Aishik Ghosh

The day a statistics student showed me the first concrete results empirically disproving a long-held belief across particle physics about the optimality of our core statistical method. Turns out, our optimality guarantees made unrealistic assumptions, and a better method is actually possible!

I noticed that most of the serious applications start coming in as we get close to the deadline.

Our two new research areas are now live!

📢 𝐆𝐫𝐚𝐝 𝐚𝐝𝐦𝐢𝐬𝐬𝐢𝐨𝐧𝐬 𝐨𝐩𝐞𝐧, 𝐞𝐚𝐫𝐥𝐢𝐞𝐫 𝐝𝐞𝐚𝐝𝐥𝐢𝐧𝐞 𝐭𝐡𝐢𝐬 𝐲𝐞𝐚𝐫!

Physics at 𝐆𝐞𝐨𝐫𝐠𝐢𝐚 𝐓𝐞𝐜𝐡 is accepting applications.

𝐌𝐲 𝐠𝐫𝐨𝐮𝐩 𝐨𝐧 𝐀𝐈 ∩ 𝐩𝐡𝐲𝐬𝐢𝐜𝐬 𝐢𝐬 𝐠𝐫𝐨𝐰𝐢𝐧𝐠! So if you know students interested in 𝐟𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥 𝐩𝐡𝐲𝐬𝐢𝐜𝐬 𝐨𝐫 𝐚𝐬𝐭𝐫𝐨, please share this.


🗓️ Deadline: 𝐃𝐞𝐜𝐞𝐦𝐛𝐞𝐫 𝟏𝟓


🔗 physics.gatech.edu/academics/gr...

📢𝐉𝐨𝐛 𝐚𝐥𝐞𝐫𝐭: Postdoc position(s) in 𝐀𝐈 𝐟𝐨𝐫 𝐟𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥 𝐩𝐡𝐲𝐬𝐢𝐜𝐬 focusing on either 𝐬𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐚𝐥 𝐢𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞 or 𝐀𝐈-𝐚𝐬𝐬𝐢𝐬𝐭𝐞𝐝 𝐭𝐡𝐞𝐨𝐫𝐲.
🏙️Join my new group at 𝐆𝐞𝐨𝐫𝐠𝐢𝐚 𝐓𝐞𝐜𝐡, based in 𝐰𝐨𝐧𝐝𝐞𝐫𝐟𝐮𝐥 𝐌𝐢𝐝𝐭𝐨𝐰𝐧 𝐀𝐭𝐥𝐚𝐧𝐭𝐚!
🗓️ Reviews begin sooner, deadline: 𝟓𝐭𝐡 𝐃𝐞𝐜𝐞𝐦𝐛𝐞𝐫
💬 Questions: Reach out!
🔗 inspirehep.net/jobs/2962185

🚨 Job Alert

We're hiring our first Postdoc to work with us on our @erc.europa.eu Project on Generative AI for Particle Physics.

Check out the details below and don't hesitate to get in touch or spread the word!

Deadline: Nov 30th

inspirehep.net/jobs/3075448

Oh yeah and without a paid version, Slack+zoom is far less smooth, especially for ad-hoc chats.

I did a straw poll with some students yesterday. Several do like Discord but prefer to discuss research on Slack. Some kind of work-life balance :)

Nice! Any preference? Which do you use for your group @claudius-krause.bsky.social?

Setting up my research group Slack workspace (free version). Has anyone considered Discord / Zulip / something else? @marielpettee.bsky.social @lukasheinrich.com

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!

Like AI + Physics, which is a well-developed field but we're still only scratching the surface of what we can do!

Congratulations @lukasheinrich.com, such good news!

Tagging @georgiatechai.bsky.social and @gtsciences.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!

Congratulations!

And we’re also listening to the constructive criticism, the most universal request, we need coffee in all the ‘coffee breaks’!

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!

Finally, Elham E Khoda talks about efficient ML and fast inference on FPGAs

Today we have the ATLAS, CMS and Neutrino parallel sessions at the ML4FP School. Julia Gonski give us an overview of ML in ATLAS

Finally, Chase Shimmin tells us about fun opportunities in the start up world!

Now @ozamram.bsky.social discusses simple and advanced anomaly detection techniques in HEP

Day 4: Sascha teaching us about diffusion, flows and all things generative

GPT-5 vs GPT-4

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...

Day 3: We're scratching our heads over the attention mechanism.

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.

Now Dennis Noll energising the room with his lecture on advanced topics in the fundamentals of ML

Kevin Greif just gave a fantastic tutorial on training your first network

Sascha Diefenbacher teaches us about the fundamentals of neural networks

tagging @berkeleylab.lbl.gov