New Faculty Spotlight
While Caltech is a small institution relative to other top universities across the nation, its influence on scientific research in a wide variety of fields is immeasurable. Part of what makes this possible is the rigorous recruitment and hiring of the most creative and cutting-edge faculty in the world. The Division of Biology and Biological Engineering is no exception and eagerly welcomes new faculty members praised for their enthusiasm, interdisciplinarity, and innovation.
New Assistant Professor of Biology, Joe Parker, arrived from Columbia University where he was supported by a Sir Henry Wellcome Postdoctoral Fellowship (Wellcome Trust, UK) and an Ellison Medical Foundation Scholarship. He is also a research associate in Invertebrate Zoology at the American Museum of Natural History. Joe received a BSc degree with 1st Class Honors in zoology in 2001 from Imperial College London. He did his graduate work at the University of Cambridge/MRC Laboratory of Molecular Biology, receiving his Ph.D. in 2006. Joe is an entomologist, whose work addresses a fundamental question in biology: how predictable is evolution, and to what extent is evolutionary change pre-determined by ancestral conditions? Joe established a unique model system to address this question: rove beetles that live symbiotically inside colonies of ants and termites. Such species embody evolution in the extreme, with dramatic behavioral, anatomical and chemical adaptations for life as social parasites. Joe has collected and studied these beetles since childhood, and his work has revealed how their extreme adaptations have in fact arisen convergently many times, illuminating the question of how predictable complex phenotypic evolution can be. Not content with studying these beetles' natural history, Joe trained as a Drosophila geneticist, with the goal of transferring the genetic expertise he acquired to rove beetles. He achieved this with the development of a new model species, Dalotia coriaria—a free-living taxon that represents the evolutionary starting conditions for social insect symbiosis in rove beetles. Empowered by new tools for gene manipulation, including CRISPR, Joe's system promises to reveal basic insights into the molecular, genetic and neurobiological changes that underlie the evolution of interspecies interactions in the animal kingdom. The convergent nature of this type of symbiosis in rove beetles provides a paradigm for understanding how complex changes in organismal biology can arise convergently over evolutionary time.
Lior Pachter is a leading computational biologist working in genomics, who came from UC Berkeley to take up the position of Bren Professor of Computational Biology at Caltech. His career began in comparative genomics, initially in genome alignment, annotation, and the determination of conserved regions using phylogenetic methods. He contributed to the mouse, rat, chicken and fly genome sequencing consortia, and the pilot phase of the ENCODE project. More recently he has become focused on functional genomics, which includes answering questions about the function and interaction of DNA, RNA and protein products. He is particularly interested in applications of high-throughput sequencing to RNA biology. Pachter is a bona fide mathematician with a B.S. in mathematics from Caltech ('94), a Ph.D. in mathematics from MIT ('99) and initial tenure at Berkeley as a Professor of Mathematics. Lior's entry into biology came while a graduate student at MIT, which included significant interactions with the Broad Institute. Lior is noted for his ability to go from basic biology all the way to impactful, high-quality software that truly enables quantitative functional genomics research.
New Assistant Professor of Biology and Biological Engineering, Rebecca Voorhees, hails from the Medical Research Council Laboratory of Molecular Biology (MRC-LMB), Cambridge, England, where she is a prestigious Sir Henry Wellcome fellow. Rebecca received her B.S. and M.S. degrees in molecular biophysics and biochemistry from Yale in 2007, and her PhD in molecular biology from the University of Cambridge in 2011. Rebecca studies the chemical and molecular mechanisms of protein production, localization, and quality control. Her current research focuses on what happens to proteins after they are synthesized by the ribosome. First, how are they trafficked to different compartments within the cell, and second, what happens when these processes fail, this work is critical for understanding the molecular basis of numerous human diseases that affect protein folding and localization, such as cystic fibrosis and Alzheimer's disease. Among other things, Rebecca has used cryo-electron microscopy to study how the cell selectively recognizes hydrophobic sequences that must be delivered to the endoplasmic reticulum for their maturation. She made the unexpected discovery that the cell uses progressively more stringent filters for identifying these hydrophobic substrates, which ensures extremely high fidelity in membrane targeting and insertion, thereby preventing protein mislocalization and ultimately disease. For her future work, Rebecca plans to continue to utilize both structural and functional techniques, including X-ray crystallography and single-particle cryo-electron microscopy, to explore detailed structural and mechanistic problems in cell biology.
New Assistant Professor of Computational Biology, Matt Thomson, arrived from UCSF where he is a Fellow with an independent laboratory. Matt received his undergraduate degree in Physics from Harvard University in 2001 and his PhD in Biophysics from Harvard in 2011. Matt's group is applying quantitative experimental and modeling approaches to gain programatic control over cellular differentiation. He is developing mathematical models to ask how cellular regulatory networks generate the vast diversity of cell-types that exists in the human body. He is applying models to engineer and rewire cellular physiology and to synthesize new types of cells that do not exist in nature. He is also developing simplified cellular systems in which physical models can be applied to control the geometry and morphology of different cell types. He uses a combination of approaches including mathematical modeling, machine learning, statistical analysis of high-throughput gene expression data, and single cell RNA sequencing experiments. Recent accomplishments include: Engineering an all-optical differentiation system in which he could optically-deliver pulsed neural differentiation inputs to embryonic stem cells; creating new computational tools for deriving cell state trajectories from single cell RNA-Seq data; and developing a stochastic modeling framework for analyzing principles that enable robust self-organization of the mammary gland.