Alumni

Jamilla Akhund-Zade

Populations can adopt different strategies to deal with a changing environment – they can adapt through the forces of natural selection or they can ‘hedge their bets’ by having a wide distribution of phenotypes at every generation to ensure some individuals will survive. Jamilla is interested in understanding whether different populations of Drosophila melanogaster adopt one or the other strategy to determine thermal preference behavior. Using modeling simulations to inform her field collections, Jamilla is investigating heritability, variability, and seasonal patterns of fruit fly thermal preference in populations sampled from across the United States.

Deniz Aksel

Deniz is a graduate student in the Biophysics program. He is interested in the coordination of tissue shape changes and cell fate decisions during the early stages of human development. Using embryonic stem cell culture as a model system, he aims to understand key molecular and mechanical parameters that are sufficient to generate the cellular diversity and spatial organization observed in the human primitive streak. To this end, he harnesses tools from synthetic biology and tissue engineering to spatiotemporally modulate signaling pathways as well as the mechanical context of cells.

Felix Barber

Felix completed his undergraduate studies in his home country of New Zealand before completing his masters in theoretical physics at Cambridge University. He is working with Ariel Amir and Andrew Murray, studying how budding yeast cells coordinate their growth with passage through Start to regulate their size. To address this question his research employs diverse tools from computation and mathematical modeling to experimental microbiology. He is currently completing his PhD in Molecular and Cellular Biology at Harvard, with a secondary field in Computational Science and Engineering.

Liyin Chen

Liyin is interested in developing microfluidic systems to solve biology problems. An ongoing project is to isolate and sequence the whole genome of a potential human virus from sewage water. It was found that swage water contains an enormous amount of unidentified viruses, some of which might be able to cause disease outbreaks in human. Being able to identify and sequence these potential pathogens allows us to analyze their etiologies and thus be more prepared for emerging viral diseases. Because the size of viruses is extremely small and the number of them in a sample is huge, we are utilizing droplet microfluidics to handle them in a precise and high-throughput manner. We envision this system greatly accelerating virology research of human viruses.

Gary Choi

Gary is a graduate student in the Applied Mathematics Ph.D. program working with Prof. L. Mahadevan and Prof. Chris Rycroft. His research interests include applied and computational geometry and interdisciplinary mathematical modeling. In particular, he has been developing computational tools for measuring and predicting biological shapes ranging from insect wings to mammalian brains.

Ivana Cvijovic

Ivana is currently working on theoretical models of evolution in fluctuating environment, and is interested generally in theoretical population genetics.

Po-Yi Ho

How does a microorganism decide when to divide? To answer this question, Po-Yi constructs mathematical models of the molecular mechanisms regulating microbial cell cycles. The models seek to explain the statistics of cell size at various cell cycle events obtained using microfluidics and time lapse microscopy. He also takes a similar approach to investigate how microorganisms time divisions in different growth conditions and away from steady state growth. Curiously, past works suggest that diverse microorganisms in all three domains of life share similar strategies to time divisions. It will be interesting to understand why.

Jordan Hoffmann

Jordan is a PhD student in Applied Mathematics (SEAS) advised by Chris Rycroft. The last four years, he has worked in collaboration with Professor Cassandra Extavour (OEB/MCB) and her PhD student Seth Donoughe (now a postdoc at University of Chicago) studying early development of the cricket Gryllus bimaculatus. With S. Donoughe, he developed a computational pipeline to process 4-8 terabyte light sheet datasets of live, developing cricket eggs. His group is now able to collect and track full 3-D datasets of the motion of nuclei as they go from just 4 to over 1000 nuclei and developed a computational model that recapitulates all aspects of motion that we are able to quantify in Gryllus.

Julian Kimura

Julian is a PhD candidate in the department of Organismic and Evolutionary Biology advised by Dr. Mansi Srivastava. He studies the highly regenerative acoel worm Hofstenia miamia, which utilizes pluripotent stem cells to regenerate entire body axes. Specifically, Julian is interested in uncovering the embryonic origins of stem cells. Studying how highly regenerative animals like Hofstenia first form stem cells during embryogenesis would be the first step in answering the basic question of how stem cells are made. Julian is using a combination of single cell sequencing and computational tools on Hofstenia embryos to identify and test genes that may be involved in this process. 

Elizabeth May

Elizabeth is a fourth year graduate student in Rachelle Gaudet’s lab, where research focuses on signaling and transport across biological membranes. Elizabeth investigates the interactions and properties of biomolecules that control contact-dependent signaling in the developing central nervous system. These molecules perform important cell-cell communication that coordinates proper development in the brain, making sure that neurons make all the right connections. The movement and interactions of these molecules in groups are key to deciphering how the brain coordinates its development.

Matthew Melissa

Matthew is interested in further exploring the range of possible behaviors that can emerge given the simplest models of asexual evolution. Evolution can be modeled as a stochastic process governed by the forces of mutation, selection and genetic drift. The simplest differential equations which describe this process are nonlinear and nonlocal, making it difficult, except in certain cases, to achieve even a qualitative understanding of the dynamics. He is working to apply methods of perturbation theory to improve our understanding of the qualitatively distinct regimes relevant to microbial populations, and to identify which dynamical features are more universally obtained.

Samuel Melton

Sam studies how genes form circuits that process information and mediate transitions of cellular identity during development. His research focuses on developing computational tools to analyze high dimensional gene expression data, particularly in regimes where the number of dimensions is greater than the number of examples, with the goal of building mathematical models that can predict targeted genetic perturbation experiments that manipulate differentiation. Sam is also interested more broadly in the intersection of inference, statistical physics, and biology.

Olivia Meyerson 

Animal behavior is both remarkably diverse and essential for survival, yet we know relatively little about the genetic basis of behavioral evolution. For example, are many genetic mutations of small effect sizes, or few mutations of large effect sizes responsible for variation in behavior? Do behaviors evolve via coding mutations, structural variants or regulatory changes? As a Biophysics graduate student in the Hoekstra lab, Olivia studies the genetic basis of behavioral evolution. Her interests lie in understanding how changes in the genome yield natural behavioral diversity. To this end, she studies the genetic basis of divergent burrowing behaviors in deer mice. Using methods in quantitative and population genetics, Olivia seeks to identify genes and mutations that have given rise to the diversity of deer mouse burrowing behaviors found in the wild. 

Bruna Paulsen

In the Arlotta lab, Bruna is working on the development of a robust long-term culture system of 3D cerebral organoids that recapitulate not only the cellular complexity, but also key aspects of the tissue architecture and circuit wiring of the endogenous human developing cerebral cortex. Ultimately, this work can contribute to a platform for understanding higher-order circuit function and dysfunction that is affected in neurodevelopmental and neuropsychiatric cortical disease.

John Russell

Yinan Shen

Cytoskeleton is composed of three components: actin, microtubule and intermediate filament. Whereas actin and microtubule is well characterized in mechanics, intermediate filament is less understood. This component is very soft compared to the other components, but it is able to greatly increase the stiffness of the cell. To study cytoskeleton mechanics, the method of reconstituting it in salt buffer has been employed for a long history. This in vitro system provides the possibility to study cytoskeleton quantitatively under well-controlled conditions. With its help, we hope to get a clear physical and mechanical picture of cytoskeleton, and thus better understand what role intermediate filament plays together with the other cytoskeleton components.

Kate Shulgina

Kate is a 4th year grad student in the Systems Biology PhD program, doing her thesis research in Sean Eddy's lab. She is interested in how alternate genetic codes evolve, in particular, how a lineage can evolve a change to the translational meaning of a codon. Since the genetic code dictates the translation of all proteins in the cell, any change is expected to disrupt the entire proteome. Kate uses computational approaches to characterize organisms that alternate genetic codes and look for patterns in their evolutionary histories.

Matthew Smith

Matt is a graduate student in the Molecules, Cells, and Organisms Ph.D. program at Harvard. His thesis work focuses on understanding how differences in the brain processing sensory information can produce significant individual differences in behavior. He is conducting this work in the lab of Benjamin de Bivort, which provides the interdisciplinary support to utilize tools from molecular biology to machine vision. Utilizing Drosophila as a model organism, they have found that animals with identical genetic backgrounds and raised in identical environments still show significant differences in the way the brain processes smells, which reflects significant differences in individual behavior.

Tzer Han Tan

Bahareh Tolooshams

Bahareh Tolooshams's research interests lie at the intersection of signal processing, machine learning, optimization, and computational neuroscience. In her research, she addresses challenges arising from the advances in neuroscience data recordings by harnessing the power of machine learning and optimization-based models. She develops mathematical tools to exploit structures underlying data and designs scalable architectures for fast and accurate analysis of data in parallel. A neuroscience application of her research is spike sorting, an essential step in analysis of neural data. She envisions a futuristic learning architecture typified by neurophysiology and data-driven models which enables neuroscientists to gain a better and deeper understanding of the brain.

Jim Valcourt

Jim Valcourt is a fifth year graduate student in the Systems Biology Ph.D. program. His work in the lab focuses on early germ layer cell fate decisions and the mechanisms and timing of lineage commitment. He received his undergraduate degree in molecular biology from Princeton in 2012, then worked at D.E. Shaw Research in New York using long-timescale computational molecular dynamics simulations to study allosteric regulation of GPCRs.

Debra Van Egeren

Debra is a fourth year Systems Biology PhD student in Franziska Michor’s lab. In collaboration with Fernando Camargo’s lab, she is trying to more precisely measure individual hematopoietic stem and progenitor cell differentiation kinetics in vivo. To do this, she is developing an experimental system capable of recording molecular histories in single cells that stores information about previous cell state as well as the time at which the cell was in that state. She also works on mathematical and computational models of cancer progression and stem cell dynamics.

Yongcheng Wang

Characterizing the transcriptome of individual cells is fundamental to understanding complex biological systems. Yongcheng is developing a new single cell RNA sequencing method that can efficiently measure the transcriptome of thousands of individual cells by using droplet microfluidics. This method could be used to characterize heterogeneous tissues, such as brain, embryo and tumor. He's also adapting this method to profile the immune repertoires of T cells and B cells. Furthermore, combined with CRISPR or transcriptional factor mediated perturbation, this method could be used to study gene functions or cell differentiation. 

Hao Wu

In nature, the chemical signals surrounding an animal can carry important information for the animal, and the concentration of these chemical cues are highly fluctuating. To study how animals utilize this type of constantly-changing cues, Hao is training mice to distinguish between two odor stimuli with the same chemical composition, but different temporal profile of concentration. From the neuronal recording of the trained mice in action, he aims to decipher how the concentration information is transformed and stored in various parts of the olfactory system and brain regions related to evidence-accumulation and decision-making. 

Jiawei Yan

Jiaweui is a theorist interested in how sophisticated behaviors emerged from simple biochemical reactions. he earned a B.S. degree in Life Sciences from Peking University, China, and joined MCO program for my PhD studies. His current research is trying to identify rules for dynamics and heterogeneity in individual cells, by applying tools from probability theory and statistical physics. Specifically, Jiawei is focusing on understanding side-effects of controlling molecular fluctuations, i.e., how reducing fluctuations in one component may affect the dynamics of other components. More broadly, he is interested in stochastic processes, control theory, complex systems, and their applications in biology.

Jeremy Yodh

Jeremy is a graduate student in physics working with Professor  L. Mahadevan.  His particular focus in the QuantBio initiative is on investigating the mechanism by which certain organisms survive water-deprived environments.  Desiccation tolerant extremophiles can survive for decades with as little as 0.1% of their total water weight. During this time, their metabolism is almost completely stalled. Upon rehydration, their metabolism recovers, and the organism resumes life as usual.  We will examine desiccation tolerance at the single-cell level in the moss, Phychomitrella patens by measuring diffusion of molecules and other dynamics within the cell, and to characterizing cellular metabolic activity; all properties will be characterized as a function of water content.  

Lu Zhang

Lu is a PhD student in the Department of Statistics. She has been developing high dimensional inference methodologies, and always held an interest in interdisciplinary research. Currently, she is working on population confounding in GWAS for admixed populations, which signify recent ancestry from two or more continents and have arisen from historical events such as the transatlantic slave trades. Confounding in admixed populations has not been fully addressed because of the complicated structures. She is applying the novel model-X based statistical approaches to this problem, exploiting the substantial knowledge about the covariates (SNPs), which has not been utilized by existing methods.