Forecasting COVID-19 cases using Machine Learning models medrxiv.org/cgi/content/sh… #medRxiv

A little side project I worked on. Can ML methods predict with little data? 👀

Today we announced a $180M Series C financing, which will allow us to expand our #AI discovery platform for 'Programmable' RNA therapeutics and support the advancement of our portfolio into the clinic. More here: bit.ly/2UVS3T2 #deeplearning #genomics #financing #biotech

🔴McGill University is red 🔵Canadian Medical Association backpacks are blue 🔴The McGill MD-PhD program welcomes you!

👋I'm Nicole (Xi (Nicole) Zhang). I'm an incoming MD-PhD student at McGill University. I develop and optimize Machine Learning models to better understand and predict biological data. On my spare time, I like to bake, paint and do photography.

We had a great time at our first MD-PhD retreat!

🧩One less missing piece to cell modelling? Our recent work 𝐌𝐞𝐭𝐚 𝐅𝐥𝐨𝐰 𝐌𝐚𝐭𝐜𝐡𝐢𝐧𝐠 incorporates principles in cancer biology - 𝐭𝐮𝐦𝐨𝐮𝐫 𝐦𝐢𝐜𝐫𝐨𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭 to flow matching. And it generalize better to out-of-sample distributions! 🚀

Nicole Zhang (Xi (Nicole) Zhang) is presenting her spotlight poster "Trajectory Flow Matching with Applications to Clinical Time Series Modelling" at NeurIPS Conference' Poster Session 5 East, #1002. Here is a short overview of her research.

We've been sharing these projects during the year, but today, they have been accepted at #ICLR2025 (1-3) and #AISTATS2025 (4) 1. The Superposition of Diffusion Models Using the Itô Density Estimator arxiv.org/abs/2412.17762 2. Meta Flow Matching: Integrating Vector Fields on the

We’re presenting Meta Flow Matching now in Hall 3 poster #13!! Come by and say hi! #ICLR2025 Xi (Nicole) Zhang

Congratulations to Thomas Jiralerspong (UdeM), Austin Kraft (McGill) and Nicole Zhang (McGill), three Mila students awarded the 2025 Vanier Scholarship! #vaniercanada View all 2025 recipients vanier.gc.ca/en/scholar_sea…