What is Quantitative Biology ?
Mission
The Quantitative Biology Initiative (QBI) at UMD's Department of Biology aims to advance quantitative approaches to understanding life sciences through collaborative research, advanced training, short- and long-form courses, and community building.
Our Vision
The Quantitative Biology Initiative (QBI) stems from the joint efforts of a core group of faculty, scientists, and students within the Department of Biology at UMD who share a common interest in leveraging mathematical modeling and data analytics to understand and explore complex living systems.
QBI members use quantitative approaches to study three main topics: ecology and evolution, epidemiology, and sensory neuroscience. In each, advances in experimental methods and large-scale data acquisition are spurring new methods for quantitative analysis— and vice versa. Our researchers advance biological understanding by building and utilizing new mathematical and computational tools, including dynamical systems of differential equations, agent-based modeling, stochastic processes, graphical models for statistical learning, deep neural networks, and other machine learning methods.
The QBI is equally focused on community-building and trainee development. Together, we provide training resources, share and discuss research in progress, reduce barriers to collaboration, and teach short- and long-form courses aimed at preparing trainees at all levels to meet grand challenges at the interface of health and the environment.
Our Research Areas
Ecology & Evolution: Predicting the future by analyzing the past
Using data from genome sequencing, ecological observation, and remote sensing, we model ecological and evolutionary dynamics to look forward and backward in time.
Spotlight: You probably have a favorite route you take to school or work, and research from Bill Fagan’s lab suggests that, thanks to evolution, cats and dogs do, too— but more so for canine species than their feline counterparts.
Epidemiology: Uncovering how epidemics spread in human, microbial, and plant systems
We trace how pathogens affect people— both directly through infection and indirectly by infecting hosts in the surrounding environment.
Spotlight: The blue-green algae in our oceans make up one of the planet’s largest carbon sinks, so what happens when they get sick? Joshua Weitz’s lab models the links between viral infections in cyanobacteria and the carbon cycle.
Sensory Neuroscience: Modeling the flow of sensory information from brain to behavior
We develop new tools to study how brains interpret sensory inputs to produce outputs at different layers of the nervous system that ultimately affect behavior.
Spotlight: Ever find it difficult to get a word in? Jonathan Simon’s lab studies how the brain processes information from competing talkers, with an interest in finding solutions for older adults.
Many of our research groups answer questions at the nexus of two or more of these topics. In Emme Bruns’s lab, researchers study how plants evolve alongside the infectious diseases that impact them, including through environmental pressures like heat.
Our Community
Our community of quantitative biologists is highly interdisciplinary but united through our shared quantitative approach. We span backgrounds including computer science, mathematics, physics, population genetics, and statistics, but we all focus on biological questions. Being part of our community means helping advance biology and strengthening connections between research groups, regardless of whether you’re a student, postdoctoral scientist, or faculty.
Explore our lab groups
The Bruns Lab uses models of ecological and evolutionary change to reveal how pathogens and their hosts coexist, with a focus on how traits like resistance and infectivity rapidly evolve to impact disease dynamics. Their ongoing projects span several questions, including how age-related factors affect transmission and resistance and how heat-sensitive pathogens evolve in response to temperature change.
Graduate students: Yanelyn Perez, Yang Yang, Michelle Launi
Postdocs: Sam Hulse
Dubbed the NeuroTheory Lab, this group both develops high-level theories of sensory system function and works to design and perform experiments to validate them. Additionally, the lab builds new analytical tools that help conduct these experiments and allow researchers to glean new information from legacy research.
Graduate students: Isabel Fernandez, Vinith Kugathasan
Researchers in the Cummings Lab address a wide variety of biological questions using data science methods like machine learning, description, hypothesis testing, hypothesis generation, prediction, and diverse statistical methods. Their currently funded research topics range from malaria antibody response in early childhood to the link between hearing and cognitive impairment in older adults.
Graduate students: Sondos Abdelhafeez, Alexa Boleda, Yi Chen
The Fagan Lab interrogates fundamental problems in ecology and evolution research, such as how changes to the timing of biological events may impact ecological populations and communities. Additionally, they are interested in developing statistical and computational tools to unlock the potential of animal tracking datasets for answering questions about how wild animals use space as they feed, grow, mate, and migrate.
Graduate students: Stephanie Chia, Qianru Liao, Frank McBride, Marron McConnell, Gayatri Anand, Phil Koshute
Postdocs: Pinar Baydemir Dastan, James McClaren
The Johnson Lab integrates classic population genetics and modern machine learning methods to infer when and where populations experienced natural selection or demographic changes. By developing statistical and mathematical models, researchers investigate adaptive immune systems in vertebrates and microbes as well as key steps in human evolution.
Graduate students: Flannery McLamb, Guillermo Hoffmann Meyer
Called the Quantitative Resilience Lab, this group uses nonlinear and stochastic dynamics, statistics, and AI to develop and test fundamental theories. Their work concerns how and why biological systems— whether that’s networks of species, bacteria, or neurons— are arranged the way that they are, and moreover how they can or cannot adapt to changing conditions.
Postdocs: Amy Patterson
The Maltas Lab centers complex biological systems, with examples spanning from the evolution of cancer and its resistance to yeast in fluctuating environments. Informed by quantitative approaches from disciplines like ecology, statistical physics and economics, the lab leverages quantitative methods to understand and ultimately control how these complex systems evolve.
Jonathan Simon’s lab answers questions in applied and theoretical neuroscience, with an emphasis on neural processing in the brain’s auditory system in both humans and other mammals. Their research investigates how aging and neural connectivity affect auditory processing, as well as how neural connectivity affects auditory processing in older adults and in patients undergoing recovery from stroke.
Graduate students: Vrishab Commuri, Charlie Fisher, Isabella Dallasta, Kavin Loganathan, Sophea Biswas
Postdocs: Karl Lerud, Samer Nour Eddine
Researchers in Joshua Weitz's Quantitative Viral Dynamics group explore how viruses transform human and environmental health, synthesizing theory, computational simulations, and model-data integration. This approach allows them to characterize environmental viral dynamics, advance the development of novel, viral-based therapeutics, and assess the link between human behavior and disease transmission as part of virally-mediated outbreaks.
Graduate students: Ali Fayyaz, Kejia Zhang, Lahne Mattas Curry, Akash Arani, Raunak Dey
Postdocs: Tapan Goel, Paul Frémont, Mallory Harris, Jacopo Marchi, Julie D. Pourtois
Learn With Us
Our work seeks to break the paradigm of requiring parallel lines of training in quantitative science and biology. Instead, we explicitly unite these areas to drive discovery at their intersection. We offer a range of courses taught by faculty within the Initiative as well as courses taught by postdocs. We are passionate about training the next generation of quantitative biologists, and in the past we have worked with undergraduates to help them develop and teach courses through the University of Maryland’s student-initiated courses (STICs) program.
Formal courses offered by initiative faculty:
Mathematical Modeling in Biology (BSCI374/HLSC374/BIOL667)
Population Genetics (BSCI405/BIOL709C)
Statistics & Modeling for Biologists (BIOL705)
Quantitative & Computational Biosciences (BSCI 435)
Computational Neuroscience (NSCS 643)
Theoretical Ecology (BIOL660)
Past student-initiated courses (STiC) taught by undergraduates with a QBI faculty mentor:
R for Biologists
Incoming QBI postdoctoral fellows will collaborate with the department to create summer or winter undergraduate-focused courses in quantitative biology topics.
Beyond The Classroom
We build community through activities and programs that bring together researchers of all levels to present their work, discuss research in progress, and collaborate on cross-disciplinary projects.
Quantitative Ecology & Evolutionary Dynamics (QEED) Seminar Series: Students and postdocs lead a weekly seminar series as a venue to both brainstorm ideas for early stage research and present polished work ready for publication. While faculty attend, the experience is trainee-led to provide students and postdocs with the opportunity to steward the conversation.
Quantitative Biology Postdoctoral Fellow Program: Beginning in summer 2026 and following a biannual cohort model, 3 postdoctoral fellows will work alongside QBI faculty to solve critical problems in quantitative biology. Fellows will build an innovative research program that bridges between disciplines, develop undergraduate-targeted courses, and benefit from a collaborative training and mentoring environment. Applications are now being accepted for the first cohort with a best consideration date of March 14, 2026 [link to posting: https://umd.wd1.myworkdayjobs.com/en-US/UMCP/job/University-of-Maryland-College-Park/Post-Doctoral-Associate_JR103315].
Annual symposium: The QBI will host an annual symposium, acting as a means for researchers to share discoveries and innovations in training. The symposium will highlight quantitative biology topics of broad interest across the QBI and UMD community.