Thank you to all our attendees, speakers, and sponsors who made this event possible!
Friday/10
Saturday/11
Sunday/12
MIXER
NIGHT
THE MAIN EVENT
WORKSHOPS
Join us for an evening of networking and discussion! Our founders Dr. Amira Aissiou and Dr. Shane Eaton will be opening the evening with a peek into the world of medicine and an intro to how AI can be used in the field. There will be food and plenty of opportunity to meet experts and learners in the fields of medicine and computing sciences.
This day features talks from experts in the field of artificial intelligence and healthcare, discussions, poster presentations, industry booths, and more! This is our main event, be sure not to miss it!
Let's talk shop! This day is geared towards learning some of the details of machine learning algorithms and how they can be used in medicine. Join us for interactive sessions and opportunities to collaborate with students and researchers from different fields.
1700h - 2000h
0830h - 1700h
0900h - 1600h
THE MATRIX HOTEL
10640 100 Ave NW
Edmonton AB T5J 3N8
Headquarters
10065 Jasper Ave #1101
Edmonton, AB T5J 3B1
Itinerary
Speakers
Dr. Patrick Pilarski
Rehabilitation medicine
BLINC lab | AMII
Dr. Patrick M. Pilarski is a Canada CIFAR Artificial Intelligence Chair, past Canada Research Chair in Machine Intelligence for Rehabilitation, and an Associate Professor in the Division of Physical Medicine and Rehabilitation, Department of Medicine, University of Alberta. In 2017, Dr. Pilarski co-founded DeepMind's Alberta office, where he continues as a team lead and Senior Staff Research Scientist. He is a Fellow and Vice Board Chair of the Alberta Machine Intelligence Institute (Amii), co-leads the Bionic Limbs for Improved Natural Control (BLINC) Laboratory, and is a principal investigator with the Reinforcement Learning and Artificial Intelligence Laboratory (RLAI) at the University of Alberta. As part of this research, Dr. Pilarski has developed and made prominent machine learning techniques for continual sensorimotor control and prediction learning on prosthetic devices. These include some of the first published approaches to ongoing user training of upper-limb prosthesis control systems via reinforcement learning, and he pioneered the use of general value functions in prediction learning to continually adapt myoelectric control interfaces in real time.
Key
note
Dr.
Nidhi
HeGde
ML Privacy and Fairness
AMII
Dr. Nidhi Hegde is an Associate Professor in the Department of Computing Science at the University of Alberta and a Fellow and Canada CIFAR AI Chair at Amii. Her current research is focused on fundamental problems in trustworthy and robust algorithms for Machine Learning. Before joining the University of Alberta, she spent many years in industry research labs. Most recently, she was a Research team lead at Borealis AI (a research institute at Royal Bank of Canada), where her team worked on privacy-preserving methods for machine learning models and other applied problems for RBC. Prior to that, she spent many years in research labs in Europe working on a variety of interesting and impactful problems. She was a researcher at Bell Labs, Nokia, in France from January 2015 to March 2018, where she led a new team focussed on Maths and Algorithms for Machine Learning in Networks and Systems, in the Maths and Algorithms group of Bell Labs. She also spent a few years at the Technicolor Paris Research Lab working on social network analysis, smart grids, privacy, and recommendations.
Dr.
Eytan
Wine
Pediatric Gastroenterology
Dr. Eytan Wine is a Professor of Pediatrics & Physiology, Clinician Scientist, & Pediatric Gastroenterologist at the University of Alberta. He completed a Peds GI at the Toronto Hospital for Sick Children and a PhD in Cellular Microbiology at the University of Toronto.
Dr. Wine’s clinical expertise is managing children with inflammatory bowel diseases (IBD) with specific interest in diet. This interest fits well with his laboratory research focus on involvement of intestinal bacteria and nutrition in development of intestinal inflammation, enabling translational bench-to-bedside research.
Dr. Wine is co-Chairs of the Canadian Children IBD Network (CIDsCaNN) and is on the Executive of the European Society for Pediatric Gastroenterology, Hepatology, and Nutrition (ESPGHAN) Porto IBD Group.
Dr.
Nazila
Ameli
Dentistry
Dr. Nazila Ameli is a third year PhD student at the Faculty of Medicine and Dentistry, University of Alberta. Her research interests include medical/dental imaging, deep learning and machine learning. After getting her DDS and MS degrees in Orthodontics at Shahid Beheshti University, Iran she secured a full-time position as an Assistant Professor and a member of the Research Council at Semnan Dental School. Due to her research exploits which were accompanied by various publications, she was nominated as the Vice-Dean of Research with an immediate promotion to the position of Associate Professor. As a Ph.D. student at the University of Alberta under the supervision of Dr. Hollis Lai, her research projects incorporate the use of analytics to inform and improve dental education practices. We are using this novel field of applying data analytics techniques in Dentistry to address patient care in order to better understand dental procedures in relation to patients; information and the diagnosis of oral diseases. The results obtained from these projects may significantly inform and improve the use of data-enabled innovations and analytics in Dentistry, health profession education, and the healthcare system as a whole.
Dr.
Peter
Campbell
Ophthalmology
Oregon Health & Science University
Dr. Peter Campbell is the Edwin and Josephine Knowles Professor of Ophthalmology at the Casey Eye Institute, Oregon Health & Science University. He has a clinical focus on adult and pediatric vitreoretinal surgery, and is a translational clinician scientist broadly focused on imaging in pediatric vitreoretinal disease. Specifically, he has been actively involved in two main research areas: the development of artificial intelligence (AI) algorithms in retinopathy of prematurity (ROP), and optical coherence tomography (OCT) for pediatric retina. Dr. Campbell is the PI for the Imaging and Informatics in ROP (i-ROP) research consortium, previously led by Michael Chiang (now director of the National Eye Institute). He is also been a close collaborator with the Center for Ophthalmic Optics & Lasers [COOL Lab] headed by David Huang, MD at OHSU. He was recently a member of the 3rd International Classification of Retinopathy of Prematurity Committee, and is the Chair of the American Academy of Ophthalmology Committee on Artificial Intelligence.
Dr.
Yan
Yuan
Biostatistics & Public Health
University of Alberta
Dr. Yan Yuan is interested in developing and applying statistical learning methods in cancer related population health and biomedical research using data from observational studies. Methodologically, her research interests are statistical prediction and classification, and developing appropriate metrics for quantifying the prediction performance. Two ongoing applied health research projects are: 1) personalized risk prediction of late effects in childhood and adolescent & young adult cancer survivors based on treatment and genetic data; 2) brain tumour surveillance in Canada and developing artificial intelligence tools for improving cancer surveillance.
Dr.
JihYun
Yun
Medical Physics
Cross Cancer Institute and University of Alberta
Dr. Jihyun Yun is a medical physicist at the Cross Cancer Institute (CCI) and Assistant Professor at the University of Alberta. His clinical work at the CCI involves the management of the Linear Accelerator, Gamma Knife Icon, Linac-based SRS, and more. His area of research involves real-time tumor tracking using Linac-MR - he was responsible for the world’s first demonstration of real-time tumor-tracked beam delivery using linac-MR. He also incorporated machine learning and deep neural networks into tumor auto-segmentation algorithms in MR images and tumor motion prediction algorithms. In addition to this, Dr. Yun teaches several university-level oncology courses that incorporate the principles of medical physics in patient care.
Dr.
Phedias Diamandis
Neuropathology
Princess Margaret Cancer Centre
Dr. Phedias Diamandis is a Neuropathologist at The University Health Network and a Scientist at the Princess Margaret Cancer Centre in Toronto. His research focuses on using chemical biology, deep learning and mass spectrometry-based proteomics to resolve phenotypic heterogeneity in different brain and glioblastoma niches.
He is an Associate Professor at the University of Toronto in the Departments of Laboratory Medicine and Pathobiology.
Dr. Phedias Diamandis completed the combined MD/PhD Program at the University of Toronto under the mentorship of Drs. Michael Tyers and Peter Dirks. He pursued post-graduate training also at the University of Toronto in Neuropathology.
Dr.
Gillian Lemermeyer
Nursing
University of Alberta
Dr. Gillian Lemermeyer, PhD, RN is an Assistant Professor in the Faculty of Nursing at the
University of Alberta, Canada. Dr. Lemermeyer’s research explores the embodied ethics of healthcare practices, employing a phenomenological method to investigate the nurse’s touch in the neonatal intensive care unit. Other research projects have explored the effects of AI and other digital technologies in K-12 education and the experience of families in the NICU, and during the process of considering organ donation. Her nursing background is in neonatal intensive care, family bereavement, and professional regulation. Her teaching practice is in healthcare ethics with undergraduate and graduate students.
The questions she explores are situated in the relational encounters between nurses and other healthcare practitioners with the people in their care. Dr. Lemermeyer focuses on themes of relational ethics, the nurse’s touch, and the ethics of artificial intelligence in healthcare.
Dr.
Robert Paproski
Dr. Robert Paproski is the co-founder and Chief Technology Officer of Nanostics which develops medical devices using machine learning models. Since earning his B.Sc. in Pharmacology and Ph.D. in Oncology at the University of Alberta, Dr. Paproski has developed expertise in laboratory assay development and computational analysis. Within Nanostics, Dr. Paproski oversees machine learning and software development as well as regulatory compliance for software products.
Medical Devices
Nanostics
Dr.
Michael
van Manen
Dr. Michael van Manen, MD, PhD, FRCPC(Peds,NICU,CIP) Endowed Chair in Health Ethics is the Director of the John Dossetor Health Ethics Centre and an Associate Professor in the Department of Pediatrics at the University of Alberta. Dr. van Manen also has a clinical practice as a physician in neonatal-perinatal medicine with the Stollery Children’s Hospital. His research his primarily concerned with relational ethics, situated within the tradition of phenomenology.
Pediatrics & Medical Ethics
Stollery Children's Hospital
Dr.
Bo
Wang
Dr. Bo Wang is a tenure-track Assistant Professor in the departments of Computer Science and Laboratory Medicine & Pathobiology at the University of Toronto. He is the inaugural Temerty Professor in AI Research and Education in Medicine. Dr. Wang leads the AI team at Peter Munk Cardiac Centre at the University Health Network. He also holds a CIFAR AI Chair at Vector Institute. Dr. Wang obtained his PhD from the Department of Computer Science at Stanford University in 2017. Dr. Wang has published multiple first-authored papers in world-renowned journals such as Nature Methods and the Lancet Digital Health. Dr. Wang’s primary research areas are machine learning, computational biology, and computer vision with applications in healthcare.
Computing Sciences and Biopathology
University of Toronto
Dr.
André
Dos Santos
Dr. André dos Santos is a Machine Learning Educator at the Alberta Machine Intelligence Institute (Amii). With his experience and expertise in responsible AI, causality, and deep learning, he is a sought-after speaker and lecturer. His passion for educating people on Ethics in AI and mitigating risks with AI applications led him to develop and deliver workshops to businesses.
Prior to joining Amii, André was a Postdoctoral Fellow at the University of Alberta, where he researched synthetic data generation in partneship with Scotiabank. He also served as a Lecturer in the Computer Science department at the University of Regina.
André holds a Ph.D. and M.Sc. in Computer Science from the University of Regina and an Industrial Engineering degree from Brazil. When he's not busy educating and researching, he enjoys cartooning, playing ukulele, boudlering, and practicing Japanese jiu-jitsu.
Machine Learning Educator
Alberta Machine Intelligence Institute (Amii)
Tim
Tran
Tim Tran is a software Engineer at DrugBank, specializing in Machine Learning pipelines. His work involves designing processes for all aspects of the ML lifecycle, as well as augmenting and supporting Drugbank's existing ML systems. During Tim's day-to-day, he writes code, plans software projects and collaborates with a fantastic team of product managers, engineers, data scientists and pharmacologists. Tim Tran has a degree in Software Engineering from the UofA.
Software Engineer