Supervisors: Professor Andrea Tricco (University of Toronto), Dr. Carole Lunny (University of British Columbia), Professor Ebrahim Bagheri (Toronto Metropolitan University)I will be working on this research and will be a co-author on the publication.Introduction: Between 2000 and 2019, the number of systematic reviews (SRs) increased more than 20-fold. With this explosion, duplication of SRs on the same clinical, public health, or policy questions becomes problematic for decision makers who must choose between the different SRs.Objectives: We aim to develop an algorithm (called WISEST) to support decision makers in comparing and choosing between multiple SRs on the same question.Features: The items mapped from the AMSTAR 1, AMSTAR 2 and ROBIS tools to assess the quality of SRs will be used as the “quality” features. These manual tools have undergone face validity and usability testing.Work: (a) with support, clean a dataset of 100 SRs; (b) develop code to train, test and validate machine learning models (Random Forests and Neural Network) classification models such as Facebooks’ StarSpace and Fasttext. We will use a “supervised” learning model which learns by making predictions given examples of data, and the models are corrected to better predict the expected target outputs in the training dataset; (c) develop a shiny app to house the pilot (beta) WISEST tool (https://engineering- shiny.org/successful-shiny-app.html; and https://shiny.rstudio.com/tutorial/).

Teaching Assistant for STA130 - An Introduction to Statistical Reasoning and Data Science. Main programming language used: Python- Holding in-person weekly tutorials for a group of 25 students- Holding weekly online office hours- Exam invigilation - Grading on weekly tutorial assignments, weekly problem sets, capstone projects, and final exams

Working on the project "Learning cellular representations from highly multiplexed imaging data that are robust to segmentation errors".Supervisor: Dr. Kieran Campbell and his graduate student Jett Lee

Teaching Assistant for STA130 - An Introduction to Statistical Reasoning and Data Science. Main programming language used: R- Holding in-person weekly tutorials for a group of 25 students- Holding weekly online office hours- Exam invigilation - Grading on weekly tutorial assignments, weekly problem sets, capstone projects, and final exams

- Work-study Research Assistant for Professor Camille Hebert and Professor Irene Yi at Rotman School of Management- Work together cooperatively with undergraduate students, graduate students and professors to carry out and complete research (Teamwork).- Effectively use at least one new research method or statistical analysis software (Stata or R).- Judge a source to be valid or not in order to make relevant and accurate conclusions about the research at hand (Investigation and synthesis).- Collect relevant information from a variety of sources and organize the information so that it is comprehensible to others (Knowledge creation and innovation, Organization and Records Management).

Work as a behavioral science research assistant. The role is mainly to help with data, online scraping, running experiments, literature reviews. I also worked with Professor Ruttan to prepare for conference presentations about if corporations should take a stand on social issues with details and solutions focusing on “Why, When and How”. Supervisor: Prof. Rachel Ruttan

Participated in ROP (Research Opportunity Program) and was supervised by Professor Samantha-Jo Caetano. Responsibilities: Writing literature review reports; Performing statistical analysis and presenting results; Meeting with collaborators where collaborators provide insights into their research projects and responsible to provide verbal advice on how to approach statistical analysis; Hosting collaborator meetings (organizing meeting details).

The Intelligent Adaptive Interventions lab is directed by Joseph Jay Williams, an assistant professor in Computer Science at U of Toronto, with (courtesy) cross-appointments to accept PhD students in Psychology and Statistical sciences, and a faculty affiliate at the Vector Institute for Artificial Intelligence. Our research agenda is to transform components of any real-world user interfaces into adaptive systems that are perpetually enhancing and personalizing interventions to help people.(http://www.josephjaywilliams.com/)

- Mentorship Program with leading firms across business industries (Big Four, banks...)- Seek Sponsorships ($5000+) from CFA Society Toronto, RBC, P&G, CIBC- Partnerships with student organizations of top universities across North America (Princeton, McGill, UBC, ...)- Online Business Conference with 500+ attendees (with greeting letter from Prime Minister Justin Trudeau)

- Implemented calendar software that can better help students track their activities and goals with multiple design patterns: Factory, Dependency Injection, Iterator, Strategy, Observer, and Façade.- Responsible to the overall design with clean architecture; self-taught automatically sending email using Java.

- Curated Canada’s largest student-run business conference virtually with 57 executive speakers and 1117 attendees; received Letter of Honor from Justin Trudeau and the Toronto Mayor- Established and constantly communicated with various external parties such as universities, corporate sponsors, and student group partners- Secured $10 000 in sponsorship and partnered with 23 external student groups

Conducting research on senior departments is particularly meaningful with the rapid aging of populations in nowadays society. By conducting field research on 4 senior departments in Canada, analysing its building designs, costs, facilities, management and service system, then comparing the results with senior departments in China, taking advantage of each, I proposed how senior departments can improve in two countries.