Priyanka is a postdoctoral fellow, co-mentored by Prof. James Fraser and Dr. Willow Coyote-Maestas at UCSF. She is interested in integrating deep sequencing with machine learning techniques to determine the structural basis of fusion protein-driven oncogenesis. She did her Ph.D. at Indian Institute of Science under the supervision of Prof. Raghavan Vardarajan. She developed high-throughput screens using deep mutational scanning to study the effects of mutations on protein activity, stability, and co-translational folding.
Alex is a postdoctoral researcher in Prof. Nicolas Thomae’s lab at EPFL in Lausanne, Switzerland. She is currently working on establishing high-throughput screening assays to develop novel cancer drugs and uses deep mutational scanning to understand targetable protein interfaces. In her PhD, which she did in Dr. Guillaume Diss’ lab at the FMI in Basel, Switzerland, she worked on sequence-function relationships of protein-protein interactions by conducting deep mutational scanning of an entire protein domain family.
Ohanna is a CANSSI STAGE postdoctoral researcher at the University of Toronto in the Dalla Lana School of Public Health. She applies statistical methods in DNA methylation and whole genome sequencing data to understand the epidemiological, genetic, and epigenetic determinants of complex diseases. A molecular biologist by training, Ohanna received a master’s and PhD degree in Genetic Epidemiology from the Oswaldo Cruz Institution in Brazil, where she studied genetic susceptibility of infectious diseases in admixed population. For her bachelor’s degree, Ohanna received a master's and PhD degree in Cellular and Molecular Biology from the Oswaldo Cruz Foundation (FIOCRUZ/Brazil). Her dissertation focused on the Genetic Epidemiology of Infectious Diseases. Currently, she is a Postdoc of the CANSSI Ontario STAGE HostSeq Project in Dalla Lana School of Public Health at University of Toronto, studying genetics and epigenetics of complex traits.
Matteo is a Novo Nordisk Foundation Postdoctoral Fellow at the University of Oxford / University of Copenhagen, where he is supervised by Prof. Charlotte Deane and Prof. Philip Biggin. Matteo's current research interests are in immunoinformatics, computational structural biology and variant effect prediction. During his Ph.D. in Biology, supervised by Prof. Kresten Lindorff-Larsen at the University of Copenhagen, Matteo worked on understanding the mechanisms behind loss-of-function and built predictors to classify variants based on their effects on proteins.
Ziyi is a PhD student in the Department of Molecular Genetics at the University of Toronto, under the supervision of Dr. Gregory Costain. Her doctoral research focuses on leveraging large-scale genome sequencing data to investigate variant effects and their transmission within human populations. In addition to her primary research, Ziyi actively participates in workgroups dedicated to newborn sequencing and engages in scientific outreach initiatives.
Yi-Wen is a Postdoctoral Scientist in Dr. Pei-Chen Peng’s lab in the Department of Computational Biomedicine at Cedars-Sinai Medical Center. His research focuses on cancer genomics, cancer epidemiology, and artificial intelligence in healthcare. By leveraging large-scale genomic, pathology, and clinical datasets, he develops statistical and machine learning methods for cancer risk prediction, treatment decision-making, and precision oncology. His work aims to translate biomedical discoveries into clinically actionable tools that support personalized cancer care.
Nurdan is a postdoctoral researcher in Dr. Adam Siepel's lab at Cold Spring Harbor Laboratory, where her research spans computational evolution and population genomics, with a current focus on developing a polygenic risk prediction approach using ancestral recombination graphs. She is broadly interested in variant interpretation, building on her previous postdoctoral work at Sabancı University in Türkiye, where she developed phylogeny-aware methods for predicting the effects of missense mutations and detecting protein coevolution. Nurdan's background is in mathematics and optimization, and she enjoys working at the interface between statistical methodology and human genetics.
Jingyou is a PhD student in the Department of Computer Science at the University of California, Los Angeles, where she conducts research under the guidance of Dr. Harold Pimentel. Her work focuses on developing rigorous statistical inference frameworks tailored to diverse types of deep mutational scanning data. Additionally, she is informally co-mentored by Dr. Willow Coyote-Maestas at the University of California, San Francisco, where she enjoys bridging computational analysis with experimental biochemistry and biophysics.
Justine is a PhD candidate in Biological Engineering at MIT, where she conducts research in Paul Blainey's lab. Her work combines genomic screening with microscopy to study how genetic perturbations affect cell biology — bridging high-throughput sequencing and quantitative imaging to link genotype to phenotype at scale.
Adelaide is an NHGRI MOSAIC K99/R00 postdoctoral fellow at the University of Michigan where she works with Drs. Stephen Parker and Jacob Kitzman. She completed her PhD training in statistical genetics and genomics to study gene-environment interactions. Currently, she leads a multi-institution effort to characterize all noncoding variants associated with type 2 diabetes across cell types and stimulation states using massively parallel reporter assays. With the support of her K99/R00 award, she is building a research program to study broad aspects of complex disease including network circuitry disrupted along the continuum of monogenic and polygenic human diseases.
