December 13, 2019

April 17, 2015 at The Fields Institute (Room 230)

Statistics Graduate Student Research Day

Statistics Graduate Student Union (SGSU), University of Toronto
Department of Statistical Sciences, University of Toronto

Organizing Committee (University of Toronto) :
Co-chair: Tadeu Ferreira (Ted), Ph.D. Candidate & President SGSU
Co-Chair: Reihaneh Entezari, Ph.D. Candidate & Vice-President SGSU

James Stafford
Nancy Reid
Annette Courtemanche
Christine Bulguryemez




Statistics Graduate Student Research Day is an annual student initiative supported by the Department of Statistical Sciences, University of Toronto and Statistics Graduate Student Union. The purpose of Research Day is to provide graduate students with exposure to current methods, leading experts, and important topical themes in the field of statistics.

Research Day further aims to provide students with an academic forum in which they can present, discuss and receive feedback on their research from their peers, faculty, and invited guests. Student presentations are given by graduate students in Statistics, Biostatistics, Computer Science and other related departments at the University of Toronto. Graduate students from all institutions that sponsor the Fields Institute are welcome to attend this event.


Theme: Machine Learning for Big Data

It is widely known that Machine Learning is a multidisciplinary field which comprises the development of algorithms that can learn from data. Machine Learning and data are inseparably united. Thus, continuous updates and improvements of Machine Learning procedures is needed in order to adapt to a relentless and massive generation of data.

In this context, it is imperative to approach the theme “Machine Learning for Big Data” where the increased processing power of ordinary computers allowed researches and professionals of different fields to combine computationally intensive methods - usually present in Machine Learning - with large amounts of data. These methodologies have been successfully implemented in leading world companies like Google, AT&T Bell Labs, Microsoft, Netflix, Facebook, Amazon, and many others.

“We are drowning in information but starved for knowledge” John Naisbitt, Megatrends (1982)


Keynote Speakers

Three renowned researchers working in companies that are at the forefront of innovation in Machine Learning for Big Data, have honoured the Department of Statistical Sciences by accepting the invitation as keynote speakers for our Research Day:

Dr. Robert Bell (Researcher Google)
Robert Bell is scheduled to join Google on April 6, 2015. Until recently, he was a member of the Statistics Research Department at AT&T Research since 1998. He previously worked at RAND doing public policy analysis. His current research interests include machine learning methods, analysis of data from complex samples, and record linkage methods. He was a member of the team that won the Netflix Prize competition. He has served on the Fellows Committee of the American Statistical Association, the board of the National Institute of Statistical Sciences, the Committee on National Statistics, the advisory committee of the Division of Behavioral and Social Sciences and Education, and several previous National Research Council advisory committees studying statistical issues from conduct of the decennial census to airline safety.

Dr. Alekh Agarwal (Researcher Microsoft)
Dr. Alekh Agarwal is currently a researcher in the New York lab of Microsoft Research. He spent two years as a post-doctoral researcher at the same institution, where his research was primarily focused on Machine Learning, Statistics and Convex Optimization. Prior to that he obtained his Ph.D. in Computer Science from UC Berkeley, where he worked with Peter Bartlett and Martin Wainwright. He received the MSR Ph.D. Fellowship in 2009 and Google Ph.D. Fellowship in 2011.
Dr. Agarwal’s interest is in Machine Learning, Statistics and Optimization focusing on problems which arise while applying Machine Learning techniques to massive datasets. Part of his research aims to understand the tradeoffs between learning and computation, as well as designing efficient learning algorithms that can learn under a given computational budget. More recently he has been looking at approaches for learning feature representations from data in a theoretically principled and practically efficient manner.

Dr. Kevin Patrick Murphy (Researcher Google)
Dr. Kevin Murphy is a research scientist at Google in Mountain View, California where he works on AI, Machine Learning, Computer Vision and NLP. Before joining Google in 2011, he was an Associate Professor of Computer Science and Statistics at the University of British Columbia in Vancouver, Canada. Before starting at UBC in 2004, he was a post-doctoral at MIT. Kevin received his BA from University Cambridge, his MEng from University Pennsylvania, and his Ph.D. from UC Berkeley. He has published over 80 papers in refereed conferences and journals as well as an 1100-page textbook called "Machine Learning: a Probabilistic Perspective" (MIT Press, 2012), which was awarded the 2013 DeGroot Prize for best book in the field of Statistical Science. Kevin is also the (co) Editor-in-Chief of JMLR (the Journal of Machine Learning Research).

Please use our online registration (link at top) for the opportunity to submit questions to our panel of keynote speakers.



8:30 a.m. Coffee
9:00 a.m. Welcome Address
Dr. James Stafford (Professor & Statistics Chair)
Tadeu Ferreira (Ph.D. Candidate & Co-chair of Research Day)
Reihaneh Entezari (Ph.D. Candidate & Co-chair of Research Day)
9:15 a.m Keynote Speaker:
Dr. Alekh Agarwal (Researcher Microsoft)
Efficient and Optimal Interactive Learning
10:15 a.m. Student Speaker:
Alexander Shestopaloff (University of Toronto)
Topic TBA
10:35 a.m Coffee & refreshments break
11:00 a.m. Keynote Speaker:
Dr. Kevin Patrick Murphy (Researcher Google)
Knowledge extraction from text, images and video
12:00 p.m. Student Speaker:
Patrick Halina (University of Toronto)
Data Science for Profit: Career advice for fresh grads going to industry
12:20 p.m. Lunch (provided) at Fields
1:20 p.m. Student Speaker:
Jimmy Ba (University of Toronto)
Graphical models and reinforcement learning on visual attention

1:40 p.m. Keynote Speaker:
Dr. Robert Bell (Researcher Google)
Lessons from the $1,000,000 Netflix Prize
2:40 p.m. Coffee & refreshments break
3:00 p.m. Panel Discussion:
Drs. Robert Bell, Alekh Agarwal, Kevin Murphy, Ruslan Salakhutdinov, Daniel Roy
4:00 p.m. Closing Remarks
Dr. James Stafford (Professor & Statistics Chair)
Reihaneh Entezari (Ph.D. Candidate & Co-chair of Research Day)
Tadeu Ferreira (Ph.D. Candidate & Co-chair of Research Day)


The Research Day was first organized in 2009 and was a very successful event. In particular, the students benefited greatly from the exchange of ideas and direct interaction with top researchers in the field. We have held the Research Day at the Fields Institute for the past few years and hope to continue to do so in the coming years.

In 2011, the theme for Research Day was Computationally Intensive Methods. This theme was selected to reflect the effect technological innovations had in the amount and data available for interpretation. The theme for 2012 was Models for Dependent Data, emphasizing how contemporary models and methods are better able to capture dependence in data. In 2013, Statistics in Networks was the topic for the Research Day

Information about the format of our last Research Day can be found at here.




Full Name
Abou Chacra, David University of Waterloo
Aflaki, Saba University of Waterloo
Agarwal, Alekh Microsoft
Agrawal, Ajay Rotman School of Management, University of Toronto
Alkinani, Monagi Western University
Amer, Ihab AMD
Amza, Cristiana University of Toronto
Ao, Shuang Western Univerity
Ataei, Masoud York University
Atluri, Sravya University of Toronto
Azadbakhsh, Mahdis York University
Ba, Jimmy University of Toronto
Bajracharya, Sagun Kobo
Balachandra Bhat, Aparna Queen's University
Balazia, Michal University of Toronto
Bashiri, Ali University of Toronto
Bell, Robert Google
Bi, Hongbo University of Waterloo
Bulguryemez, Christine University of Toronto
Champati, Jaya University of Toronto
Chan, Matthew University of Waterloo
Chen, Jun McMaster University
Chen, Webber University of Waterloo
Cheong, Hyunmin Autodesk Research
Cheung, Donny Google Canada
Choi, Jongsok University of Toronto
Choo, Heeyoung University of Toronto
Chrapka, Phil McMaster University
Courtemanche, Annette University of Toronto
Damiano, Claudia University of Toronto
Davoudi, Heidar York University
Deng, Wei Qxi University of Toronto
Dufort, Paul University of Toronto
Duszak, Kris University of Toronto
Eichel, Justin Miovision Technologies
Elbagoury, Ahmed University of Waterloo
El-Sakka, Mahmoud Western Univerity
Elshamli, Ahmed University of Guelph
Entezari, Reihaneh University of Toronto
Erez, Jonathan University of Toronto
Fang, Yihao McMaster University
Farahani, Mohammadreza University of Waterloo
Farahany, David University of Toronto
Ferreira, Tadeu University of Toronto
Fok, Ricky York University
Fortin, Alex-Antoine University of Toronto
Fu, Hui University of Waterloo
Fukuda, Eric University of Toronto
Ghasemi, Ehsan University of Toronto
Gibbs, Alison University of Toronto
Gold, Nathan York University
Gweon, Hyukjun University of Waterloo
Haider, Masoom Sunnybrook Hospital / University of Toronto
Halina, Patrick University of Toronto
Hasler, Caren  
Hassan, Safwat Queen's University
Hidru, Daniel University of Toronto
Hoehn, Logan University of Waterloo
Honarvar, Ali University of Toronto
Huang, Xuancheng University of Toronto
Ibrahim, Rania University of Waterloo
Im, Jiwoong University of Guelph
Javed, Tariq Ryerson University
Jeya, Logan University of Waterloo
Ji, Zheng University of Waterloo
Jung, Yaelan University of Toronto
Khalifa, Shadi Queen's University
Khan, Salman University of Waterloo
Khazaei, Taraneh University of Western Ontario
Khosravani-Tehrani, Nazanin Kobo
Kim, Thomas Accenture
Kiselev, Igor University of Waterloo
Korolev, Sergei University of Toronto
Koudstaal, Mark University of Toronto
Krass, Dmitry University of Toronto
Kraus, Oren University of Toronto
Krishnan, Krishanth McMaster University
Le Bek, Peter  
Lee, Timothy University of Toronto
Leung, Brian  
Li, Fan University of Waterloo
Li, Jinfei York University
Li, Mufan University of Toronto
Li, Wei Autodesk Research
Li, Xiang University of Western Ontario
Li, Xuan York University
Li, Yuke University of Toronto
Li, Zhi University of Toronto
Lian, Lanny University of Toronto
Liang, Jackson University of Toronto
Liang, Jiaxi University of Waterloo
Lin, Wei University of Toronto
Lin, Wu University of Waterloo
Lisicki, Michal University of Guelph
Litus, Yaroslav Google Canada
Liu, Chang Western University
Liu, Da University of Toronto
Liu, Jiange University of Waterloo
Liu, Renfeng Western University
Lo, Charles University of Toronto
Luo, Yan Western University
Malhotra, Aarti University of Waterloo
Maqbool, Sana University of Toronto Mississauga
Mascher, Philipp Queen's University
Mawyin, Tomas UTIAS
Milne, Tristan Queen's University
Murphy, Kevin Patrick Google
Myrden, Andrew  
Nabavi, Morteza University of Waterloo
Narayan, Apurva University of Waterloo
Neal, Radford University of Toronto
Neish, Drew University Of Guelph
Neto, David Google Canada
Nikou, Mohammad University of Waterloo
Parmar, Noopur Creative Destruction Lab
Paryab, Neda University of Waterloo
Pat, Ankit University of Waterloo
Ponnambalam, Kumaraswamy University of Waterloo
Poulos, Zissis University of Toronto
Qin, Zhen Toronto University
Raghav, Prashant University of Waterloo
Rao, Chitong University of Toronto
Rasooli, Marzieh Volvox Inc
Redding, Nigel Carleton University
Reid, Nancy University of Toronto
Ren, Mengye University of Toronto
Rezazadeh Sereshkeh, Alborz University of Toronto
Romdhani, Sihem University of Waterloo
Roy, Daniel University of Toronto
Sadat Rezai, Seyed Omid University of Waterloo
Salakhutdinov, Ruslan University of Toronto
Salem, Mahmoud University of Waterloo
Sariri, Amir University of Toronto
Sarrafzadeh, Bahareh University of Waterloo
Sawh, Deitra University of Waterloo
Scaranelo, Anabel University of Toronto - Princess Margaret Cancer Centre
Shahbazi, Nima York University
Shen, Mi Proteocyte Diagnostics Inc.
Shen, Qinghua University of Waterloo
Sheng, Ann University of Toronto
Shestopaloff, Alexander University of Toronto
Shi, Limeng Wilfrid Laurier University
Shum, Marco University of Western Ontario
Sines, Gabor AMD
Smart, Michael University of Waterloo
Stafford, James University of Toronto
Sun, Xiaoying York University
Sun, Yinming University of Toronto
Sundaravarathan, Kiran Queen's University
Sussman, Marshall University Health Network
Taback, Nathan University of Toronto
Tai, Justin University of Toronto
Tarafdar, Maif University of Toronto
Taylor, Graham University of Guelph
Trischler, Adam University of Toronto
Tyrrell, Pascal University of Toronto
Vendrov, Ivan University of Toronto
Veneris, Andreas University of Toronto
Veres, Matthew University of Guelph
Wang, Caifeng University of Waterloo
Wang, Lei University of Waterloo
Wang, Xiaohui RNA Diagnostics
Wang, Yi Xin University of Toronto
Wei, Dongwei York University
Wu, Yingzhou University of Toronto
Xu, Han University of Waterloo
Yancheva, Maria University of Toronto
Yang, Jinyoung University of Toronto
Yang, Qianmin McMaster University
Yasmeen, Farzana York University
Yu, Guang Wei University of Toronto
Yuan, Zhonglin University of Toronto
Zemel, Richard University of Toronto
Zhang, Shixiao York University
Zhou, Weijian University of Toronto



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