So grateful for the experience to work with ⁦Pallavi Tiwari⁩ and ⁦Ruchika Verma⁩ combining deep learning with genomics to identify sexually diamorphic characteristics of #GBM !! science.org/doi/10.1126/sc…

Great to see our review out on macrophage migration inhibitory factor (MIF, most important factor, 😉) as a #TME modulator in Neuro-Oncology Advances pubmed.ncbi.nlm.nih.gov/39233830/ - congrats to @CleClinicLCM medical student Jakub Jarmula on leading this effort, supported by American Brain Tumor Association

Taking some much needed rest and traveling out west for some mountain biking and hiking the back country of Montana and Wyoming.

Researchers led by Tyler Alban and Nadeem Riaz (Nadeem Riaz) showed on a large scale that mutations producing #neoantigen-reactive T cells are likely to decrease in frequency during therapy, consistent with therapy-induced immunoediting. ✏️ 👉 go.nature.com/3XRl4vo

Excited to be part of team science published today in Nature Medicine with Tyler Alban 🗞️ Both NSCLC responders and non-responders had anti-tumor T cells. Responders target clonal antigens. 👉rdcu.be/dVyiU

We get all the cool tech in Timothy Chan lab! Excited to see how label free live cell sorting helps improve our single cell seq data quality! 🧐 LevitasBio

New insights into nivolumab-induced immunoediting bit.ly/403lMIZ  Tyler Alban  Nadeem Riaz  Timothy Chan

Super cool to see our work highlighted by ACIR If you haven’t had a chance to check it out yet this is a great summary!

At the National Academy of Medicine — Joined by my dear buddies and comrades in arms against cancer! Congrats!! Jedd Wolchok Jennifer Wargo MD Luis Diaz

Here at #ASCO2025 excited to give a talk later on our AI work! CLEImmunoUpdate

Incredible opportunity to share the stage tonight with Vamsi Velcheti, MD MBA FASCO tonight at an amazing venue #ASCO2025 CLEImmunoUpdate

Excited to share our manuscript on quantum machine learning! I’m a believer in team science so here we teamed up with quantum computing experts from IBM Research and used quantum ensemble approaches for modeling transcriptomic data to predict IO response. arxiv.org/abs/2506.02213

Great to have John Metzcar visit us yesterday and share insights into how mathematical modeling can inform #GBM growth! Looking forward to continuing these exciting collaborations!