Session III: Bioinformatics & AI
15:40-17:20
生物資訊的市場將在 2030 年達到 452億美元,是生技中蓬勃發展的領域之一。San Diego作為美國第三大生物產業聚落,許多的知名研究機構以及藥廠均有設點在此,更不用說生技公司是多如繁星。近年由於資訊技術快速進步與硬體開發到位,生物資訊領域蓬勃發展。今年SoCal TBA年會,我們將會跨界生物學與 AI 結合未來新科技的生物資訊研究。 |
Speakers
Dr. Jerry Lo
Computational Scientist III, Genentech |
Jerry completed his Ph.D. degree in Molecular Biology in Stephen Smale’s lab at UCLA, where his research focused on using a combination of bioinformatics approach and CRISPR genome engineering to study the gene regulations in stem cells and innate immune response. After completing his Ph.D. in 2019, Jerry started his biotech career as a Bioinformatics Scientist at the Cancer Genomics Division in Agilent Technologies to lead the R&D efforts of genomics products development. During his term at Agilent, he contributed significantly to the technology development of Whole Exome Sequencing and Target Enrichment RNA sequencing, and participated in two genomics product launches and one patent filing. Trained in Molecular Biology and Computational Biology, Jerry was attracted to Genentech in 2021 by a unique opportunity of joint appointment between gRED (Genentech Early Research & Development) and PTD (Pharma Technical Development). As a Computational Scientist 3 in the Oncology Bioinformatics Department, he focuses on Early Target Identification & Verification, Drug Resistance, and Immuno-Oncology studies using CRISPR genetics screening, coupled with single cell multiomics, to deconvolute gene regulatory networks in different cancer models. On the pharma side, Jerry bridges the cross-functional teams between Cell & Gene Therapy and Cancer Immunotherapy groups to co-develop GxP compliance bioinformatics pipelines for engineered cell products and manufacturing process development.
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Dr. Michael Chien-Cheng Shih
Senior Data Scientist, Novartis |
As a Senior Data Scientist at the Novartis Institutes for Biomedical Research, I partner with life scientists to create advanced image analysis solutions for bio-assay development. Prior to Novartis, I served as a Staff Scientist at the Washington University Center for Cellular Imaging (WUCCI), where I focused on employing state-of-the-art microscopy imaging techniques to advance biomedical research. I earned my Ph.D. from the Department of Pharmacology & Physiology at Georgetown University in 2016.
I embarked on my data science journey at the late stage of my Ph.D., driven by my conviction in its transformative potential. I am confident that machine learning will not only expedite the digitization of life sciences but also foster progress in medical and healthcare research, ultimately yielding lasting benefits for humanity. |
Moderator
Ting Yang
PhD student, UCSD Bioengineering Ting Yang graduated from National Tsing Hua University. During her undergraduate research, she studied the inorganic synthesis and formation of nanoparticles for brain tumor treatment. She also developed a paper-based diagnostic device for chronic wound monitoring. Tina is currently a Ph.D. student at UCSD at Alexandrov Ludmil’s lab, with a focus on cancer genomics and discovering structural variant events during cancer progression. |
Hsuan-lin (Charlene) Her, M.D.
PhD Student, UCSD Bioinformatics Hsuan-lin is currently a Ph.D student at UCSD Bioinformatics and Systems Biology. She is a student in the Yeo Lab, aiming to decode post-transcriptional regulation using computational methods. Previously, she received her M.D. in Taipei Medical University. During her undergraduate work, she studied antibiotic resistance in Escherichia coli pan-genome. She developed an algorithm to infer protein function and characterize several new pathways that might be involved in resistance. She believes that sequencing is the future of medicine and she hopes to be part of this revolution. |