Principal investigator
John M. Marshall, PhD (he/him) Professor in Residence Divisions of Biostatistics & Epidemiology School of Public Health Innovative Genomics Institute Center for Computational Biology University of California, Berkeley (which sits on the territory of xučyun, the ancestral and unceded land of the Chochenyo Ohlone people) Honorary Professor Department of Statistics University of Auckland, Aotearoa/New Zealand Mailing address: School of Public Health, 2121 Berkeley Way #5302, UC Berkeley, Berkeley, CA 94720-7360, USA Phone: +1-510-664-4724 Office: 2121 Berkeley Way #5328 Email: john.marshall@berkeley.edu Website: https://www.MarshallLab.com/ Twitter: https://twitter.com/MarshallJohnM Google Scholar: https://scholar.google.com/citations?user=aG77NyAAAAAJ&hl=en Current CV: JohnMarshallCV.pdf |
John received his PhD in biomathematics from UCLA in 2008 writing his dissertation on the use of gene-edited mosquitoes to control malaria transmission. Prior to joining UC Berkeley, he worked on several aspects of this project as a postdoc - social, cultural and regulatory issues at the UCLA Center for Society & Genetics, ecological field work at the Malaria Research and Training Center in Mali, molecular biology and population genetics at Caltech, and infectious disease modeling and epidemiological field work at Imperial College London. Here at UC Berkeley, he teaches two courses on mathematical modeling of infectious diseases and consults on this field generally. His own research focuses on the use of mathematical models to inform novel genetics-based strategies for mosquito control, and to support efforts to control and eliminate mosquito-borne diseases such as malaria, dengue and Zika virus broadly.
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Héctor M. Sánchez C., PhD
Héctor received his BSc in 2009 in Mechatronics Engineering and his PhD in 2017 in Computer Science at Tecnológico de Monterrey, México. In the past, he collaborated in animal vocalizations research with Charles Taylor (UCLA), the Malaria Elimination Initiative (UCSF), worked as a consultant for David L. Smith (UW) in the software development of mosquito-transmitted diseases models, and was awarded one of the 2016 Google Research Awards in Latin America. Nowadays, his work focuses on modeling, simulating, and analyzing spatio-temporal aspects of CRISPR-based mosquito control interventions. He loves guitars, singing, Pusheen, DataViz, and programming! Email: sanchez.hmsc@berkeley.edu Website: https://chipdelmal.github.io/blog/ |
Rodrigo Corder, PhD (he/him)
Rodrigo earned a BS in Electrical Engineering from the University of São Paulo (Brazil), an Erasmus Mundus Joint MSc in Mathematical Modeling in Engineering from the University of L’Aquila (Italy), University of Hamburg (Germany) and Autonomous University of Barcelona (Spain) - The MathMods Consortium - and a PhD in Biology of Host-Pathogen Interactions from the University of São Paulo. His PhD thesis, which was partly carried out at the Liverpool School of Tropical Medicine (UK), focused on mathematical and statistical modeling of malaria transmission in the Amazon Basin accounting for the local risk heterogeneity and aimed to provide evidence for the rational deployment of control interventions and elimination. He joined the Marshall Lab in July, 2021 and now his work focuses on the development of mathematical models to inform novel genetics-based strategies for mosquito-borne diseases control and elimination. Email: rodrigo.corder@berkeley.edu |
Agastya Mondal, BS (he/him)
Agastya Mondal is a doctoral student in the department of Epidemiology. He received his BS in Biomedical Engineering and Applied Mathematics from Johns Hopkins University in 2016, after which he worked in a variety of software engineering roles in the biotech and humanitarian aid sectors. At Berkeley, he is interested in the intersection of computation, mathematics, and public health, hoping to apply heterogeneous stochastic models, graph theory, and statistical methods to better inform infectious disease dynamics. He also hopes to use these insights to analyze and guide epidemiological policy. A native East Coaster, he enjoys arguing about regional foods, film photography, collecting records, and paying too much for coffee. Website: https://agastyamondal.com Email: agastya_mondal@berkeley.edu |
Shuyi Yang, BS
Shuyi Yang is a MA student from the Biostatistics program at UC Berkeley. She graduated from UC San Diego with a BS degree in Data Science and a minor in Biology in 2018. She is currently working on the Close-kin mark-recapture (CKMR) project under the supervision of Dr. Marshall. She has research experience in mathematical modeling of infectious diseases including COVID-19 and HIV. She also has academic interests in biomedical data science, machine learning, and causal inference. During her leisure time, she enjoys hiking, rock-climbing, and snowboarding. Email: shuyiyang@berkeley.edu |
Victor Mero, MSc
Victor Mero is a PhD student at UC Berkeley, with research interests in infectious disease modeling, particularly vector-borne diseases. Prior to joining UC Berkeley, Victor was a Data Scientist at Ifakara Health Institute (IHI), where he supported the National Malaria Control Program in Tanzania. He holds an MSc in Information and Communication Science from the Nelson Mandela African Institution of Science and Technology (NM-AIST). Beyond his academic pursuits, Victor enjoys fitness and spending time with family and friends. Email: merovictor@berkeley.edu |
Xingli Yu
Xingli is a senior studying Bioengineering, and she is passionate about working at the intersection of biotech and data science. She is currently working on the Mosquito Gene Drive Machine Learning Library under Dr. Héctor Sanchez. Outside of school, she enjoys filmmaking and biking around the city with no particular destination. Email: xingliyu@berkeley.edu |