We come from around the world and join the group at different times. Yet all of us are excited to work on systems and algorithms that are intensely challenging and breathtakingly beautiful.
Chen Ying, Ph.D. Candidate
Chen is currently a first-year Ph.D. student in the iQua research group at the Department of Electrical and Computer Engineering, University of Toronto. She received her B.Engr. degree from School of Computer Science, Wuhan University, Wuhan, China, 2017.
In her undergraduate years, Chen achieved excellent academic performance, ranking top 1% among four hundred students. In the summer of 2016, she took an internship at the University of Toronto, receiving an opportunity to build robots that can track and monitor signs of Alzheimer’s disease or dementia. That was when she fell in love with the city and the university, and made up her mind to continue her graduate studies here.
She enjoys travelling and photography in her leisure time.
Hao Lan, Ph.D. Candidate
Hao is a second-year Ph.D. student in the iQua research group at the Department of Electrical and Computer Engineering, University of Toronto. He received both of his B.E. and M.E. degrees from Xidian University, Xi'an, China, in 2015 and 2018 respectively.
Hao's research interests include datacenter networking, distributed computing, and software defined networking. Currently, he is working on optimizing the machine learning cluster using reinforcement learning.
Salma Emara, Ph.D. Candidate
Salma is a third-year Ph.D. Candidate. She joined iQua group in September 2018 as a MASc student and transferred to the Ph.D. program in September 2019. She received her BASc in Electronics and Communications Engineering from the American University in Cairo, Cairo, Egypt in June 2018.
Salma ranked top of her graduating class in June 2018. Out of her undergraduate thesis project, Salma published a paper in an IEEE conference. Salma's current research interests focus on finding practical solutions to networking problems using Deep Reinforcement Learning.
In her leisure time, Salma enjoys long walks in the City of Toronto.
Tianhang Zheng, Ph.D. Candidate
Tianhang is a first-year Ph.D. Student in the Department of Electrical and Computer Engineering at the University of Toronto. He received his B. Eng. degree and M. Sc. Degree from Peking University and University at Buffalo, respectively. In his Master's studies, he has published several top-conference and journal papers.
Currently, his research interests focus on statistical learning theory, trustworthy machine learning, and computer vision.
Sijia Chen, Ph.D. Candidate
Sijia is a first-year Ph.D. Student in the Department of Electrical and Computer Engineering at the University of Toronto. He received his B.Engr. degree and M. Sc. Degree in Telecommunication Engineering from Xidian University, China. During this period, he worked as an intern in SUTD (Singapore) and China Mobile while studying in NTU (Singapore). Due to his excellent academic performance while pursuing his Master's degree, he won a national scholarship, several first-class scholarships and the title of outstanding graduates.
His research interests focus on multi-modal learning, Bayesian learning, and computer vision. Currently, he is trying to solve problems in cross-modal data alignment and generation by exploiting Information Geometry.
Chenghao Hu, Ph.D. Candidate
Chenghao is a first-year Ph.D. student in the Department of Electrical and Computer Engineering at the University of Toronto, starting from September 2020. He received his B.Eng. degree from the South China University of Technology and M.Sc. from Tsinghua University. Chenghao's current research interests focus on distributed machine learning, and specifically, using deep reinforcement learning to improve the performance of distributed training and inference.
Chenghao enjoys playing guitar alone in his leisure time, and he has a regular plan to work out.
Yufei Kang, Ph.D. Candidate
Yufei is a first-year Ph.D. student in the Department of Electrical and Computer Engineering at the University of Toronto. She received her B.Engr. degree in Telecommunication Engineering in 2019 from Xidian University, China. In her undergraduate years, Yufei worked hard and performed well in her studies. In the summer of 2018, she worked as an intern at the Department of Cloud Computing and Big Data Research and Development at China Unicom Cloud Computing Ltd. Co. .
Currently, her research interests focus on applications of Deep Reinforcement Learning.
Ningxin Su, Ph.D. Candidate
Ningxin is a second-year Ph.D. student in the iQua group, and joined in September 2020. She received her M.E. Degree and B.E. Degree from The University of Sheffield and Beijing University of Posts and Telecommunications in 2020 and 2019, respectively.
Ningxin is not a "good" student at school. She loves dancing, singing and travelling. She thinks the museum is the best place to learn the history of a city, so one of her life goals is to visit as many museums as possible. Because of the pandemic of COVID-19, she changed her goal to visiting beautiful natural scenery. Her research interests focus on federated learning, specifically, asynchronous federated learning and federated unlearning.
Fei Wang, Ph.D. Student
Fei is a first-year Ph.D. student in the Department of Electrical and Computer Engineering at University of Toronto. In June 2020, She received her B.Eng. degree in Computer Science and Technology at Hongyi Honor College, Wuhan University, China. Prior to the graduate program enrolment, she spent two wonderful semesters at iQua participating in research studies as an intern. Fei's research interests lie at the intersections of deep reinforcement learning (DRL), networking, and communication.
Fei takes pleasure in listening to music and singing. She loves to plan her trips to new countries and cities in her leisure time, stepping out to explore and experience elsewhere.