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
Giuseppe Carenini, Director, MDS Programs
"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
Jeff Andrews, Co-Director and Assistant Professor, MDS Okanagan
“The MDS program has been 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 assistant 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.
Mike Gelbart, Co-Director and Assistant Professor of Teaching, MDS Vancouver
"There’s something great about teaching students who understand the opportunity cost of their education. Many of them left good jobs or other opportunities to do this program — so they are here to work hard and make the most of the 10 months."
Mike Gelbart joined UBC in 2015 and was part of the team that designed the MDS curriculum. He holds an undergraduate degree in physics from Princeton University and a PhD from the machine learning group at Harvard University. Outside of UBC, Mike is also an advisor at Vanedge Capital, a local venture capital fund in the technology space. Learn more about Mike.
Bryan Gick, Director, MDS Computational Linguistics
“Language is no longer just our main tool for interfacing with other people, but has become our main tool for interfacing with new technology. Every company will need to be able to navigate this space at the intersection of language and technology – this is the space the Master of Data Science in Computational Linguistic program occupies.”
Bryan Gick is the Head of the Linguistics department, Director of the Master of Data Science in Computational Linguistics program and Director of UBC’s Interdisciplinary Speech Research Laboratory (ISRL). As well, at UBC, Bryan is Co-chair of the Language Sciences Initiative, and holds associate appointments in the Department of Psychology, the School of Audiology and Speech Sciences and the Institute for Computing, Information and Cognitive Systems. Bryan’s overarching research focus is on how people interact with each other and their environment, and how this interaction can inform models of linguistic communication.
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.
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. Learn more about Tiffany.
Muhammad Abdul-Mageed, Assistant Professor, MDS Computational Linguistics
"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.
Tomas Beuzen, Postdoctoral Research and Teaching Fellow, MDS Vancouver
"The huge diversity of expertise and backgrounds in the UBC-MDS teaching team and student cohorts makes the MDS program an amazingly well-rounded, practical and exciting program to be a part of - perfect for getting students ready to practice data science in the real-world!"
Originally from Sydney, Australia, Tomas developed a passion for engineering and science early on in life and, unwilling to choose just one, completed both a B.Eng (Civil Engineering) and B.Sc (Climate Science) at the University of New South Wales. During his undergraduate studies, Tomas discovered programming and data science and went on to complete a PhD in coastal engineering, in which he studied the application of machine learning techniques to better understand and predict coastal storm erosion. Tomas now has a keen interest in using data science to solve real-world, practical problems and joined MDS in August 2019 to share this passion with others. Learn more about Tomas.
John Braun, Professor, MDS Okanagan
Dr. John Braun obtained his Ph.D. from the University of Western Ontario. Braun's research interest includes computational statistics, with applications to fire science; statistical process control; and statistical education.
Julian Brooke, Instructor, MDS Computational Linguistics
“The Computational Linguistics option is aimed at helping those who, like me, have a love for language to turn that interest and experience into a career that will involve building cutting-edge technology.”
Julian Brooke has a Bachelor’s of Science in Symbolic Systems from Stanford University, a Masters of Arts in Linguistics from Simon Fraser University, and a Ph.D in Computer Science from the University of Toronto. For over 10 years, he has been carrying out research in diverse areas of computational linguistics, including applications in education, social science, the law, and literary studies. He recently taught computational linguistics as part of the MDS program at the University of Melbourne. His industry experience includes NLP projects at Microsoft, Thomson Reuters, and Maluaba.
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 analystics 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.
Varada Kolhatkar, 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.
Firas Moosvi, Lecturer, MDS Okanagan
"In this program, we think a lot about data, its potential, and its perils. We do our best to teach students the responsible use of data science while also underscoring the importance of reproducible analysis methods."
Firas Moosvi has a BSc from UBC in Honours Biophysics, an MSc in Medical Biophysics from the University of Toronto, and a PhD in Physics from UBC. His research interests are varied but the two main umbrellas are medical imaging for applications in cancer, and the scholarship of teaching and learning (SoTL). Most recently, he is looking at how the field of learning analytics can provide insight to surface and reduce inequities in STEM programs. Firas has a deep appreciation for data visualizations and is excited to bring his experience to the MDS program!
Apurva Narayan, Assistant Professor, MDS Okanagan
"With the advent of numerous safety-critical applications such as Unmanned Aerial Vehicles (UAV), Autonomous Cars, and the buzzing advancements in Internet of Things (IoT), the software systems have become complex and the problem of data deluge is intensifying. Graduates from the data science program here at UBC can help understand these complex systems and make these systems safe and secure for the masses."
Dr. Apurva Narayan obtained his Ph.D. from the Department of Systems Design Engineering, University of Waterloo and his Bachelor’s degree in Electrical Engineering from Dayalbagh Educational Institute in 2015 and 2008 respectively. Dr. Narayan’s research investigates artificial intelligence/machine learning with emphasis on explainable AI/ML and quantum machine learning, data mining, data analytics, safety and security of cyber physical systems, software engineering, graph theoretic analysis of complex systems, and decision-making under uncertainty.
Joel Ostblom, Postdoctoral Research and Teaching Fellow, 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, Postdoctoral Research and Teaching Fellow, 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.
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-CL 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.
Irene Vrbik, Instructor, MDS Okanagan
“The need for Data Scientists has grown rapidly over a relatively short amount of time. I am proud to be contributing to a program that is keeping pace with this demand.”
Irene Vrbik completed her PhD in Statistics at the University of Guelph and is a newly appointed instructor at the University of British Columbia Okanagan. As a former NSERC Postdoctoral Fellow (UBC Okanagan) and postdoctoral researcher (McGill University), her research has covered a range of topics including: modelling the spread of fire, developing semi-supervised learning algorithms, presenting theoretical results for robust distributions, and analyzing HIV transmission dynamics with phylogenetic data.
Kate Lewis, Program Administrator, MDS Computational Linguistics
"The enthusiasm and drive of UBC students has inspired me over the past eight years, and I’m excited to be a part of the new CL option available for them."
Kate Lewis joined the University of British Columbia in 2010 and during this time has worked with students, faculty and the greater community across campus, from Enrolment Services to graduate student support. Most recently she oversaw the practical implementation of a new Graduate certificate program at UBC. Prior to this, Kate worked at the University of Alberta where she gained expertise in navigating post-secondary administration. She is committed to ensuring students have a positive experience throughout their program, from application to graduation.
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.
Angela Pau, Career Advisor, MDS Program
“The continued growth of Data Science jobs across many different industries and the ability to impact business, community and societal decisions makes this a really exciting field of work to be in.”
Angela Pau is an advisor and educator with over 15 years of experience supporting individuals to reach their career goals. She has a Bachelor of Arts from Simon Fraser University and has experience working in both the public and non-profit sector. At UBC she has developed career programming for both undergraduate and graduate students across a multitude of faculties and departments. She also has experience collaborating with campus partners to develop and implement career development strategies for international students and mentoring programs. Since joining MDS, Angela is excited to be making so many new connections to employers, MDS alumni and students who are passionate about Data Science.
Ryan Taylor, Career Planning and Placement Coordinator, MDS Computational Linguistics
"As a professional program, our goal is to give students the training that they need to get the jobs they want. In putting together the program, this meant researching industry trends, labour market statistics and student interests. In practice, this means collaborating with industry, students and faculty every day to make the MDS Computational Linguistics program the best it can be.”
Ryan has a passion for helping students to thrive in their post-graduation career. He began working at UBC in 2016, and over the next two years helped to create what would become the MDS Computational Linguistics program. Prior to starting at UBC, Ryan had worked at a computational linguistics firm in Quebec and completed a PhD in Psycholinguistics with a certificate in Behavioral and Cognitive Neuroscience from the University of Groningen in the Netherlands. He’s keen to put knowledge of industry and data science to the service of students in building the careers they desire.