Courses in the UBC Master of Data Science - Vancouver program are primarily taught by our core teaching team. The team is in constant communication to share ideas, support each other, and collaboratively build the best program we can. These are the faces that you will be seeing every day throughout the MDS program.
- 11 : The total number of different languages we speak (including Spanish, Kurdish, Vietnamese, Mandarin, Swedish and Marathi)
- 13 : The total number of coding languages we have experience working with as a whole.
- 8 : The number of different countries our team cheers for during the Olympics.
- 7.4 : The average number of years our team has of teaching experience (with a standard deviation of 2.1).
- 11 : The median number of postsecondary education years our team has studied.
- The team often uses Bitmojis to communicate with one another.
- The team is an assortment of morning birds (early risers) and night owls (late sleepers).
- We have a teamwork contract that promotes a respectful and transparent work environment.
- We hold weekly team meetings where we discuss not only our work progress but also our social wellbeing (this was implemented during COVID when we were working from home and we decided to keep it).
Florencia D’Andrea, Postdoctoral Research and Teaching Fellow
Florencia D'Andrea joined the MDS team at UBC in the summer of 2021. Florencia's field of work has been ecotoxicology, specializing in Pesticide Risk Assessment. She studied at the University of Buenos Aires where she obtained her Bachelor's, and Doctorate in Biology. During her PhD, she worked with multiple databases and used a model to simulate the environmental fate of pesticides.
Florencia has a teaching degree at the University the Buenos Aires. She has been an instructor for The Carpentries and is an RStudio Certified Trainer for Tidyverse and Shiny. When Florencia is not teaching or working, she can be found listening to podcasts, hiking or doing yoga.
In the last 6 months, Florencia has gained experience developing Shiny apps.
Florencia's favourite data science topics are visualization, reproducibility and software development.
Learn more about Florencia here.
Mike Gelbart, Co-Director and Associate Professor of Teaching
Mike Gelbart joined UBC in 2015 and was part of the team that designed the MDS curriculum. He attended Princeton University where he obtained an undergraduate degree in physics and worked on research projects in biophysics. Mike then changed directions and received a PhD from the machine learning group at Harvard University. Mike is passionate about education. Recently he has co-founded the Vancouver Independent School for Science and Technology, a not-for-profit STEM high school. When Mike isn't teaching, you can find him at home with his kids or driving them somewhere new, riding his bike or playing video games.
In the last 6 months, Mike has learned that graph neural networks are becoming an increasingly popular and powerful tool for harnessing network data. He also learned how much temperature affects the quality of his sleep.
Mike's favourite data science topic is interpreting ML models.
Learn more about Mike here.
Gittu George, Postdoctoral Research and Teaching Fellow
Gittu George became a part of the MDS team in the spring of 2021. He graduated with a Bachelors of Computer Science from Mahatma Gandhi University and completed a Master of Science from the University of Houston in the same field but specializing in Big Data Analytics. He furthered his education in the field of Bioinformatics by obtaining a PhD from the University of Dundee. In his research he explored new ways of visualizing GWAS across multiple phenotypes by creating a 3D ‘landscape'.
Learn more about Gittu here.
Varada Kolhatkar, Assistant Professor of Teaching
Varada Kolhatkar joined the MDS program in October 2018 as a teaching and research postdoctoral fellow. She 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. 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. When Varada is not in the classroom you can find her biking, cooking or in Victoria.
In the last 6 months, Varada has learned that it's not easy to buy a home in Vancouver.
Varada’s favourite data science topic is unsupervised learning.
Learn more about Varada here.
Quan Nguyen, Postdoctoral Research and Teaching Fellow
Quan Nguyen 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 an Adjunct Lecturer 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. In his spare time, Quan enjoys playing soccer, basketball, guitar and piano.
In the last 6 months, Quan has learned how to use AWS Sagemaker.
Quan's favourite data science topics are time-series, network analysis and asessing biases and fairness in machine learning models.
Learn more about Quan here.
Joel Östblom, Postdoctoral Research and Teaching Fellow
Joel began his involvement with MDS as a TA while working on his PhD and joined as his current position, in the Summer of 2020. 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. Outside of the classroom, Joel can be found playing soccer, hockey, hiking or on the beach.
In the last 6 months, Joel has learned the beginnings of meditation.
Joel's favourite data science topics are visualization, ethics and clustering.
Learn more about Joel here.
Alexi Rodríguez-Arelis, Postdoctoral Research and Teaching Fellow
Alexi commenced his current role at MDS in January 2021. He 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. When Alexi is not working and teaching, he can be found swimming, trying out new restaurants, or exercising.
In the last 6 months, Alexi has learned about the many different ways that machine learning and statistics are connected.
Alexi's favourite data science topics are those involving statistics, specifically, inferential tools.
Learn more about Alexi here.
Arman Seyed-Ahmadi, Postdoctoral Research and Teaching Fellow
Arman Seyed-Ahmadi joined The MDS program in July 2021. He obtained his undergraduate degree from Urmia University of Technology in Mechanical Engineering and a Master's degree in Computational Fluid Dynamics from the University of Tabriz. Arman dove deeper into computational physics and continue his studies in the field by completing a doctorate from UBC. His research involves large-scale numerical simulations of particle-laden flows based on first principles, which he utilizes in developing physics-informed data-driven models. When Arman is not working, he is either reading, playing the violin or biking.
In the last 6 months, Arman has learned the importance of ethics in data science and some basics of AWS.
Arman's favourite data science topics include physics-informed machine learning and statistics.
Learn more about Arman here.
Tiffany Timbers, Co-Director and Assistant Professor of Teaching
Tiffany joined the founding team who developed the Master’s of Data Science program at UBC as a Postdoctoral Teaching and Learning Fellow. She received PhD in Neuroscience in 2012 from UBC, following which she held a Banting Postdoctoral Fellowship at Simon Fraser University where her research focused on cell biology & genomics. This postdoctoral research was data intensive and required the application of data science and statistical methodologies. In 2018, she joined the Statistics Department at UBC as an Assistant Professor of Teaching. She primarily teaches courses courses on introductory statistics and data science, computer programming, reproducible workflows and collaborative software development.
Tiffany's favourite data science topics are reproducibility and software development.
Learn more about Tiffany here.