Erika Braithwaite, PhD
Co-Founder | Statistical Consultant
I obtained my bachelors and master’s in psychology and then completed a PhD in Epidemiology at McGill University. My journey from the social sciences to the biomedical field has helped me gain a host of expertise related to study design, such as clinical trials, statistical modelling techniques drawn from causal inference and econometrics.
The common thread to all the fun things I get to do in my everyday? Data. When I’m not playing with numbers (which is rare), I’m googling pictures of dogs, doing gymnastics or playing with makeup (coming soon - makeup and data collide!)
Kathryn Morrison, PhD, AStat
Co-Founder | Statistical Consultant
My training is in biostatistics, epidemiology, and geographic information science. I finished my PhD in February 2017. I’m especially interested in predictive analytics, Bayesian inference, spatio-temporal modelling, and modern approaches to data visualisation.
As the famous* John Tukey said, the best thing about being a statistician is that you get to play in everyone’s backyard. I’ve worked with data from infectious diseases and environmental health to pharmacoepidemiology, social sciences and biotechnology.
I’m an avid R programmer and I've benefited greatly from the online, open-source R community. I strongly believe in reproducible research practices and try to make my work as accessible as possible. I also love knitting, yoga, podcasts, and dogs.
*Yes, there are famous statisticians.
Robert Platt, PhD
I am a Professor in the department of Pediatrics at McGill University and the department of Epidemiology, Biostatistics and Occupational Health, where I also serve as Director of Graduate Programs. As the inaugural holder of the Albert Boehringer 1st Chair in Pharmacoepidemiology, and as a Senior Scientist at the McGill University Health Centre Research Institute, my research focuses on biostatistics and statistical methods for pharmacoepidemiology and perinatal epidemiology. I am especially interested in causal inference in observational studies; particularly large pharmacoepidemiologic studies. I am also the Co-Principal Investigator and Leader of the Methods team for the Canadian Network for Observational Drug Effect Studies, as well as President-Elect of the Statistical Society of Canada. In my free time I enjoy skiing and spending time with my wife and kids and our corgi, Maggie.
Deepa Jahagirdar, Msc
I am nearing the completion of my PhD in Epidemiology at McGill University where I received training and experience in statistical methods, analysis of large quantities of spatiotemporal data and epidemiologic methods. In all my work, I love to distill complexity into an elegant story. This conviction drives my interest in data visualization, statistical methods, predictive modelling, econometric methods to identify causal effects, and everything from visual and descriptive exploration to machine learning algorithms to make sense of big data. It also drives my strong interest as a writer, in teaching and, ultimately, in finding the beauty in chaos.
Nancy Zhu, BSc
I am a Masters student in Epidemiology at McGill University. In summer 2017, I did an internship at Health Canada, where I developed several R shiny applications for interactive visualization of Canada Vigilance Adverse Reaction Database. The experience motivated me to explore more in big data, data visualization and data mining. With open-source communities, there are endless learning opportunities in this field and I am thrilled to be part of the journey!
Katie Dunkley-Hickin, Msc
In my Master’s in Epidemiology and while working at the Lady David Institute of the Jewish General Hospital I heavily employed econometric methods, in particular for investigating the causal impacts of policy introduction on population health outcomes. I have always worked with many disparate sources of data which I pride myself in cajoling into a coherent picture.
Having spent years in the noble (but slow as molasses) world of academia I have since caught the bug for consultancy, and am thrilled to be working and learning in this fast-paced and (my favourite part) collaborative environment.
Aside from the rush I get when I finally solve that knotty coding problem, I also love cats (dogs are great, but nothing beats a purring kitty), books, crochet, yoga and food. Especially chocolate. Okay, any dessert.
Asli Sari, MEng
I discovered my passion about data mining and machine learning during my undergraduate education in Computer Science and Biology. I’m currently pursuing my PhD degree in analysis of mine deposits and mine planning. I find it fascinating to utilize the power of computing to solve real world problems. At Precision Analytics, I work on creating dashboards using R Shiny and Plotly for data visualization. Aside from my evident coding enthusiasm, I love running, baking/cooking, reading and jazz.
Aman Verma, PhD
I have a PhD in Epidemiology from McGill University, and an undergraduate degree in Computer Science. I have experience in developing machine learning systems with large databases, particularly for scientific data in healthcare. I am comfortable learning any programming language, but I have recently become particularly interested in R. I get excited about applying fancy statistical and machine learning techniques to large datasets, particularly in healthcare.
I am currently involved in a number of projects, including measuring how following opioid prescription guidelines can decrease the risk of opioid overdose, modelling trajectories of chronic obstructive pulmonary disease, and how we can better prioritize ambulance calls using secondary healthcare data.