The DiMaio lab interested in developing novel computational tools to determine high-resolution structures using only low-resolution data. Key to this is drawing information from the tens of thousands of previously solved structures.
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Shawn is interested in de novo enzyme design for applications in sustainable chemical bioproduction. Specifically, he aims to develop methods for the efficient generation of novel protein catalysts that can accelerate the transition to a sustainable bioeconomy and reduce the environmental impact of industrial chemical processes. He has a B.S. in Chemical Biology from UC Berkeley.
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Gaby is interested in protein engineering applied toward improving cancer therapeutics, including cellular therapies and antibody-drug conjugates. Through her work, she aims to expand her expertise in immunology and explore ways to harness the immune system’s power to treat cancer. In line with her passion for immunology and protein engineering, she is also interested in vaccine design. Gaby has a College of Engineering Deans Fellowship and a Hispanic Scholar Fund Scholarship. She earned her B.S. in Chemical Engineering from the University of Texas at Austin. Read More
Juyoung is interested in understanding and designing biological mechanisms through an interdisciplinary approach that integrates deep learning with life sciences. He is particularly excited about creating new enzymes or developing tools to model and engineer biological networks and signaling pathways. He has a Korea Foundation for Advanced Studies (KFAS) fellowship. He holds a B.S. in Life Sciences, a B.S. in Mathematics, and a B.S. in Chemical and Physical Biology, which integrates physics and chemistry. Additionally, he completed the MIT MicroMasters program in Statistics and Data Science. Read More
Tingli is interested in developing and applying computational tools for molecular design, with the goal of creating therapeutic molecules for the treatment of diseases. She is also passionate about understanding biomolecular mechanisms through computational methods. As an undergraduate, she conducted research at the intersection of computational biology and pharmaceutical chemistry, working on multiple projects that employed data science approaches and computational modeling. She has a B.S. in Bioinformatics from The Chinese University of Hong Kong, Shenzhen. Read More
Avery interested in coupling computational enzyme design with high-throughput microfluidic assays to understand the principles of engineering dynamics in proteins. In particular, she plans to use these methods to improve enzymes that catalyze challenging reactions such as carbon capture, nitrogen fixation, and plastic degradation. She worked as an undergraduate research assistant in the Michelle Chang Lab, where she structurally characterized and engineered several Fe(II) aKG-dependent radical amino acid halogenases to understand their mechanism better and expand their substrate scope. She has a B.S. Read More
Rafi is interested in developing deep-learning methods to facilitate protein design, including novel enzymes, targeted binders, exciting nanostructures, and more. During his undergraduate studies, he worked on machine learning models for binding affinity estimation and small-molecule library generation. He has a B.S. in Molecular Biophysics & Biochemistry from Yale University. Read More
Arnav is interested in applying machine learning to protein design. He has worked on classifying protein folds in AlphaFold predictions and developing graph neural network-based force fields. He has his B.S. in Bioengineering, UC Berkeley. Read More
Alex is a graduate student in David Baker’s lab as well as a trainee in the University of Washington’s medical scientist training program. He aims to utilize de novo protein design to elucidate the underpinnings of complex biological mechanisms. He holds a B.S. in Quantitative Biology and an M.S. in Quantitative and Computational Biology from the University of Southern California Read More
My lab develops and uses integrated approaches for spatiotemporal, multimodal measure and control of complex living systems from molecules to tissues. We recently created protein-based sensors and actuators for chemical sensing and chemogenetic or optogenetic manipulation of cell behaviors in behaving animals. We developed polony gel (clonal DNA cluster array of ≤ 1-µm features)-based spatial barcoding and sequencing to spatially map single-cell transcriptomes and proteomes in morphologically intact tissues to study physiological, pathological, and pharmacological changes. Techniques frequently used in current projects include protein display and high-throughput screening, polony gel fabrication and sequencing, Pixel-seq, SMI-seq, mass spectrometry, and fluorescence imaging. Read More