Adam Trischler
Principal Research Manager
About
I lead the Machine Comprehension team at Microsoft Research, Montreal. I received my PhD from the University of Toronto Institute for Aerospace Studies, working in the Space Robotics Group under Gabriele D’Eleuterio. My doctoral thesis, A Computational Model for Episodic Memory Inspired by the Brain, combined continuous-time recurrent neural networks with deep belief networks to model compression, storage, and retrieval of sensory experience. I made the jump to natural language processing in 2015, when I joined the Canadian startup Maluuba. I was the first member of its nascent deep learning research team.
I currently study language as an instrument of intelligent agents for the representation and communication of information. I design neural systems for NLP using methods from deep and reinforcement learning, information theory, and computational linguistics. Much of my work up to now has focused on question-answering, but I’m now interested in metalearning, lifelong learning, and…
Featured content
Building Literate Machines with Dr. Adam Trischler
Episode 16, March 21, 2018 - Learning to read, think and communicate effectively is part of the curriculum for every young student. But Dr. Adam Trischler, Research Manager and leader of the Machine Comprehension team at Microsoft Research Montreal, would like to make it part of the curriculum for your computer as well. And he’s working on that, using methods from machine learning, deep neural networks, and other branches of AI to close the communication gap between humans and computers. Today, Dr. Trischler talks about his dream of making literate machines, his efforts to design meta-learning algorithms that can actually learn to learn, the importance of what he calls “few-shot learning” in that meta-learning process, and how, through a process of one-to-many mapping in machine learning, our computers not may not only be answering our questions, but asking them as well.