We are very excited to announce this year’s U of T Department of Statistical Sciences Award winners, who will all be honoured at our Graduate Student Excellence Ceremony on June 17 starting at 4:00 pm.
Congratulations to this year’s winners! We had a very strong pool of nominees for all categories which is a testament to the amazing work our students are doing.
This year's winners stood out in a variety of ways – from excellence in academia, research and teaching to being leaders and ambassadors amongst their peers. We are very proud of you and lucky to have you as part of our community.
Without further ado, here are the winners.
Doctoral Award:
Jeffrey is a fourth-year PhD student. His fields of study include probability theory, statistical computing and theoretical statistics. Jeffrey is also the recipient of the prestigious Vanier Canada Graduate Scholarship. Additionally, he has contributed to several papers in leading machine learning journals, including “Advances in Neural Information Processing Systems”.
The Doctoral Award is given on the basis of excellence in research.
Andrews Academic Achievement Award:
Ruyi Pan
Ruyi is graduating from the Master of Science (MSc) program with a focus in statistics. Ruyi’s interests include both theoretical and applied statistics. Her undergraduate degree was completed in computer science. She hopes to continue her academic journey by persuing a PhD.
The Andrews Academic Achievement Award is given on the basis of outstanding academic work in the Master’s program.
Teaching Assistant Award:
Amar Dholakia
Amar Dholakia is currently an MSc Statistics candidate at U of T. His academic interests include machine learning and cluster analysis. He aspires to work as a data scientist or AI engineer. Amar is passionate about teaching, having served as a teaching assistant for the courses STA130, STA302 and STA305 this past year. He is currently co-leading a tutorial series on Python for Data Science. Outside of his academics and work, some of his hobbies include hiking, running, and biking.
The Teaching Assistant Award recognizes the student that has demonstrated quality and effective work as a teaching assistant.
Student Leadership Award:
Sabrina is currently a second-year PhD student with a focus in data science, probability theory and theoretical statistics. Outside of the classroom, Sabrina is president of the Statistical Sciences Graduate Student Union.
The Student Leadership Award recognizes a graduate student who has shown excellence in leadership.
Student Ambassador Award:
Nnenna is a second-year PhD student with a focus in data science, statistical computing, and theoretical statistics. Nnenna has served as a teaching assistant for multiple courses within the department. “As a TA, I especially enjoyed witnessing first-hand the excitement people have when they finally connect with a concept,” says Nnenna.
The Student Ambassador award is given to the student that has demonstrated excellence in data science outreach.
Doctoral Early Research Excellence Award:
Blair is a third-year PhD student with a focus in probability theory, theoretical statistics, and machine learning. He conducts research at the intersection of statistics and computer science. Blair is a researcher at the Vector Institute and is also a recipient of the Alexander Graham Bell Canada Graduate Scholarships-Doctoral Program (CGS D).
The Doctoral Early Research Excellence Award is given to a current PhD student for research excellence.
Data Science Award:
Sasha Nanda
Sasha is a student at the University of Toronto, pursuing a Master’s in Applied Computing (MScAC), Data Science Concentration. She graduated from Caltech in 2020 with a Bachelor’s Degree in Physics and a minor in Computer Science. Sasha worked at the intersection of quantum computing and machine learning research. She was a Feynman Quantum Resident at NASA Ames, and a Quantum AI Summer Resident at Google X. She is currently an intern at Deloitte’s AI consulting practice, where she builds machine learning models for forecasting. Sasha is particularly interested in the social implications of machine learning and AI. She hopes to pursue a career as a data science consultant while educating clients and furthering research in AI bias and ethics.