CSB 2023 Retreat


Sunday, Oct 8, 2023 to Monday, Oct 9, 2023


8:30 am to 1:30 pm


140 Ocean Avenue

Kennebunkport, ME. 04046

(800) 552-2363


Event Description: 

The Computational and Systems Biology Ph.D. Program will hold our annual retreat at the Colony Hotel in picturesque Kennebunkport, ME. Sunday, October 8th - Monday, October 9th 2023. Our retreat will feature a poster session, lobster buffet, and talks from CSB students, MIT Faculty, and invited industry speakers.

Our Career Panel is Monday from 10:45 am - 11:45 am and will feature: Dr. Kathy Lin( Dyno Therapeutics), Dr. Alex Drong (Rome Therapeutics), Dr. Amy Moody (Pfizer), Prof. Olivia Corradin (MIT Biology), and Prof. Connor Coley (MIT Chemical Engineering).

We are pleased to announce our lineup of speakers:

Guest Speakers : 

Sunday, October 8, 2023, 11:15-11:45 AM

Prof. Katie Galloway, MIT Chemical Engineering Department

Talk Title: "Engineering high-precision genetic control systems for cellular reprogramming"

Bio: Katie Galloway is the W. M. Keck Career Development Professor in Biomedical Engineering and Chemical Engineering at Massachusetts Institute of Technology (MIT). Galloway earned a Ph.D. and an MS in Chemical Engineering from the California Institute of Technology (Caltech), and a BS in Chemical Engineering from the University of California at Berkeley. She completed her postdoctoral work at the University of Southern California. Her research has been featured in Science, Cell Stem Cell, Cell Systems, and Development. She has won multiple fellowships and awards including the NIH Maximizing Investigators' Research Award (MIRA) R35, the NIH F32, and Caltech’s Everhart Award.


Sunday, October 8, 2023, 11:45 am -12:15 pm

Prof. Bin Zhang, MIT Chemistry Department

Talk Title: "Nuclear Zoning as a Model for Genome Function"

Bio: Bin Zhang attended the University of Science and Technology of China (USTC) as a chemical physics major. After graduating from USTC in 2007, Bin moved to the United States to pursue doctoral research at the California Institute of Technology in Thomas Miller’s group. Upon graduation, Bin accepted a position as a postdoctoral scholar with Peter G. Wolynes at the Center for Theoretical Biological Physics at Rice University. Bin joined MIT faculty as an assistant professor in 2016. His research focuses on studying three-dimensional genome organization with interdisciplinary approaches that combine bioinformatics analysis, computational modeling and statistical mechanical theory. While at MIT, Bin has received awards that include the Scialog Fellowship and the NSF CAREER Award.

Sunday, October 8, 202, 1:30 - 2:00 pm

Dr. Kathy Lin, Dyno Therapeutics, Head of Product Development, CSB Alum

Talk Title: "Machine-guided design of novel improved AAV capsids for gene therapy delivery"

Bio: Kathy studied biology and computer science at Harvard from 2010 to 2014. She received her Ph.D. from the MIT CSB Ph.D. Program in 2019. During her Ph.D., she worked on using machine learning to predict biochemical properties and targeting efficacy of AGO-miRNA complexes in the lab of David Bartel. Since 2019, Dr. Lin has been at Dyno Therapeutics and is currently head of product development.

Abstract: AAV capsids are the most widely-used viral vector for delivering gene therapy and have been successfully deployed as delivery vehicles in several FDA-approved therapies. However, naturally-occuring AAV serotypes have several drawbacks that severely limit their utility for most indications that could benefit from gene therapy. These include the lack of tissue and/or cell-type specificity, propensity for off-target effects, and high manufacturing costs. Dyno is focused on engineering novel AAV capsids with improved properties along multiple dimensions by closing the loop between high-throughput data generation and ML-guided capsid engineering. I'll be walking through our general strategy, as well as vignettes on computational approaches we've developed to solve specific problems.


Sunday, October 8, 2023, 2:00 -2:30 pm

Dr. Alex Drong, Rome Therapeutics; Director, Data Science

Talk Title: "Mechanism-guided quantification of LINE-1 reveals p53 regulation of both retrotransposition and transcription"

Bio: Alex has a Ph.D. in Genomic Medicine and Statistics from the Wellcome Trust Centre at the University of Oxford, where he worked on integrating RNAseq, Epigenetic, and Genome-wide association data. He then continued his scientific journey as an MRC Skills Development Fellow at the Big Data Institute in Oxford and Columbia University in New York. After a short stint at Regeneron's Data Science and Molecular Profiling group, he became a team lead at Oxford Nanopore, where he led a team of bioinformaticians developing new applications for long-read sequencing, such as single-cell isoform detection. He is the Director of Data Science for Method Development and Sequencing Tech at ROME, applying his long and short read and drug development skills to explore the repeatome. 

Abstract: Somatic activity of LINE-1 (L1) mobile elements has been implicated in cancer etiology, which may be related to the loss of p53-mediated regulation as a result of TP53 mutations. Quantifying the mechanisms of L1 regulation in cancer has been challenging. Here, we build a statistical model of L1 regulation by simultaneously quantifying L1 retrotransposition, L1 expression, and the fitness costs of mutated TP53 with precision. We first developed Total ReCall, an algorithm specifically tailored to the mechanisms of L1 reintegration, to detect L1 insertions from short-read whole-genome sequencing. Applying Total ReCall to high-quality data consisting of >750 paired tumor and normal samples from The Cancer Genome Atlas (TCGA) shows high L1 insertion heterogeneity among tumor types, with increased retrotransposition burden in lung squamous cell carcinoma, head and neck, and colon cancers. We next assessed the active RNA expression of intact L1 in >9,000 TCGA tumor samples, establishing, for the first time, a clear correlation between L1 expression and retrotransposition. Finally, we integrated the number of L1 insertions, L1 expression and a mathematical model of TP53 fitness into a multi-modal model of p53- mediated mechanisms of L1 regulation. We show that TP53 mutations enable retrotransposition both by disinhibiting L1 expression and enabling its reintegration and quantify the relative weights of this dual regulatory role. We demonstrate how mechanism-based multi-modal modeling applied at scale can statistically disentangle the complex interplay between canonical driver events in tumor evolution and retrotransposon activity.


Sunday, October 8, 2023, 5:00 -5:30 pm

Dr. Amy Moody, Pfizer, Senior Principal Scientist, Translational Modeling and Simulation Group

Talk Title: " Quantitative Model-Based Assessment of Multiple Sickel Cell Disease Therapeutic Approaches Alone and in Combination"

Bio: Amy Moody is a senior principal scientist in the Translational Modeling and Simulation group at Pfizer supporting small molecule programs during pre-clinical development. She uses a combination of modeling approaches, from simple empirical PK-PD to highly mechanistic quantitative systems pharmacology models, to predict the safe and effective drug dose for first in human clinical studies. Key to this process, she assesses the biologic pathway to determine the required extent and duration of target coverage and relates target modulation to biomarkers and clinical endpoints.

She began her scientific career as an experimentalist and completed her PhD studying the role of ion channels in cancer progression at Tufts University. She then transitioned to modeling during her post-doc advised by Bree Aldridge at Tufts University and Suzanne Gaudet at Dana Farber Cancer Institute with support from the Lab of Systems Pharmacology at Harvard Medical School. Her post-doc project involved investigating macrophage immune signaling dynamics using a combination of experimental and modeling approaches. Her post-doc provided a key opportunity to gain computational skills which enabled her to transition out of the lab and take a full-time modeler position at Pfizer.

Abstract: In sickle cell disease (SCD) red blood cell sickling is driven by concentration dependent polymerization of mutation-carrying deoxygenated hemoglobin (deoxHbS). Three strategies, inducing HbF, stabilizing oxygenated hemoglobin (oxyHbS), and lowering 2,3-BPG similarly aim to reduce deoxHbS. To predict the required level of target modulation, we extended the Monod-Wymann-Changeux (MWC) oxygen saturation model to include hemoglobin binding to 2,3-BPG and oxyHbS stabilizers and added an additional species to represent HbF. The model allows simulation of varying levels of oxyHbS stabilizer occupancy,  2,3-BPG lowering, or HbF intervention alone or in combination to calculate the deoxHbS concentration at oxygen tensions found in peripheral tissue and assess polymerization protection.


Sunday, October 8, 2023 5:30- 6:00 pm

Dr. Gevorg Grigoryan, Generate Biomedicines, Co-Founder and Chief Technology Officer

Talk Title: "Illuminating protein space with a programmable generative model"

Bio: Gevorg Grigoryan, PhD, is a co-founder and chief technical officer at Generate Biomedicines. He is also a research associate professor of computer science, biological sciences, and chemistry at Dartmouth College. He received two bachelor’s degrees, in computer science and biochemistry, and went on to obtain a PhD from the Massachusetts Institute of Technology, where he studied computational protein design and modeling of protein interactions. After completing his postdoctoral work at the University of Pennsylvania in 2011, Gevorg was appointed to the faculty at Dartmouth, where he obtained tenure in 2017.

Prior to co-founding Generate Biomedicines, Gevorg’s research at Dartmouth focused on understanding the relationship between amino-acid sequence and structure, seeking rigorous ways of inferring principles governing protein folding, interaction, and function from data. The powerful ideas that were discovered suggested a fundamentally new and promising paradigm for the design of macro-molecules that was based on general principles inferred from data. Armed with this new and powerful understanding, Gevorg envisioned the possibility of a company that uses the breakthrough of data-driven protein design, powered by Machine Learning, to transform therapeutic discovery towards a faster, more precise, and less expensive endeavor. Collaborating with colleagues at Flagship Pioneering brought this vision into reality, leading to the founding of Generate Biomedicines. The most enjoyable part of Gevorg’s role as the founding Chief Technology Officer at Generate has been to work with incredibly talented scientist on some of the world’s most challenging problems in molecular and therapeutic science.

Gevorg has authored over 50 peer-reviewed papers, including in Nature, Science, PNAS, and other top journals and conferences, and his work has received awards and recognition from the Alfred P. Sloan Foundation, the National Institutes of Health, the National Science Foundation, and the American Cancer Society.

Abstract: Three billion years of evolution have produced a tremendous diversity of protein molecules, and yet the full potential of this molecular class is likely far greater. Accessing this potential has been challenging for computation and experiments because the space of possible protein molecules is much larger than the space of those likely to host function. We recently introduced Chroma, a generative model for proteins and protein complexes that can directly sample novel protein structures and sequences and that can be conditioned to steer the generative process towards desired properties and functions. This talk will briefly discuss the technical underpinnings of the method and illustrate some of its applications, arguing that we are entering an age where design of functional proteins becomes increasingly routine. The question before the field now is what we will we do with this capability.


 Monday, October 9, 2023,  9:30 - 10:00 am

Prof. Connor Coley, MIT Chemical Engineering Department

Talk Title: " Designing, evaluating, and synthesizing new molecules with the help of AI"

Bio: Connor received his B.S. in Chemical Engineering from Caltech and his Ph.D. in Chemical Engineering MIT. His research interests are in how data science and laboratory automation can be used to streamline discovery in the chemical sciences.


Monday, October 9, 2023,  10:00-10:30 am

Prof. Olivia Corradin, MIT Biology Department

Talk Title: "Pathogenic dysregulation of transcriptional enhancer elements"

Bio: Olivia Corradin was appointed as a Whitehead Member and Assistant Professor at MIT in 2021. She began her independent career in 2016 through the Whitehead Institute Fellows program. Prior to that, Olivia completed her PhD at Case Western Reserve University under the mentorship of Dr. Peter Scacheri. The Corradin Lab investigates genetic and epigenetic variation that contribute to diverse human diseases including multiple sclerosis and opioid use disorder.


Student Speakers & Posters: 

Sunday, October 8, 2023, 7:30-7:45 pm

Cameron Flower

Research Advisor:  Prof. Forest White

Talk Title:"Mapping the early signaling and transcriptional dynamics of oncoprotein inhibition"

BioCam is a PhD candidate in CSB at MIT under the supervision of Forest White, located at the Koch Institute for Integrative Cancer Research. In the White Lab, Cam studies the cellular signaling networks that dictate response to anti-cancer targeted therapies, making heavy use of mass spectrometry-based proteomics and computational modeling. He was a recipient of a graduate fellowship from the MIT Ludwig Center in 2021 and 2022 and will begin a postdoc in 2024 at the Dana-Farber Cancer Institute.


Sunday, October 8, 2023, 7:45 - 8:00 pm

Sam Goldman

Research Advisor: Prof. Connor Coley 

Talk Title:  “Learning to break bonds and discover metabolites”

Bio: Sam is a 5th year PhD student at MIT in CSB and is advised by Professor Connor Coley. His research focuses on elucidating small molecule metabolites from mass spectrometry data. Sam is also interested in biotech entrepreneurship and has served as Co-President of the MIT Biotech Group and as a Co-Managing Director of Nucleate Eco, a student-led non-profit, where Sam’s particular focus was creating programming for trainees to start biotechnology companies addressing climate change. Prior to MIT, Sam studied computer science at Harvard where he conducted research with Philippe Cluzel in systems biology and also competed on Harvard’s NCAA wrestling team for four years.


Sunday, October 8, 2023,  8:00 - 8:15 pm

Matt Leventhal 

Research Advisor: Prof. Ernest Fraenkel

Talk Title: “Network integration of genetic risk factors of Alzheimer’s disease and neurodegeneration uncovers mechanisms of age-associated neurodegeneration”

Bio: Matt Leventhal is a fifth-year CSB PhD candidate advised by Ernest Fraenkel. Before his PhD, Matt double majored in mathematics and biology at Bowdoin College, and then worked with Ben Ebert and Gad Getz at the Broad Institute as a computational associate at the Broad Institute. His thesis research utilizes computational network models to understand the functional impact of genetic variations in neurodegenerative diseases including Alzheimer's disease and Huntington's disease. 


Sunday, October 8, 2023, 8:15 - 8:30 pm

Christopher Rodriguez

Research Advisor: Prof. Peter Reddien

Talk Title: "Exploring the Limits of Longevity"

Bio: Christopher Rodriguez is a fifth-year PhD candidate in the Reddien Lab. He is interested in evaluating claims of agelessness in planarians and other highly regenerative organisms. His talk will focus on what mathematical models of the evolution of aging can tell us about the limits of evolved lifespan. 


Poster session: Sunday, October 8, 2023,  8:30 - 10:30 pm

Student                             Year                       Lab                              Poster Title

Athreya, Advait


Bin Zhang

“Epigenetic regulation of chromatin phase separation”

Burgos, Emanuel



Chris Smillie

“Development of Computational Methods for Analyzing Bacterial single-cell RNA-Seq”

DeWeirdt, Peter



Michael Laub

"Leveraging Machine Learning to Unearth Undiscovered Prokaryotic Defense Systems"

Keys, Allison



Heather Kulik/Laura Kiessling

“Elucidating the Energetic Landscape of CH-π Interactions in Protein-Carbohydrate Binding”

Kozareva, Velina



Ernest Fraenkel

 "Integrative network analysis identifies key pathways contributing to neuronal degeneration after TDP-43 loss in ALS"

LeNail, Alexander



Myriam Heiman

"Transcription Factor Gene Therapies to Reverse Neurodegeneration"

Leventhal, Matthew


Ernest Fraenkel

“Network integration of genetic risk factors of Alzheimer’s disease and neurodegeneration uncovers mechanisms of age-associated neurodegeneration” 

Litz, Mackenzie



Pulin Li

“Mesenchyme Cell signaling and the branching lung “

Liu, Ivy



Alex Shalek

 “Single-cell profiling of tuberculosis-infected human lung”

Maher, Kamal



Xiao Wang

“Spectral decomposition of spatial omics data”

Owen, Erik


David Page

“Menopause or Just Aging?: Identification of ovarian expression patterns more informative of follicle status than age status”

Pagane, Nicole



Harikesh Wong

 “Tissue-specific optimization of T cell control in draining lymph nodes”

Prabhu, Gautam



Peter Reddien

"Dynamic Pattern Formation during Planarian Regeneration"

Shen, Anne



Eric Alm

 “Finding novel loci associated with human mannose-binding lectin (MBL) binding capability in Ligilactobacillus salivarius through a microbial genome-wide association study (mGWAS)”

Sundar, Vikram



Kevin Esvelt

“FLIGHTED: Inferring Fitness Landscapes from High-Throughput Experimental Data”

Torillo, Paul



Tami Lieberman

“Reversions mask the contribution of adaptive evolution in microbiomes”

Tseo, Yitong



Ian Hunter

“Novel Biohybrid Actuator Scaffolded from Dead Myocytes"