program teaches you how to interpret your data responsibly and answer data-related questions in a principled way, without ignoring the limitations of the technology or the data."
Varada Kolhatkar was born and raised in Pune, India, where she completed her undergraduate degree in Computer Science. After working in industry for two years in India, she pursued her Master’s degree from the University of Minnesota Duluth and a Ph.D. degree from the University of Toronto, both in Computer Science, specializing in Computational Linguistics. Before moving to UBC, Varada spent two years at Simon Fraser University as a post-doctoral fellow, where she developed datasets and computational tools that will help keep online communities engaged in constructive discussions. Varada has diverse experience of working in industry as well as in academia with different universities, countries, and cultures. She joined MDS in October 2018 as a teaching and research postdoctoral fellow. For Varada, learning and sharing knowledge are deeply satisfying practices, expressions of who we are and what we can achieve as human beings and her goal as a teacher is to instill this satisfaction in learning and sharing knowledge by encouraging learners to challenge, to discover, to try out new things, and to think about something in a way they had never thought before.
Tiffany Timbers, Co-Director and Assistant Professor of Teaching, MDS Vancouver
"We teach cutting-edge tools and techniques that are used by data scientists out in the wild."
Tiffany Timbers received her Bachelor of Science in Biology from Carleton University in 2001, following which she completed a doctorate in neuroscience at the University of British Columbia in 2012, which focused on the genetic basis of learning and memory. After obtaining her doctorate, Tiffany carried out data-intensive postdoctoral research in behavioural and neural genomics at Simon Fraser University (published in PLoS Genetics). During this time, she also gained valuable experience teaching computational skills to students and scientists through her work with Data and Software Carpentry, the SFU scientific programming study group, and teaching a course in computation in Physical Sciences at Quest University. Tiffany began her teaching role in the MDS program at UBC in the summer of 2016.
Katie Burak, Assistant Professor of Teaching, MDS Vancouver
“The MDS program provides students the tools they need to tackle real-world problems in a variety of industries. Focusing on both theoretical and applied aspects of data science, the faculty at MDS strive to prepare students to be successful outside of the classroom.”
Katie completed her PhD in Statistics at the University of Alberta where her academic work focused on increasing the computational efficiency of nonparametric approaches such as bootstrapping using concentration of measure. Prior to that, she completed her undergraduate and master’s degrees in Mathematics and Statistics, respectively. Katie has a passion for statistical outreach and education and has organized a variety of outreach events in her community. Additionally, she is interested in investigating modern pedagogical methods and best teaching practices in the field of data science.
Daniel Chen, Postdoctoral Research and Teaching Fellow, MDS Vancouver
"The MDS faculty puts a tremendous amount of effort on the education and pedagogy of learning real-world data science skills. The courses are constantly adapting to new tools and gives the opportunity to practice the skills used in the workplace. During the capstone project, each learner consolidates all the skills into a specific domain in a collaborative team environment."
Daniel received their Bachelor of Arts in Psychology and Behavioral Neuroscience from Macaulay Honors College at CUNY Hunter College and their Master of Public Health in Epidemiology from Columbia University Mailman School of Public Health. Their PhD work was on data science education in the biomedical sciences from Virginia Tech where they looked at the process of creating and assessing the effectiveness of domain-specific data science materials with learner personas. They have also been involved with The Carpentries since 2014 where has has been an instructor, instructor trainer, and community maintainer lead. Daniel is a Data Science Educator at RStudio, PBC and joined the MDS faculty in March of 2022.
Gittu George, Postdoctoral Research and Teaching Fellow, 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.
Quan Nguyen, Postdoctoral Research and Teaching Fellow, MDS Vancouver
"After completing 10 months of this intensive data science master program, you will be prepared with industry desirable skills and knowledge to tackle real-world challenges using data."
Quan Nguyen, Ph.D. began his teaching role in the MDS program at UBC in the summer of 2021. Prior to joining UBC, he was a Postdoctoral Research Fellow in Learning Analytics and taught in the Master of Applied Data Science at the University of Michigan. His research applies statistical and machine learning techniques on large-scale clickstream data from learning management systems to predict student performance and interactions. Quan completed his Ph.D. in Learning Analytics from The Open University and received his Bachelor’s and Master’s degree in Economics from Maastricht University.
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.
Alexi Rodriguez-Arelis, Assistant Professor of Teaching, MDS Vancouver
"One of the MDS program's most outstanding strengths is its background diversity within the teaching team and student cohorts. Furthermore, the program has the perfect balance of Machine Learning and Statistics courses which are complimentary. We strive to provide students with the right theoretical and practical foundations to approach real-life and crucial data-related inquiries."
Alexi Rodríguez-Arelis completed his PhD in Statistics at the University of British Columbia in 2020. Born and raised in Mexico, he pursued an undergraduate degree in Industrial Engineering and a master's degree in Applied Statistics at Tecnológico de Monterrey. His machine learning research focuses on computer experiments that emulate scientific and engineering systems via Gaussian stochastic processes. Moreover, he has professional experience in the financial sector along with statistical consulting. Throughout his PhD program, Alexi developed an enthusiasm for teaching Statistics in a Data Science context. He is particularly passionate about projects involving the use of Data Science for social good. Alexi commenced his current role at MDS in January 2021. Learn more about Alexi.
Milad Maymay, Director, Program Operations and Student Management, MDS Vancouver
"Nearly all the employers I talk to are starting to recognize [or appreciate] the real need for trained and knowledgeable staff who can help them not only make sense of, but also develop the thread of a story, from the vast amount of data that is out there."
Milad Maymay received his Bachelor of Science at the University of British Columbia. He has over 17 years of experience managing projects and programs in both the non-profit and public sectors. At UBC he has managed the Work Study/Work Learn program, the NSERC Undergraduate Research Awards, and the launch of the CareersOnline management system. A trained career educator, he has experience in helping students explore career options, write resumes and cover letters, practise interview skills, and negotiate salaries. Over the years he has built excellent relationships with the local employer community, which helps MDS students achieve their ultimate goal of a fulfilling career as a data scientist.
"Our Data Science program offers a solid academic program with courses that were designed specifically for our students, with their needs and skills in mind. Moreover, our curriculum is revised and updated regularly, and our academic staff and students are in close communication with industry (e.g. preparing and delivering capstone projects). The result is that our students learn the conceptual foundations of data science and the latest tools used in industry in a program created and delivered exclusively for them, and they do it in a collegial, diverse and inclusive environment."
Matías Salibián-Barrera joined UBC as a faculty member in 2004, and is currently a Professor in the Department of Statistics. In 2015 he received the CRM-SSC Prize in Statistics, which recognizes research accomplishments during the the first fifteen years after receiving a PhD. His research interests revolve around the problem of extracting reliable information from data sets that may not be completely trustworthy. Early on in his career he worked in the statistical software industry, and his contributions are being widely used. At UBC, he created the Statistics Department course on Statistical Learning, and participated in the creation of UBC's first undergraduate Data Science course (DSCI 100), which now attracts over 1000 students per year across all faculties.
Jeff Andrews, Principal Co-Director and Associate Professor, MDS Okanagan
“The MDS program has been a shining example of inter-disciplinary and inter-campus collaboration, culminating in a professional degree that employers, alumni, instructors, and current students all value. I am proud to be a part of it."
Jeff Andrews is an associate professor of statistics and leads the Statistical Machine Learning Laboratory at UBC’s Okanagan Campus. His research primarily focuses on unsupervised machine learning with mixture models, including model development, implementation, and optimization. He has been a recipient of two international awards for his research in this field: the 2017 Chikio Hayashi Award for Young Researchers from the International Federation of Classification Societies, and the 2013 Distinguished Dissertation Award from the Classification Society. He has attracted more than $200k in research funding as a primary investigator since joining UBC in 2015, and more than triple that as co-investigator on several collaborative and interdisciplinary projects—such as the Medical Physics and Data Analytics Cluster. Beyond his academic research, he has consulting experience from a diverse range of industries --- including sport management, food product evaluation, workplace safety, biomedical instruments, heavy machinery, and the financial sector.
Khalad Hasan, Co-Director and Assistant Professor, MDS Okanagan
"The MDS program is an exciting journey for the students as it provides them the opportunity to build a strong understanding of data science subject matters and use this knowledge out in the wild."
Khalad Hasan is an assistant professor of computer science at UBC’s Okanagan campus. His research interest is in human-computer interaction, with a focus on developing and studying novel interactions with mobile and wearable devices. More specifically, he is interested in exploring users’ needs and making an impact in their lives, specifically when it concerns interacting with large data on small devices. Before joining UBC Okanagan, Khalad worked as an NSERC postdoctoral fellow at the University of Waterloo.
Ifeoma Adaji, Assistant Professor, MDS Okanagan
"The MDS program is designed to give students the relevant ‘hands on’ skills they need to succeed as data scientists. The strengths of the program include the diversity of the instructors and the evolving curriculum to meet current industry needs and standards."
Ifeoma Adaji is an assistant professor of computer science at UBC's Okanagan campus. She completed her Master's degree from the University of Aberdeen in Scotland, UK and her Ph.D. from the University of Saskatchewan in Canada. She briefly worked in industry as a data scientist after her Ph.D. in lieu of a postdoc. Her research interests include the development of tailored persuasive technologies for social good and the use of user generated data online to understand and predict the behaviour of online users. She is also interested in Fairness, Accountability, Transparency & Ethics in AI (FATE).
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.
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.
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.
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.
Gema Rodrigues-Peres, Assistant Professor, MDS Okanagan
"Working with data allows MDS students to play with knowledge. The MDS program is an amazing opportunity for them to expand their skillset and knowledge and make an impact in today’s world. I’m glad to be part of this program."
My research work focuses on empirical software studies that mine the development historical data of software systems. I use a combination of quantitative and qualitative techniques to understand the problem and determine approaches that can help to solve it. Specifically, I research the technical and non-technical aspects in software engineering with the aim of improving software development processes and practices, and increasing diversity in online communities.
John Thompson, Assistant Professor, MDS Okanagan
"The MDS program brings together bright students from various disciplines and trains them in statistics and machine learning skills needed to be successful data scientists. I'm excited to participate in a program dedicated to developing the quantitative skills needed for handling modern, complex data problems."
John R.J. Thompson is an assistant professor of statistics at UBC's Okanagan campus whose areas of expertise are nonparametric statistics and machine learning. John's statistical research interests lie in nonparametric statistics, clustering, metric learning, climate risk evaluation through direct and indirect environmental impacts, modelling the behaviours of Canadian investors under the guidance of financial advisors, and designing effective financial measures and Robo-tools that aid financial advisors in supporting their clients' investment portfolios. John is a member of Canada's Financial Wellness Lab, which aims to develop data-driven tools that Canadians can use to improve their financial resilience, reduce financial stress, and support better financial decision-making.
"Our Data Science program offers a solid academic program with courses that were designed specifically for our students, with their needs and skills in mind. Moreover, our curriculum is revised and updated regularly, and our academic staff and students are in close communication with industry (e.g. preparing and delivering capstone projects). The result is that our students learn the conceptual foundations of data science and the latest tools used in industry in a program created and delivered exclusively for them, and they do it in a collegial, diverse and inclusive environment."
Matías Salibián-Barrera joined UBC as a faculty member in 2004, and is currently a Professor in the Department of Statistics. In 2015 he received the CRM-SSC Prize in Statistics, which recognizes research accomplishments during the the first fifteen years after receiving a PhD. His research interests revolve around the problem of extracting reliable information from data sets that may not be completely trustworthy. Early on in his career he worked in the statistical software industry, and his contributions are being widely used. At UBC, he created the Statistics Department course on Statistical Learning, and participated in the creation of UBC's first undergraduate Data Science course (DSCI 100), which now attracts over 1000 students per year across all faculties.
Garrett Nicolai, Director and Assistant Professor of Teaching, MDS Computational Linguistics
"It's a really exciting time to be working in NLP. The field has been revolutionized multiple times in the past decade, and we are seeing great progress solving problems that were unfathomable in the past. I'm thrilled to be working with the MDS-CL as we prepare students to process, analyse, and model data that is increasing at an unprecedented rate."
Garrett Nicolai joined the MDS Computational Linguistics program in 2020 as a post-doctoral researcher and Capstone mentor, before becoming an Assistant Professor of Teaching. Garrett completed his MSc. in Artificial Intelligence at the University of Regina before obtaining a PhD in NLP at the University of Alberta, completing a BA in Linguistics along the way. Before coming to Vancouver, Garrett was a post-doctoral researcher at Johns Hopkins University's Center for Language and Speech Processing, working on low-resource computational morphology. His research interests lie in improving the quality of computational tools for under-resourced languages, including the construction of computational corpora for such purposes.
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.
Miikka Silfverberg, Assistant Professor, MDS Computational Linguistics
“The amount of useful language data on the internet is vast and continuously growing. The MDS Computational Linguistics program makes you an expert at processing and understanding language data using cutting-edge technologies such as deep neural networks.”
Miikka Silfverberg joined MDS Computational Linguistics program as an Assistant Professor in 2020. Miikka has a PhD in Language Technology and an M.Sc in Mathematics from the University of Helsinki. After completing his PhD, Miikka spent one and a half years as a postdoctoral researcher at the University of Colorado at Boulder where he worked on topics related to computational modeling of word structure using deep neural networks. Miikka’s research focuses on broadening the understanding of how deep neural networks learn to represent information about language.
Jian Zhu, Assistant Professor, MDS Computational Linguistics
"I am thrilled to be teaching the MDS-CL program at a time when Natural Language Processing (NLP) is advancing at a rapid pace. With breakthroughs in deep learning, we are witnessing a revolution in the way machines understand and process human language. As an instructor, I am excited to share my knowledge and expertise with the students, and to guide them as they explore the latest NLP techniques and technologies. It is an exciting time to be at the forefront of this field, and I can't wait to see what the future holds for NLP and its applications."
Jian Zhu received his Ph.D. degree in Linguistics and Scientific Computing from the University of Michigan, Ann Arbor in 2022. After his Ph.D., Jian had conducted NLP research both in the industry and in the academia. Before joining UBC, Jian was a post-doctoral research fellow in the School of Information at University of Michigan, working on the large-scale computational sociolinguistics. His current research interests lie in teaching machines to recognize spoken languages across the world and unstanding people's linguistic behavior in the online communities through large-scale computational methods.
Kenna McEwan, Program Manager, MDS Computational Linguistics
“I’m inspired by the work ethic and drive of the MDS students and am excited to support students in creating a healthy learning environment as they delve into the study of data science”
Kenna McEwan is born and raised in British Columbia and received her Bachelors in Linguistics at the University of British Columbia. Prior to taking on the Masters of Data Science - Computational Linguistics Program Manager role, she has worked at UBC in both undergraduate and research-based graduate programs, where she gained skills in navigating post-secondary administration. Kenna is committed to supporting students in having a positive experience during their time in the program, from application to graduation.
Sonya Thomlinson, Career Advisor, MDS Okanagan and Computational Linguistics
“Data Science is a vast and exciting field with the potential to create enormous impact across all sectors and industries. I’m thrilled to be part of one of the highest rated Data Science Professional Programs in Canada."
Sonya Thomlinson has been an entrepreneur for over 20 years as a founder of multiple businesses as well as a US non-profit. Sonya has been building relationships and working with individuals to help them attain their career goals in the MDS program at UBC Okanagan and CL in Vancouver. Since joining UBC in 2022, Sonya has enjoyed the energy and excitement on campus and is passionate about helping students prepare for their future careers, discover their own areas of passion, and ensure that they have the tools to succeed to their fullest potential.
Vanessa Ho, Marketing Coordinator, MDS Program
"I am always amazed and blown away with all the students who pass through the MDS program. They all come from diverse backgrounds who learn from each other as they go through this intensive 10-month program on their path to a new career in data science."
Vanessa Ho obtained her Bachelor's of Journalism degree from the University of Regina and worked for four years as a technology journalist in Toronto. Vanessa moved back to Vancouver in 2008 and transitioned into a career as a digital content creator for a variety of technology companies in the Vancouver area. She started at the MDS program in 2018 as the marketing coordinator chronicling the MDS student journey. Outside of MDS, Vanessa is a pop culture enthusiast and enjoys biking and baking.
Muhammad Abdul-Mageed, Assistant Professor, MDS Computational Linguistics (On Leave)
"Deep learning is revolutionary. Some of the most exciting progress in deep learning is happening with language. It is in your car, your browser, and your pocket. Deep learning of language is in its infancy, with fascinating progress ahead.”
Muhammad Abdul-Mageed is an Assistant Professor of Computational Linguistics, Information Science, and Computer Science and Director of the Natural Language Processing Lab at the UBC. He is a core member of UBC Institute for Computing, Information and Cognitive Systems and Centre for Artificial Intelligence Decision-making and Action. His research focuses on developing novel deep learning methods for natural language socio-pragmatics, with a goal to build `social’ machines to enhance human health and well-being.
Giuseppe Carenini, Director, MDS Programs (On Leave)
"One of the most unique aspects of this program is that it is designed for students whose main expertise is not in CS and Stats, but rather in other fields like life sciences, healthcare, business, and journalism; after graduation our students will be ready to effectively work as data scientist in those domains."
Joining the University of British Columbia’s Computer Science Faculty in 2004, Giuseppe Carenini has been teaching artificial intelligence, machine learning and natural language processing, for over 15 years. In his research, Giuseppe has focused on text summarization, information visualization, and decision support, publishing over 120 peer-reviewed publications and receiving two best-paper awards – one from the UMAP 2014 conference (premier user modeling conference ) and the other from the ACM-TiiS-14 journal (top journal on Intelligent Interfaces). Giuseppe's research has been applied by companies like Microsoft, IBM, Google, Huawei and Yahoo to develop summarization techniques for product reviews and for conversational data (e.g., emails and blog), as well as basic techniques for discourse parsing and topic modelling. Giuseppe has also collaborated with local companies that aim to make data more useful in supporting complex decisions (Compass) and for public engagement (Metroquest). Currently, he is serving as the ConVISation Labs Chief Scientific Officer, with the goal of transferring his research on text analytics to the healthcare domain, in collaboration with the WelTel company
