Rishal Aggarwal
Machine Learning, Statistical Mechanics, Structural Biology. F1 and Football ⚽. PhD Student CMU-Pitt Comp Bio | IIITH | BITS Pilani
- Reposted by Rishal AggarwalIf you like to sample from the Boltzmann distribution and are in San Diego for NeurIPS, be sure to check out Rishal's (@rishalchich.bsky.social) poster (#2110). Great work with Nick Boffi (@nmboffi.bsky.social) and Jacky Chen. neurips.cc/virtual/2025... arxiv.org/abs/2507.00846
- Reposted by Rishal AggarwalOur new preprint PharmacoForge: Pharmacophore Generation with Diffusion Models is out now! PharmacoForge quickly generates pharmacophores for a given protein pocket that identify key binding features and find useful compounds in a pharmacophore search. Check it out! 🧪 doi.org/10.26434/che...
- Reposted by Rishal AggarwalHappy to introduce 🔥LaM-SLidE🔥! We show how trajectories of spatial dynamical systems can be modeled in latent space by --> leveraging IDENTIFIERS. 📚Paper: arxiv.org/abs/2502.12128 💻Code: github.com/ml-jku/LaM-S... 📝Blog: ml-jku.github.io/LaM-SLidE/ 1/n
- Reposted by Rishal AggarwalLong & windy road of academic publishing! Few journal rejections and two years (!!!) after preprint, AIMNet2 paper was just published @chemsocrev.rsc.org With 69 citations to it as of now, it's immediately part of 2025 HOT🌶️ Article collection. pubs.rsc.org/en/content/a... #chemsky #compchem
- Reposted by Rishal AggarwalThanks to everyone for helping make #ICLR2025 successful. 🥳 It was an honor to serve as General Chair. The best part was using @iclr-conf.bsky.social as my personal meme account the past two years (first as Senior Program Chair). I hope that future ICLR organizers continue the tradition. 🤪
- Reposted by Rishal AggarwalPlease welcome AITHYRA, the Research Institute for Artificial Intelligence of the Austrian Academy of Science on social media. Follow us and connect via Bluesky and LinkedIn 👋
- Reposted by Rishal AggarwalOur latest preprint is out on bioRxiv! A collaboration between the groups of @martinsteinegger.bsky.social , David Jones and Christine Orengo, we clustered AlphaFold Database and ESMatlas, a whopping 821 million proteins! We reveal biome-specific groups & over 11k novel domain combinations.
- Reposted by Rishal AggarwalHello, we are AITHYRA! I am very excited to share with you the corporate identity of AITHYRA, the Research Institute for Biomedical AI. Check out the brand design video (sound on!) to learn more. **REMINDER** One week left to apply for Starting PI positions (Life Science and AI/ML). Come join us!
- We proudly present to you the #AITHYRA corporate identity, a mixture of logo, motion and sound design. Thanks to our Design Partner Studio Dumbar for a creative and joyful process, and the OeAW and BIS for giving us the confidence and trust to go new ways. More to come www.oeaw.ac.at/aithyra/news...
- Reposted by Rishal Aggarwal"De novo prediction of protein structural dynamics" I'll be presenting an overview of the field tomorrow at a workshop. Link to a PDF copy of the presentation: delalamo.xyz/assets/post_...
- Reposted by Rishal AggarwalWho is at #AACR25? I’m here representing my group’s work at the intersection of AI and drug resistance in cancer, and want to hear about what you’re doing!(1/4)
- @iclr-conf.bsky.social blog posts are now live at iclr-blogposts.github.io/2025/blog! Unfortunately I won't be able to present our blog post at the conference in person 😔, but I am happy to chat about it online if you find it interesting! Poster attached 🙂.
- New "blogpost" from our lab, that got accepted at ICLR 2025! We compare an old MCMC method known as Sequential Monte Carlo to generative models trained on energy functions (iDEM/iEFM) and show that MCMC does better. Check it out here: rishalaggarwal.github.io/ebmvsmcmc/
- New "blogpost" from our lab, that got accepted at ICLR 2025! We compare an old MCMC method known as Sequential Monte Carlo to generative models trained on energy functions (iDEM/iEFM) and show that MCMC does better. Check it out here: rishalaggarwal.github.io/ebmvsmcmc/
- With this baseline, we emphasize that such generative methods should focus on computational efficiency and transferability in their model design and benchmarks. Work done with Daniel ( @countrsignal.bsky.social ), Justin ( @shaojus.bsky.social ), and Minhyek ( @minhyekj.bsky.social )
- New paper at the turn of the new year :) Check out our latest paper on using reinforcement learning for pharmacophore elucidation on protein binding sites. It comes with a google colab notebook for use. bmcbiol.biomedcentral.com/articles/10....
