
Asst. Prof. @UNMCCC Previously @DanaFarber @HarvardChanSPH @MGHCancerCenter @broadinstitute @genome_gov @UofMaryland Develop AI & statistical models of tumors
Albuquerque, NM
Joined October 2019
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Presenting #LitGene! An interpretable transformer for gene representations, integrating unstructured and structured data - unified framework mitigates bias, enhances interpretability, and grounds AI predictions in scientific literature at tinyurl.com/muu4wyfe 1/2
Our humble approach!
MedGraphNet: Leveraging Multi-Relational Graph Neural Networks and Text Knowledge for Biomedical Predictions biorxiv.org/cgi/content/shor… #biorxiv_bioinfo
Avi Sahu & Lab (hiring)🇺🇦 retweeted
Thanks to KOAT-TV for highlighting Dr. Sahu's work. The Lobo Cancer Challenge provides pilot funding to a number of UNMCCC researchers. Pilot funding helps kick-start the new research projects that deepen our understanding of cancer and how to treat it.
koat.com/article/new-mexico-…
Our lab research highlighted at KOAT TV.
Lobo Cancer Challenge supporting cutting-edge research at UNM | Click on the image to read the full story koat.com/article/new-mexico-…
Avi Sahu & Lab (hiring)🇺🇦 retweeted
Lobo Cancer Challenge supporting cutting-edge research at UNM | Click on the image to read the full story koat.com/article/new-mexico-…
Avi Sahu & Lab (hiring)🇺🇦 retweeted
(1/n) Excited to announce a new article with @rafalab @AviSahuAI describing our approach scDist for finding cell types with transcriptional changes between conditions in single-cell data!
nature.com/articles/s41467-0…
Avi Sahu & Lab (hiring)🇺🇦 retweeted
LitGene: a transformer-based model that uses contrastive learning to integrate textual information into gene representations biorxiv.org/content/10.1101/…
Avi Sahu & Lab (hiring)🇺🇦 retweeted
LitGene: a transformer-based model that uses contrastive learning to integrate textual information into gene representations biorxiv.org/cgi/content/shor… #biorxiv_bioinfo
We demonstrated its capability in predicting protein properties & zero-shot risk genes for obesity, asthma, hypertension, & schizophrenia Accessible at litgene.avisahuai.com 🌐 #AI #Bioinformatics #MachineLearning #OpenScience #EthicalAI
Avi Sahu & Lab (hiring)🇺🇦 retweeted
⚡️🔬📣 Excited to share our new @Nature article building and evaluating PathChat, a multimodal generative AI copilot and chatbot for human pathology. Article: nature.com/articles/s41586-0… Open Access Link:
rdcu.be/dKC0r
We leverage our previous success in building foundation models for computational pathology such as UNI / CONCH and combine it with the advancements of large vision language models and generative AI to enable PathChat to answer diverse pathology-related queries. We assessed PathChat using both multiple choice diagnostic questions and open-ended questions.
Congratulations to @MYLu97 @chenbowen118 @DFKW_MD @richardjchen and everyone else who contributed to this work.
Also see blog post from @MYLu97 about this work: linkedin.com/pulse/towards-m… , also teasing the development and preview of PathChat 2, a successor to PathChat 1 bringing new capabilities and substantially improved performance to the state-of-the-art.
Avi Sahu & Lab (hiring)🇺🇦 retweeted
Why do the loss of chromosome 10 and the gain of chromosome 7 happen so often in #gliomas? We investigate this over-four-decade-old mystery and shed some new light on this! Our work is now out in bioRxiv! #cancer @theNCI @NCIResearchCtr
The co-occurrence of chromosome 10 loss and 7 gain in #gliomas is the MOST frequent loss-gain co-aneuploidy pair in human #cancers, a phenomenon that has been investigated without resolution since the late 1980s. What is this mystery? We investigate! (1/n)
biorxiv.org/content/10.1101/…
Avi Sahu & Lab (hiring)🇺🇦 retweeted
The co-occurrence of chromosome 10 loss and 7 gain in #gliomas is the MOST frequent loss-gain co-aneuploidy pair in human #cancers, a phenomenon that has been investigated without resolution since the late 1980s. What is this mystery? We investigate! (1/n)
biorxiv.org/content/10.1101/…
Avi Sahu & Lab (hiring)🇺🇦 retweeted
Congratulations to Sarah Adams, MD, on being named Dean of the Department of Defense Ovarian Cancer Clinical Trial Academy. This award will also fund an AI-based biomarker discovery project based at UNM with Avinash Sahu, PhD.
Avi Sahu & Lab (hiring)🇺🇦 retweeted
Congratulations to @MuradRMamedov and co-author @AviSahuAI, both 2019 #MichelsonPrizes recipients, on a new paper published in @Nature that uncovers unexpected interactions between T cells and cancer cells: michelsonphilanthropies.org/…
Avi Sahu & Lab (hiring)🇺🇦 retweeted
Congrats, @MuradRMamedov and co-author @AviSahuAI, both 2019 #MichelsonPrizes Winners, for their exceptional research published in @Nature.
gladstone.org/news/how-uniqu…
How likely is it that an email that begins with "hope you are doing well" and ends with "looking forward to hearing from you" was composed by ChatGPT? 🙃
Avi Sahu & Lab (hiring)🇺🇦 retweeted
Just a reminder that you can download the @poe_platform app on your mobile phone and access a lot of artificial intelligence models.
In particular, you can access:
- Sage
- Claude-2-100k
- Claude-instant-100k
- GPT-4
- Claude-instant
- ChatGPT
- ChatGPT-16k
- GPT-4-32k
- Google-PaLM
Avi Sahu & Lab (hiring)🇺🇦 retweeted
Clustering algorithms report clusters even when none exist. In single-cell RNA-Seq pipelines, novel cell types are often identified by clustering algorithms. Expanding on Kimes et al.'s work, we introduce significance analysis for single-cell RNA-Seq data: nature.com/articles/s41592-0…
Avi Sahu & Lab (hiring)🇺🇦 retweeted
Want to join an AI-based antibody therapeutics company with a 1st-in-class molecule in the clinic and help us solve the antibody code? Please consider GV20! linkedin.com/jobs/view/36415…
1/n: Data-to-paper with CHATGPT! Will the resulting papers pass the peer-review process? How will the review process adapt to these sophisticated writing tools? 🤔#AI #peerreview
4/n: Or, could this automation create an efficient pipeline for science and research, leading to a new breed of PIs who can focus on bigger ideas? This feels similar to the 1960s, when computers were becoming widespread. People feared 'technological unemployment' then, too. 🖥️💼
5/n: The fear has fluctuated over decades, depending on economic conditions and pace of technological change. Are we in a similar place now? Is AI and machine learning our new wave of 'technological unemployment'? Is our fear rational or irrational? 📈📉 #technology #fear




















