What we're about

This meetup is about sharing knowledge & learning about machine learning, data engineering, data analytics, parallel algorithms, and distributed systems. It provides an opportunity for data engineers, data scientists, software engineers, statisticians, and innovators to get together and make connections. Our events will vary from introductory to advanced, but are always intended to provide new ideas, concepts and tools to help you solve your hardest problems. We also will aim in always getting in some practical hands-on sessions.

Upcoming events (1)

Transitioning from academia to industry & Key influencers in social networks

We would like to welcome you all to the April Meetup of the Waterloo Data Science and Data Engineering meetup on April 1st. For this we'll have one talk and one panel discussion. Talk: Identifying Key Influencers in Large Social Networks The problem of identifying influencers in large social networks has attracted lot of research interest in the past decade. This NP-Hard problem has been tackled with many heuristic solutions but still there is an opportunity to improve existing solutions. Faraz Zaidi (https://www.linkedin.com/in/farazazaidi/) is an Advisor in the Health Analytics team at the Region of Peel. His current research interests include developing data-driven solutions for the health department at the regional municipality where he uses advanced analytics, complex algorithms and visualization to develop innovative solutions. Before this, he has worked as a Data Scientist, a Research Scientist and an Academician in USA, Switzerland, France and Pakistan. He has a PhD in Data Mining and Visual Analytics, a Masters in Complexity and Algorithms and a Masters in Software Engineering. Panel: Transitioning from Academia to Industry A lot of Data Engineers and Data Scientists come from Masters and PhD programs. (https://medium.com/indeed-engineering/where-do-data-scientists-come-from-fc526023ace). In this session we will discuss the transition from Academia to Industry with Mayya Sharipova (https://www.linkedin.com/in/mayya-sharipova-a40a0256/), David Rossouw (https://www.linkedin.com/in/david-rossouw-aa911b9b/) and Slava Kohut (https://www.linkedin.com/in/slavakohut/). In the panel we will discuss their experiences and both the advantages and disadvantage from both industry and academia who all made this transition successfully. Mayya has a PhD in Artificial Intelligence in Education, Intelligent Tutoring Systems from the University of Saskatchewan and works now as a Java Search Engineer at Elastic. David has a PhD in Material Science and Engineering from McMaster University and works as a Data Scientist at Dialpad. Slava has PhD in Computation Chemistry from Western University and Scientific Computing and is now a Data Scientist at Validus Research Inc.

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