Principal Investigator


 
LingchongYou.jpg
 

Lingchong You

James L. Meriam Distinguished Professor of Biomedical Engineering

Director, Center for Quantitative Biodesign

you@duke.edu
Duke BME
Google Scholar

Ph.D. University of Wisconsin at Madison, 2002
M.S. University of Science and Technology of China (China), 1997
B.S.E. Chengdu University of Science and Technology (China), 1994

 
 
 

Postdoctoral Fellows

 

 
Emrah.png

Emrah Simsek emrah.simsek@duke.edu

Ph.D. Physics, Emory University (2019)

My research revolves around ecology and evolution of microbial communities with specific emphases on antibiotic resistance, spatial dynamics, and pattern formation. I generally employ a combination of mathematical modeling, experimental microbiology, and synthetic biology

 
Dongheon.jpg

Dongheon Lee dongheon.lee@duke.edu

Ph.D. Chemical Engineering, Texas A&M University (2020)

Currently I’m working on a hybrid mechanistic-data-driven approach to model complex biological processes.

 

Rohan Maddamsetti (personal website)

rohan.maddamsetti@duke.edu

Ph.D. Evolution, Ecology, and Behavioural Biology, Michigan State University (2016)

My current research focuses on experimental evolution, microbial genomics and synthetic biology.

 

Xiaoli Chen xiaoli.chen@duke.edu

Ph.D. Energy and Resources Engineering, Peking University (2024)

I am broadly interested in the assembly and evolution of microbial communities, mainly focusing on how microbial interactions impact the evolutionary and ecological dynamics of microbial communities.

 
 
 

PhD Students

 

 
HelenaMa.jpg

Helena Ma
helena.ma@duke.edu

B.S. Chemical Engineering, Princeton University (2017)

My research focuses on understanding the principles that govern evolutionary response of bacteria to combination treatments and developing a framework for optimizing combination dosing.

 

Jia Lu
jia.lu@duke.edu

B.S. Biology and Mathematics, McGill University (2017)

I’m working on programming microbial spatiotemporal dynamics using synthetic biology and computational tools. In particular, I focus on self-organized patterning systems such as Pseudomonas aeruginosa, an important pathogen in infectious disease, and engineered E.coli.

 
KyeriKim.jpg

Kyeri Kim
kyeri.kim@duke.edu

B.S. Physics and Biological Science, Sookmyung Women’s University (2014)
M.S. Biomedical Engineering, Duke University (2019)

I am currently working on modeling of the bacterial heterogeneous growth population dynamics in β-lactam antibiotics treatment to enrich certain subpopulations and designing experiments using growth rate reporter proteins, microfluidic chambers, and the single live cell microscopy.

 
KatieDuncker.jpg

Katherine Duncker
katherine.duncker@duke.edu

B.S. Biomedical Engineering, Northwestern University (2019)

I'm working on encapsulating engineered bacteria to control bacterial population dynamics and create a multi-sensing and actuating system for applications in medicine and environmental remediation.

 

Zhengqing Zhou (personal website) zhengqing.zhou@duke.edu

B.S. Physics, Peking University (2021)

I am broadly interested in the ecology of microbial communities and plasmids. I combine mechanistic modelling, machine learning and quantitative experiments to elucidate the principles of bacteria interactions.

 

César Villalobos cesar.villalobos@duke.edu

B.S. Biotechnology Engineering, Monterrey Institute of Technology and Higher Education (2021)

I am interested in feedback systems within bacterial communities. I want to understand how they can be modeled and engineered for industrial and pharmaceutical settings.

 

Ashwini Shende

ashwini.shende@duke.edu

B.S.E. Chemical and Biological Engineering, Princeton University (2023)

I am interested in investigating the environmental factors that influence horizontal gene transfer and plasmid persistence in bacterial communities.

 
HyeinSon.jpg

Hye-In (Hailey) Son
hyein.son@duke.edu

B.S. Bioengineering, UC Berkeley (2015)

I am interested in understanding the dynamics of antibiotic resistance spread among bacterial cells. This study may contribute to the development of a novel therapeutic method to reverse antibiotic resistance.

 
YuanchiHa.jpg

Yuanchi Ha
yuanchi.ha@duke.edu

B.S. Computer Science and Mathematics, University of California San Diego (2018)

I am using mathematical analysis, modeling, and machine learning to predict relationships in complex microbial communities to understand the information encoded by complex biological features.

 
ZacharyHolmes.jpg

Zachary Holmes
zachary.a.holmes@duke.edu

B.S. Chemical Engineering, Purdue University (2013)

I am using gene circuits to develop population dependent behavior to manufacture molecules of interest. Within my research, I use division of labor (DOL) and encapsulation with the intention of developing an effective biomanufacturing platform. 

 
Hamrick_Headshot.JPG

Grayson Hamrick grayson.hamrick@duke.edu

B.S. Chemistry, B.S. Mathematics, Haverford College (2021)

My current research is focused on combining metabolic division of labor and horizontal gene transfer for the design of microbial communities with robust function.

 
 

Kinshuk Sahu kinshuk.sahu@duke.edu

B. Tech. and M. Tech. Biochemical Engineering, IIT (BHU) Varanasi, India (2019) M.S. Bioengineering, University of California San Diego (2022)

I am interested in using synthetic and systems biology tools to understand the dynamics of pattern formation in microbial systems.

 

Kristen Lok

kristen.lok@duke.edu

B.S. Bioengineering, UC Berkeley (2023)

I am interested in using directed evolution, division of labor, and horizontal gene transfer to engineer microbial consortia.

 
 
 

Master’s Students

 

 

Zhixiang Yao zhixiang.yao@duke.edu

B. S. Materials Science and Engineering, Technion-Israel Institute of Technology (China) (2022)

My current research interest lies in plasmid dynamics and different approaches to cure plasmids carrying antibiotic resistance genes in a bacterial community.

 

Jiwoo Chae
jiwoo.chae@duke.edu

B.S. Environment and Information Studies, Keio University (2023)

I am interested in investigating the quantitative bacterial responses to antibiotics including the dynamics at population-level and the horizontal gene transfer of antibiotic resistance genes among plasmids.

 

Sizhe Liu sl804@duke.edu

Bachelor of Engineering, Sun Yat-sen University (2022)

I’m interested in programming bacteria with synthetic biology tools and exploring their potential applications in medical and biomanufacturing fields. 

 
 
 

Research Associate


 

Harris Davis

harris.davis@duke.edu

B.S. Biology and Mathematics, UNC Chapel Hill (2023)

Currently, I am interested in mathematical modeling of microbial community dynamics and applying those models to biosynthetic pathways for small molecules.

 

Undergraduates


 

Ryan D’Cunha ryan.dcunha@duke.edu

Biomedical engineering and computer science(2025)

I’m working with Katie on encapsulating engineered bacteria and expressing synthetic amyloids in cells to control bacterial populations.

 

Alex Hoffman alexandra.hoffman@duke.edu

I am working with Zach to characterize the effects of genetic mutations on bacterial growth rate and lag time. My work involves both wet lab work and machine learning.

 

Ryan Su

ryan.su@duke.edu

Biomedical Engineering and Computer Science (2026)

I'm currently working with Emrah on studying population density-dependent antibiotic resistance in bacterial populations, with the goal of finding a universal mechanism responsible for resistance to many antibiotics.

 

Helen Xu helen.z.xu@duke.edu

Computer Science and Biomedical Engineering (2024)

I am working with Helena to understand the factors that affect the growth of antibiotic resistant bacteria to optimize antibiotic and inhibitor combination treatments.

 

Anokh Ambadipudi

anokh.ambadipudi@duke.edu

Biophysics and Computer Science

I am currently engaged in a collaborative research effort alongside Zhengqing and Andrea, which involves a combination of wet lab and dry lab methodologies, to gain a comprehensive understanding of plasmid persistence in multi-strain communities over extended periods by investigating factors such as segregation errors, plasmid burden, and horizontal gene transfer..