Arvis Sulovari

WORK HISTORY

EDUCATION

ABOUT ARVIS SULOVARI

I am passionate about translating the complexity of human biology into real-world impact. I am currently pursuing this mission by building intelligent systems that accelerate innovation across scientific disciplines. I studied Computer Science and Human Genetics during my undergraduate at Dartmouth College, followed by two years in Dr. Jason Moore’s Computational Genetics Lab, where I used machine learning guided by biological heuristics to uncover genetic epistasis in cancer. I went on to earn a PhD in Human Genetics at the University of Vermont under Dr. Dawei Li, focusing on statistical and computational genetics of neuropsychiatric disorders, and published the first CNV-based GWAS for substance use disorders among 7 other first-author publications. As a postdoctoral fellow with Dr. Evan Eichler (2017–2020), I deepened my expertise in human genomics, long-read sequencing, and neurodevelopmental disorders. I assembled and genotyped complex genomic regions across species, discovered tandem repeats linked to genetic instability, and analyzed tens of thousands of whole-genome sequences from families affected by autism. Using multiple sequencing platforms (PacBio, ONT, 10x Genomics, Strand-Seq, Illumina), I identified novel sequences and disease-causing structural variants that improved genetic diagnoses (Miller, Sulovari, Wang et al, AJHG 2021) and refined the human genome reference (Audano & Sulovari et al, Cell 2019).At Cajal Neuroscience (2020–2025), I led human genetics efforts for neurodegenerative disease target discovery, integrating patient genetic and multi-omic data. Since mid-2025, I’ve been part of Edison Scientific, a FutureHouse spin-out developing an AI-driven discovery platform. I use the platform to generate new biological insights, evaluate its performance, and explore novel biomedical applications while supporting early partnerships that turn discoveries into real-world scientific and therapeutic impact.