TrainCheck

Rafi is a Ph.D. candidate in Biomedical Engineering at the University of British Columbia. His current research employs machine learning to design cis-regulatory models, develop methods to interpret them and explore ways to enhance their performance, contributing to a quantitative comprehension of cis-regulatory logic. Connect with Rafi: https://www.linkedin.com/in/abdul-muntakim-rafi-205002154/. Find all episodes of the TrainCheck Podcast at traincheck.ai.

Adam Dziedzic is a Postdoctoral Fellow at the University of Toronto and Vector Institute, advised by Prof. Nicolas Papernot. His research focus is on secure and trustworthy machine learning, especially model stealing and defenses as well as on collaborative machine learning. Adam finished his Ph.D. at the University of Chicago, advised by Prof. Sanjay Krishnan, where he worked on input and model compression for adaptive and robust neural networks. He obtained his Bachelor's and Master's degrees from Warsaw University of Technology. Adam was also studying at the Technical University of Denmark and EPFL. He worked at CERN, Barclays Investment Bank, Microsoft Research, and Google. Connect with Adam: https://www.linkedin.com/in/adziedzic/. Find all episodes of the TrainCheck Podcast at traincheck.ai.

Dr. Ali Ayub is a Postdoctoral fellow at the University of Waterloo in the Department of Electrical and Computer Engineering. Prior to his postdoc, he earned his Ph.D. from The Pennsylvania State University in Electrical Engineering. He studies long-term autonomy for autonomous systems that continually learn personalized knowledge from people to assist them in their daily environments. He is a recipient of Google’s Diversity, Equity, and Inclusion (DEI) award and was also selected as a Pioneer at the ACM/IEEE International Conference on Human-Robot Interaction (HRI). Connect with Ali: https://www.linkedin.com/in/ali-ayub-170787a6/. Find all episodes of the TrainCheck Podcast at traincheck.ai.

Brian McCrindle is an Engineering Physicist turned Machine Learning Engineer deeply focused on creating interpretable and reliable models. These days, he spends his time at Parallel Domain, a synthetic data generation company for autonomy-based applications. Connect with Brian: https://www.linkedin.com/in/brianmccrindle/. Find all episodes of the TrainCheck Podcast at traincheck.ai.

Join Mohammad and Matt as they discuss the epistemology of trust.  Mohammad Ashkani earned a Combined BA in Math and Economics from the University of British Columbia and is a Blockchain Researcher at Aquanow. He utilizes his quantitative background to provide data science expertise for various blockchain projects. Mohammad is also fascinated by deep learning and loves to study the topic. Connect with Mohammad: https://www.linkedin.com/in/mohammad-ashkani. Find all episodes of the TrainCheck Podcast at traincheck.ai. Episode References: McLeod, Carolyn, "Trust", The Stanford Encyclopedia of Philosophy (Fall 2021 Edition), Edward N. Zalta (ed.), URL = <https://plato.stanford.edu/archives/fall2021/entries/trust/>.

Franziska is a Postdoctoral Fellow at the Vector Institute in Toronto. She obtained her PhD in Computer Science from Freie University Berlin. Her research focuses on trustworthy machine learning and privacy. She received a Fraunhofer grant for outstanding female early career researchers and the German Industrial Research Foundation prize. Connect with Franziska: https://www.linkedin.com/in/fraboeni/. Find all episodes of the TrainCheck Podcast at traincheck.ai.

Adrin has a PhD in computational biology, and he's a maintainer of scikit-learn, a statistical machine learning library, and fairlearn, a library to help folks improve the fairness of their AI systems. These days at Hugging Face, he also works on skops, focusing on certain security aspects in ML and their documentation. Connect with Adrin: https://www.linkedin.com/in/adrinjalali/. Find all episodes of the TrainCheck Podcast at traincheck.ai.

Matthew Speciale is a Masters of Management in Artificial Intelligence graduate from the Schulich School of Business at York University and is currently working as a Data Scientist at BMO. Connect with Matthew: https://www.linkedin.com/in/matthew-speciale/. Find all episodes of the TrainCheck Podcast at traincheck.ai.

Join Mohammad and Matt as they discuss the nature of trust.  Mohammad Ashkani earned a Combined BA in Math and Economics from the University of British Columbia and is a Blockchain Researcher at Aquanow. He utilizes his quantitative background to provide data science expertise for various blockchain projects. Mohammad is also fascinated by deep learning and loves to study the topic. Connect with Mohammad: https://www.linkedin.com/in/mohammad-ashkani. Find all episodes of the TrainCheck Podcast at traincheck.ai. Episode References: McLeod, Carolyn, "Trust", The Stanford Encyclopedia of Philosophy (Fall 2021 Edition), Edward N. Zalta (ed.), URL = <https://plato.stanford.edu/archives/fall2021/entries/trust/>.

Host, Matt Faltyn, introduces his trustworthy machine learning themed podcast, explaining his motivations surrounding evaluating AI systems.