(1/2) Thrilled to share that I’m joining @UWMadison_BME as a tenure-track Assistant Professor starting today! Endlessly grateful to my mentors, friends, and family - I wouldn’t be here without your support 🙏 Excited for what lies ahead! #NewFaculty #UWBadgers

Always great to return to @ubcmath and catch up with the #mathbio community! Today, I spoke at @pimsmath on "Signals, Shapes, and Dynamics: Learning on Graphs for Biomedical Discovery," but the main highlight: hearing from talented students and time with my life-long mentor, LEK.

Excited to moderate the Building Accessibility Breakfast at 8:30 am, organized by the #BMES2025 Social Impact Committee! We have three incredible panelists, Darilis Suarez-Gonzalez, @lenagamboa_, and Duc-Huy Nguyen - sharing insights on accessibility in academia & industry!!

The @UWMadBiophysics program is hosting Virtual Open Houses for prospective grad students next week: ➡️Oct 7 @ 8 AM CT (13:00 UTC) ➡️Oct 9 @ 6 PM CT (23:00 UTC) Info: https://t.co/CW3BLZVyJN I’ll be recruiting exceptional students in #CompBio & #ML - informal inquiries welcome!

Drove to @illinoistech for GLSIAM last weekend to talk about spatiotemporal dynamics in cellular signaling and neural activity through the lens of geometry, topology & ML. Loved the easygoing vibe - perfect for real conversations & community building. Up next: #BMES in San Diego!

Excited for this workshop on expanding the math tools we bring to biology! My work uses #TDA + geometric deep learning for tackling inverse problems and uncovering hidden structure in complex biological systems. Thanks to @WallaceUcsf & Moumita Das (@RITscience) for organizing!

I'm co-organizing a Biological Physics FOCUS session on Physics of #Proteins at #APSSummit26 (Mar 15-20, CO). 3 sessions: ➡️ Structure, Dynamics, Folding ➡️ IDPs & Evolution ➡️ Recognition & Design Work on #AI4Science, #PINNs welcome! Submit by Oct 23:

Abstract deadline for #MathOnco25 extended! I already submitted mine on STAGED: agent-based modeling + attention-based graph neural ODEs to learn cellular communication & GRNs from spatial omics. Great conference for folks at the ML ⇄ math modeling interface - don’t miss it!

Thanks to @joaof_cbr, @Siddharth2814, @KeXU0828 , Shabarni Gupta, and everyone at @GarvanInstitute for making this happen. Looking forward to more of these workshops!

#PHATE has been building momentum as a go-to method for dimensionality reduction + visualization, now surpassing many other approaches. It's integral to many of the techniques we've developed, including Cflows which incorporates a biologically enhanced MIOFlow for traj inference!

All tutorials are FOSS and available on GitHub: https://t.co/9zSUigaUQb The dataset we used comes from our recent #bioRxiv preprint on learning continuous trajectories + GRNs (and much more!) from scRNA-seq data:

Last week we wrapped up the Cancer + ML Workshop at @GarvanInstitute, co-led by @KrishnaswamyLab and @c_chaffer. I presented #PHATE & helped run a hands-on RiTINI tutorial. Thanks to ~200 participants from 14 countries across 6 continents who made it such a rewarding experience!

Back from an amazing week at the Cycle Representatives workshop at @BIRS_Math! I came away with several ideas on how ML + TDA can tackle open problems. Loved brainstorming software, community, and LLMs w/ @elizabethmunch and others. Huge thanks to the organizers & #TDA community!

PFTB was the recommended textbook for Josef Solymosi's Topics in Geometry (MATH 309) I took at @ubcmath. I learnt graph theory from it and got to appreciate just how beautiful proofs can be. I recall we got bonus points for solving the Rubik's Cube under a minute in this class!

Nonlinear dynamics and chaos was probably my favourite class as an undergrad and Strogatz's book is also a classic! An honorable mention here for Ermentrout's mathematical neuroscience book and XPPAUT tutorials that go hand in hand. 4/n

I first encountered #TDA during my PhD at Brown. I read Harer and Edelsbrunner’s Computational Topology cover to cover - more than once. It's rigorous but approachable, and it really impacted how I think about structure in data. 3/n

Leah’s #mathbio primer is an absolute classic. I’ve seen it on syllabi pretty much everywhere I’ve been. I was fortunate to be advised by her as an undergrad, and that honestly changed everything for me. It’s what got me into research and set me on the path to academia! 2/n

It’s hard to pick just four, but I carry multiple copies of these. One for myself, and others to lend out. My copy is full of notes and worked-out problems in the margins. I return to them often! 1/n

Had a great time catching up with friends & colleagues at #SIAMAN25 in Montreal last week! Many thanks to the WCD Organizing Committee - @KJMDPhD, Amanda Laubmeier, Reginald McGee - and to Anna Nelson for inviting me and for putting together a fantastic session!

(2/2) We used a beautiful dataset from @SteinmetzNeuro et al. (Nature 2019), where mice made decisions and movements in response to visual stimuli, to explore how behavior and choice are represented in the brain - and how ML + geometry can help decode them. More to come!

(1/2) Last Fri, I wrapped up 2+ weeks as a Deep Learning project mentor for @neuromatch Academy 2025! Had so much fun learning alongside such a global and talented team: Isaac Thu, Keming Liu, @iyad_bagari, Abu MZ Rahman, and our fantastic TA, Ruixiang Li from @Brown_BME!