PhD Candidate @UTexasILS | Biotechnology and Biochemical Engineering @IITkgp 2022 | Interested in Human Genetics, Evolution, and Deep Learning
Joined December 2018
- Tweets 125
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Pinned Tweet
13 Oct 2025
Half of people with heart disease first find out after a heart attack. What if we could see risk years earlier using MRI, genetics, and blood tests? We introduce preCog, a multimodal AI for preventive cardiology trained on >500k images and genetic data from 1.25M individuals.
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Devansh Pandey retweeted
May 19
New paper from undergrad in my lab on image-based genetic association of scoliosis (i.e. spine curvature) is now out in Npj Digital Medicine. Showing again the power of precision phenotyping with imaging to identify gene targets not possible in the EHR. nature.com/articles/s41746-0…
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Devansh Pandey retweeted
Apr 27
Now published (was previously a preprint) work from @MarianaHarr looks at selection using a domain-adaptive neural network and uses time series data to investigate the affect of admixture on the detection of selective sweeps.
Read it here: pnas.org/doi/full/10.1073/pn…
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Devansh Pandey retweeted
Apr 20
Have you wondered what the wet lab success rates are for current AI-driven protein design models? Look no further!
In our new open access review, @KevinKaichuang, @avapamini, @SarahAlamdari, and I report wet lab success rates for *over 200* different protein design tasks 🧬💻
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Devansh Pandey retweeted
Apr 15
Its finally out! Over 8 years of work by @aliakbari23 shows that selection was pervasive in the last 10,000 years, including for quantitative traits. This was directional selection. Simulations show background selection, etc can not produce the observed patterns.
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🧵Super excited to share our new paper in @NatureGenet ⭐️
We apply a new multiple traits and ancestry approach to improve genetic discovery and polygenic prediction in lung diseases and traits 🫁
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Devansh Pandey retweeted
29 Oct 2025
Congratulations to @EucharistKun for successfully defending his PhD thesis on applying deep learning methods to >1.2M images from 60k people and connecting this to genetic data to understand aging and development. He's on the postdoc job market: scholar.google.com/citations….
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Devansh Pandey retweeted
15 Oct 2025
I will be presenting a poster about the LGM in Europe and the Mesolithic across Eurasia from 2:30 to 4:30 this Friday at ASHG (poster # 6027). It is unpublished and thus subject to change! If you're interested in chatting, please find me there, reach out here, or email me!
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13 Oct 2025
Half of people with heart disease first find out after a heart attack. What if we could see risk years earlier using MRI, genetics, and blood tests? We introduce preCog, a multimodal AI for preventive cardiology trained on >500k images and genetic data from 1.25M individuals.
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13 Oct 2025
I will be presenting this work at #ASHG25 in:
🧬 Session 77 — Beyond Sequencing: Genetic Architecture of Complex Traits
📅 Friday, Oct 17 | 1:30–2:30 PM ET
and also as a poster presentation:
📍 Poster Board: 9080F
🗓 Friday, Oct 17 | 2:30–4:30 PM ET
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13 Oct 2025
Big thanks to my amazing co-authors for their contributions and collaboration on this project. @xliaoyi, @EucharistKun, @joyce_yiyi_wang, @ChenfeiLi2000, @melek_alaa, Julie C. Dicarlo, Edward Castillo, @LubbDup, Charles A. Taylor and @vagheesh
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Devansh Pandey retweeted
15 Sep 2025
New paper on our group applying deep learning to measure spine curvature in thousands of individuals to identify new genetic loci associated with susceptibility. Led by star undergrad Michael Zeosky who is applying to PhD programs this fall!
x.com/EucharistKun/status/19…
15 Sep 2025
Scoliosis is the most common spinal deformity, but its genetic causes are still unclear. Using AI to measure spinal curves in 57,887 people, we discovered 2 novel genetic risk loci - showing how deep learning can unlock insights into musculoskeletal health medrxiv.org/content/10.1101/…
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Devansh Pandey retweeted
15 Sep 2025
Scoliosis is the most common spinal deformity, but its genetic causes are still unclear. Using AI to measure spinal curves in 57,887 people, we discovered 2 novel genetic risk loci - showing how deep learning can unlock insights into musculoskeletal health medrxiv.org/content/10.1101/…
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