Christopher Beckham
Machine Learning Researcher at Alpaca
Montreal, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolChristopher Beckham is a machine learning researcher and PhD candidate at MILA with 11 years of experience focused on generative modelling, few-shot learning, and model-based optimization. He combines academic rigor with industry impact through visiting research roles at ServiceNow, NVIDIA, and startups like Alpaca and Maket, and has published work on 3D visual question answering and annotation-efficient medical image segmentation. Comfortable bridging theory and application, he co-advises projects on generative approaches for fashion and meta-learning and has contributed to principled evaluation methods for generative systems. Based in Montreal, he brings a track record of translating minimal-supervision ideas into practical representation learning techniques that scale across domains.
11 years of coding experience
6 years of employment as a software developer
Master’s Degree, Computer Engineering, Master’s Degree, Computer Engineering at Université de Montréal - École Polytechnique de MontréalBachelor’s Degree, Computer Science, Hons (First Class), Bachelor’s Degree, Computer Science, Hons (First Class) at The University of Waikato
Github Skills (117)
python10
diffusion-models10
lasagne10
deep-learning10
image-generation10
mnist-dataset10
depth-estimation10
representation-learning10
audio10
diffusers10
text2image10
flux10
theano10
pytorch10
intellij10
Programming languages (10)
Github contributions (5)
christopher-beckham/weka-pyscript
Nov 2015 - Jul 2019
WEKA classifier to execute arbitrary Python scripts
Contributions:18 releases, 6 commits, 2 PRs in 3 years 8 months
classifierpython-scriptswekamachine-learning
christopher-beckham/hologan-pytorch
Sep 2019 - Jul 2020
Non-official + minimal reimplementation of HoloGAN by Nguyen-Phuoc, et al: https://arxiv.org/abs/1904.01326
Contributions:23 commits, 2 PRs, 15 pushes in 9 months
pytorcharxivabsdeep-learningreimplementation
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