🧠 At our recent Gerstein Lab roster meeting, we took a detour into… personality science!

Turns out we’re INT Central 🧪
📌 70% Introverts
📌 83% Intuitives
📌 57% Thinkers
Analysts (INTP, INTJ) dominate, far more than the U.S. baseline.

#MBTI #INTP #INTJ

4/4 ⚡ WANet + WALoss ⇒ 18 % faster SCF convergence & 1 000 × energy-error reduction vs. SOTA. One model, many properties—HOMO/LUMO, dipoles, electron densities—all from a single predicted Hamiltonian.

2/4 🧩 We introduce Wavefunction-Alignment Loss + WANet, slashing SCF iterations while keeping ab-initio precision for molecules 3× larger than training data.

1/4 🚀 New #ICLR2025 SPOTLIGHT ALERT
Gerstein Lab presents “Enhancing the Scalability & Applicability of Kohn-Sham Hamiltonians”—led by YunyangLI & Z Xia & L Huang & J Zhang & @markgerstein.bsky.social . Joint work with @msftresearch.bsky.social .

New @biophysj.bsky.social paper by Alan Ianeselli, Joe Howard and @markgerstein.bsky.social . A Molecular Dynamics algorithm to rapidly compute protein folding pathways and identify folding intermediates for targeted drug discovery! doi.org/10.1016/j.bp...

Our new paper describes the iDASH-winning method for efficient blockchain storage of biomedical data. We cut gas costs by 60% and sped up retrieval 500x with low-level Solidity optimization.
By Eric Ni, Elizabeth Knight, @markgerstein.bsky.social
doi.org/10.1016/j.jb...

New paper by Gaoyuan Wang, Jonathan Warrell, Prashant Emani and @markgerstein.bsky.social ! Check out our new model QVAE, a fully quantum variational autoencoder with latent regularization: journals.aps.org/pra/abstract...

New @plosone.org paper by Xiao Zhou, Sanchita Kedia, Ran Meng, and @markgerstein.bsky.social. Our deep learning framework analyzes fMRI scans for early Alzheimer's Disease detection, achieving 92.8% accuracy with a focus on model interpretability: t.co/Ro5WzyJUyZ