Konstantinos N. Plataniotis, Bell Canada Chair in Multimedia, is a Professor with the ECE Department at the University of Toronto. His current research interests are: machine learning, adaptive systems & pattern recognition, image & signal processing, communications systems, and big data analytics. He is a registered professional engineer in Ontario, Fellow of the IEEE and Fellow of the Engineering Institute of Canada. Dr. Plataniotis was the IEEE Signal Processing Society inaugural Vice President for Membership (2014-2016) and the General Co-Chair for the IEEE GlobalSIP 2017 (November 2017, Montreal, Q.C.). He co-chairs the 2018 IEEE International Conference on Image Processing (ICIP 2018), October 7-10, 2018, Athens Greece, and the 2021 IEEE International Conference in Acoustics, Speech and Signal Processing (ICASSP 2021), Toronto, ON, Canada.
Dr. Corwyn Rowsell is a Staff Pathologist at St. Michael’s Hospital and Associate Professor in the Department of Laboratory Medicine at University of Toronto.
He is one of three members of the GI pathology group at St. Michael’s Hospital responsible for therapeutic endoscopy cases. Previously, he spent 8 years as part of the GI and hepatobiliary pathology team at Sunnybrook Health Sciences Centre, where he helped develop national consensus guidelines for management of GI neuroendocrine tumours. In addition to gastrointestinal pathology, Dr. Rowsell has had a long-standing interest in quality assurance in pathology, having previously served on the Advisory committee for the Quality Management Program (CCO/CPSO) and as Chair of the Pathology Scientific Committee at the Institute for Quality Management in Healthcare.
Savvas became Chief Technology Officer for Huron in 2010. He joined the company (originally known as Biomedical Photometrics Inc.) in 1998 as project leader. He led the development and manufacturing of micro array readers, tissue imaging systems, and a MacroScope/Microscope combination system for general confocal imaging applications. He has been involved in the development of imaging systems for more than 20 years and is the author of several patents and more than 30 publications on confocal microscopy imaging techniques and applications.
Mahdi S. Hosseini received the B.Sc. ``cum laude'', the M.Sc., M.A.Sc., and Ph.D. degrees in electrical engineering from University of Tabriz, University of Tehran, University of Waterloo, and University of Toronto in 2004, 2007, 2010, and 2016, respectively. He is a post-doctoral fellow at the University of Toronto (UofT) and research scientist at Huron Digital Pathology in St. Jacobs, Ontario, Canada. His research is primarily focused on understanding and developing robust computational imaging and machine learning techniques for analyzing images from medical imaging platforms in digital pathology both from applied and theoretical perspectives. He leads a research team of UofT students for R&D development of the image analysis pipelines required for digital and computational pathology. Dr. Hosseini has served as a reviewer for the IEEE transaction on Image Processing, the IEEE transaction on Signal Processing and IEEE Transactions on Circuits and Systems for Video Technology.
Lyndon Chan received his B.A.Sc. degree with distinction in electrical engineering from the University of Toronto in 2017 and worked in image/video processing at Qualcomm in 2015-16. Currently, he is a graduate research assistant at the Multimedia Lab at the University of Toronto and studying for his M.A.Sc. degree in electrical engineering under the co-supervision of Professors Konstantinos Plataniotis and Parham Aarabi. His research focus is on the weakly-supervised semantic segmentation of histological tissue type from digital pathology images. He has also been involved in formulating the histological tissue type framework of the ADP database, revising the patch annotations, and analyzing the annotation quality through deep learning.
Alfred Chan is Alfred Chen and he is a M.A.Sc candidate in the Communications Group of Electrical Engineering at the University of Toronto. he is under the supervision of Prof. K. N. (Kostas) Plataniotis. Alfred received a B.A.Sc in Applied Mathematics and Engineering from Queen's University in 2018. His undergraduate focus was on applied mathematics such as information theory, stochastic processes, control theory, real analysis, and complex analysis. Alfred's research is focused on applications using the Vandermonde matrix. Specifically, inverse problems such as super-resolution and polynomial interpolation.
Joshua is an Electrical and Computer Engineering student (ECE2T1), he is a Rogers Scholar, the recipient of the Governor General Academic Medal and a cofounder of a starter gaming company called BrokenTableStudios. The company develops games via Unity and Blender which allows for realistic graphics and innovative game concepts. Joshua is responsible for a number of contribution on the ATLAS Project such as the development of this website's graphics and backend user interface, WSI patch extractor application based on patheologist's annotation and creation of the GUI application that enables efficient WSI label revision.
Yichen is a Computer Engineering student (ECE1T9) at the University of Toronto with focuses in the areas of Software Engineering, Controls and Communications. She has broad interests in Artificial Intelligence, Machine Learning, and Distributed Computing. Her role in the Summer 2019 project is to develop a tool to detect tissue abnormalities within whole slide images using a custom pre-trained Convolutional Neural Network model as a processing engine.
Guanchen is a fourth-year computer science undergraduate student at the University of Toronto, focusing on Computer Vision and Machine Learning in Biomedical applications. He is going to do his Master degree in Computer Science at Cornell University. His main task is to implement each unique feature from different tissue types, shapes, and disease, and represent them in a standard form for encoding. The goal is to translate the medical definitions of such shape deteriorations to an engineering firm to identify
Danial Hasan is a 4th year student in the Engineering Science program, majoring in Machine Intelligence, at the University of Toronto. As an undergraduate summer student, he is working towards the application of Machine Learning and Computer Vision to classify organs from histology slides. Danial hopes to attend graduate school, with primary research interests in the application of Machine Learning towards biology and medicine. In his spare time, Danial works as a freelance data scientist and tutors high school and undergraduate students. Additionally, he enjoys reading, video games, and playing soccer and basketball.
Weimin (Cheryl) is an undergraduate student majoring in Machine Intelligence in the division of Engineering Science at the University of Toronto. She has an interest in machine learning and image processing. Her main research task is to study and improve the performance of CNN models, by applying techniques such as neural architecture search and different types of data augmentation. The goal is to develop efficient CNN classifier models that assist in the semantic segmentation of histological tissue types in the digital pathology workflow.
Katherine Huang graduated in Computer Engineering from University of Toronto in 2019. She enjoys the principles by Bayes, Gauss, and Fourier and is eager to apply them to problems. She was an intern at the Multimedia Lab during summer 2019 where she developed a slide selection pipeline for populating the Atlas database. In her spare time, Katherine delights herself in the study of history and languages. Additionally, Katherine is a proud alum of Iron Dragons, the world-champion dragon boat club from UofT Engineering.
Jessica received her B.A.Sc. degree from Edward S. Rogers Sr. Department of Electrical & Computer Engineering, University of Toronto. She continues to focuse on pathological images labeling and data collection and management.
Michael Tang completed his BASc in Electrical Engineering, with a minor in Biomedical Engineering from the University of Toronto in June 2018. As a research assistant, Michael aided in the scanning and organization workflow for the whole slide scans of the physical tissue slides, as well as initial development of the tagging software and prelimary identification of tissue structures. Michael is currently a 3rd year student at the University of Toronto studying for a BA in Sociology, with plans to further pursue the field of Social Data Science.
Gabriel is a fourth year Computer Engineering student at the University of Toronto. His work on the Atlas Database includes the preliminary data collection, creating the tissue type and metadata labelling and whole slide imaging workflow. He also helped in the research and creation of the Hierarchical Taxonomy of Histological Tissues.