Aishik Ghosh
@aishikghosh.bsky.social
250 followers 82 following 48 posts
Assistant Professor of AI in School of Physics @ GT Fundamental Physics ∩ AI AI Policy AI for hypothesis generation, simulation, inference in particle & astro High-dimensional statistics, neural inference, uncertainty quantification
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Reposted by Aishik Ghosh
whereisyvette.bsky.social
Yeah, even crazier- last year for my postdoc ad a full half of the applications legit never made reference to anything my lab does and how my research would connect to theirs. You are literally in the top half of applicants for just TRYING to draw a connection in a sentence in the cover letter!
aishikghosh.bsky.social
Like AI + Physics, which is a well-developed field but we're still only scratching the surface of what we can do!
eugenevinitsky.bsky.social
For folks considering grad school in ML, my advice is to explore programs that mix ML with a domain interest. ML programs are wildly oversubscribed while a lot of the fun right now is in figuring out what you can do with it
aishikghosh.bsky.social
Congratulations @lukasheinrich.com, such good news!
aishikghosh.bsky.social
At the launch event for ‪@gtsciences.bsky.social‬'s AI4Science Centre: ai4science.ai.gatech.edu. With colleagues from psychology, math, earth sciences and everything in between. Looking forward to all the cross-pollination within the sciences and also with industry!
aishikghosh.bsky.social
And we’re also listening to the constructive criticism, the most universal request, we need coffee in all the ‘coffee breaks’!
aishikghosh.bsky.social
A little comment like one of these makes my week. Teaching and mentorship is easily the most rewarding aspect of academia. Makes it all worth it. Thanks again to all the students who came to ML4FP and interacted with us for a week. Your positive comments mean the word to us!
aishikghosh.bsky.social
Finally, Elham E Khoda talks about efficient ML and fast inference on FPGAs
aishikghosh.bsky.social
Today we have the ATLAS, CMS and Neutrino parallel sessions at the ML4FP School. Julia Gonski give us an overview of ML in ATLAS
aishikghosh.bsky.social
Finally, Chase Shimmin tells us about fun opportunities in the start up world!
aishikghosh.bsky.social
Now @ozamram.bsky.social discusses simple and advanced anomaly detection techniques in HEP
aishikghosh.bsky.social
Day 4: Sascha teaching us about diffusion, flows and all things generative
aishikghosh.bsky.social
GPT5's explanation for FTS is quite impressive, especially where it gives an intuitive explanation that is not just directly lifted from the paper. Makes it easy to learn a new statistics concept.

chatgpt.com/s/t_6894ece0...
GPT-5 vs GPT-4
chatgpt.com
aishikghosh.bsky.social
Day 3: We're scratching our heads over the attention mechanism.
aishikghosh.bsky.social
Day 2 we have Vinicius Mikuni and Kazuhiro Terao give overviews of AI in collider and neutrino, then an afternoon on neural simulation-based inference & uncertainty quantification with Tae Park, Sean Benevedes and I.
aishikghosh.bsky.social
Now Dennis Noll energising the room with his lecture on advanced topics in the fundamentals of ML
aishikghosh.bsky.social
Kevin Greif just gave a fantastic tutorial on training your first network
aishikghosh.bsky.social
Sascha Diefenbacher teaches us about the fundamentals of neural networks
aishikghosh.bsky.social
As you can see, we're very proud of the broad participation
aishikghosh.bsky.social
And we're off! Yifan Chen welcomes students to the Machine Learning for Fundamental Physics School 2025!
aishikghosh.bsky.social
I just love interdisciplinary collaborations that help us question longstanding assumptions within a field.
aishikghosh.bsky.social
Bonus: Rapid Neyman construction with ML, for those tired of throwing a gazillion toys.
aishikghosh.bsky.social
Gains are quite robust to the choice of your focus function and yield valid confidence intervals by construction.