Keynotes
Hanchuan Peng, PhD
Fellow: IEEE, AIMBE, AAIA
Executive Director, Institute for Brain and Intelligence
Director, SEU - Allen Institute Joint Center
Title: Large-Scale Profiling of Single Neurons In Whole Brains
Abstract: In current large-scale neuroscience initiatives such as USA BRAIN’s BICCN program and China’s brain science initiative, it is highly desired to generate neuron morphometry data at multiple spatial and structural levels and at the same time to map them to a standard atlas space for systematic data analysis and mining. As a crucial part of the to-date largest data analysis effort in the field, we developed a comprehensive solution with an open cloud computing platform for these goals, as well as rich biology data resources and findings of whole mouse brain cell types and neuronal sub-structures. Our platform features a whole repertoire of tools including cloud-based data serving, multi-clients synergetic computing, mobile and desktop applications, supercomputers, immersive headsets and web interfaces, streamlined high-throughput production pipeline, and interactive data mining. Through the platform, we have tackled petabyte scale computing challenges of different modalities in multiple research labs. The multi-morphometry data generated using our approach supports generating whole-brain connectomes at several multiple levels. Systematic mining of our single neuron resolution data highlights the diversity of neurons, from which we are able to investigate the structural stereotypy of critical neuronal structures for the first time.
Biography: Hanchuan Peng develops technologies to generate, manage, visualize, analyze, and understand massive-scale structure and function data related to brains and other biomedical applications. Peng was the Director – Advanced Computing, Allen Institute for Brain Science, and also an Affiliate Professor with University of Washington. Peng built the first Big Image Computing team of Janelia, HHMI.
With >23,000 citations, he is highly cited for a number of widely adopted algorithms and software/hardware systems, including Vaa3D (http://vaa3d.org) - a high-performance platform for very large multi-dimensional images (Nature Biotechnology 2010, 2016; Nature Methods, 2009, 2011, 2012, 2016, 2017, 2022; Nature Communications, 2014, 2019; Nature Protocols, 2014), mRMR – minimum Redundancy and Maximum Relevance Feature Selection (IEEE-TPAMI, 2005; a top-10 most cited and downloaded paper since 2005), Smart Microscopes (Nature Communications, 2014), etc. He built/co-developed the first 3D digital atlases for several widely used model systems at single cell resolution (C. elegans - Nature Methods, 2009; Cell, 2009; fruitfly - Nature Methods, 2011; mouse – Nature 2021a; Nature 2021b; Nature 2014; Nature Neuroscience 2019), and led the “BigNeuron” initiative (http://bigneuron.org; Neuron, 2015).
Peng was inducted into AIMBE (2019), a co-recipient of USA National Academy of Sciences’ Cozzarelli Prize (2013), DIADEM award (2010), anonymously selected a Top-10 Annual Breakthroughs of Chinese Life Sciences in 2021, Hot Topics for both SfN’2018 and SfN’2019. He was elected as an IEEE Fellow in 2020 for his contribution of big data mining, visualization, and analytics. His work has been featured in Nature, Science, NPR, NBC, New York Times, etc.
Peng founded Bioimage Informatics conferences in 2005, and helped iconize Bioimage Informatics as a new field in major bioinformatics journals including Bioinformatics, BMC Bioinformatics, Nature Methods, Nature Biotechnology, etc. He was the co-Editor-in-Chief of Brain Informatics (2016-2020) and a Section Editor of BMC Bioinformatics (2011-2018), and Bioinformatics (2021-2024).
Dajiang Zhu, PhD
Assistant Professor
University of Texas at Arlington (UTA)
Title: Individualized Connectome Analysis
Biography: Dr. Dajiang Zhu is an Assistant Professor in the Department of Computer Science & Engineering at University of Texas at Arlington (UTA). Dr. Zhu received his Ph.D. in Computer Science from the University of Georgia in 2014. Before he joined UTA, Dr. Zhu was a Post Doctoral Scholar in the Imaging Genetics Center at the University of Southern California. His research focuses on Brain Imaging Computing and Brain-inspired AI. He is a recipient of the “Rising STARs award” of the University of Texas and his research is supported by multiple NIH R01s.