March 31, 2021 – The Vector Institute announced the 2021 candidates for its Postgraduate Affiliate Program. The new cohort of 30 talented researchers is a combination of new and returning members to Vector’s growing community. Established in 2018, the program promotes engagement and collaboration among researchers in the AI community who are in the early stages of their careers. Morteza Babaie and Shivam Kalra from Kimia Lab are among the new affiliates.
Made up of graduate students and postdoctoral fellows, members of the 2021 cohort represent universities and institutions across Ontario. Their research areas span core machine learning, neuroscience, health, computational linguistics, natural language processing, computational biology, computer vision, fairness, photonics for AI, systems, and how people relate to and understand AI.
They join the 16 Postgraduate Affiliates selected in 2020 who are completing the two-year term of their appointments as well as Vector’s vibrant and talented community of over 500 researchers.
Postgraduate Affiliates are selected through a competitive process; applicants are evaluated and selected based on the strength of their past research contributions and the alignment of their interests with Vector’s vision, mission, and research.
Shivam Kalra is a Ph.D. candidate at the Kimia Lab. He has completed his MSc at the University of Waterloo and BSc in Software Engineering at the University of Ontario Inst. of Technology. Shivam is an outstanding student and a researcher, and the holder of various national, provincial, and university-level scholarships and awards. He was selected as the finalist for the Governor’s General Gold Medal from the University of Waterloo for his excellent academic standings and research contributions. During the Ph.D., Shivam has developed a search engine for digital pathology archives called Yottixel. The search technology for pathology archives, such as Yottixel is a pioneering step for tapping the immense potential of AI that can revolutionize biomedical research for infectious diseases and cancer. For the rest of his Ph.D., Shivam is interested to research in federated learning for computational pathology. Federated learning is a privacy-preserving machine learning paradigm that enables multi-institutional collaborations on collaborative diagnostic and treatment projects without disclosing patient data. Putting privacy at the forefront of AI has the potential to transform the way AI research is conducted in biomedical fields.
Morteza Babaie is a postdoctoral fellow and the lab manager at the Kimia Lab since 2018. He joined Kimia Lab as a Ph.D. visiting scholar in 2016 and started working on medical image analysis. Since then, he has been the author or co-author of 30 research papers in computational medicine journals and conferences with near 500 google citations and an H-index of 12. His main research interests include image processing, machine learning, and AI.
“I am incredibly proud to work at Kimia Lab, especially when I noticed 2 out of 28 Vector-affiliated postgraduates in 2021 were selected from our Lab, which shows the direction, impact, and quality of Professor Tizhoosh’s leadership”, says Dr. Babaie.
Modified Vector news. Original text: Ian Gormely