Computational biology research, mathematical modeling & software development

I’m an experienced software engineer with a background in applied mathematics & computer science. My current research focuses mostly on biological applications (phylogenetics, viral fitness modeling, protein modeling). In addition to computational modeling, I also have synthetic biology wet lab training in the basic fundamentals. I’m currently based in Berlin 🇩🇪 but spend some portion of the year in the NYC area 🇺🇸 where I’m from.

📚 Formal education: B.Sc., MIT: Mathematics & Computer Science, [Current] M.Sc. student, Freie Universität Berlin: Mathematics (biological applications focus)

Starting PhD in computational biology at Max Delbrück Center for Molecular Medicine in Berlin in fall 2024.

🧬 Current work & projects:

  • Master’s thesis research (computational): research assistant at the Max Planck Institute for Molecular Genetics, Vingron lab (computational molecular biology dept)

    • DMSim: In silico simulation of deep mutational scanning data for SARS-CoV-2 spike protein receptor-binding domain (RBD) to predict the mutation effects with respect to two phenotypes of amino acid mutations within the SARS-CoV-2 spike protein receptor-binding domain (RBD). Fine-tunes the Evolutionary Scale Model 2 (ESM-2) protein language model (pLM) using Hugging Face.

  • Global Teaching Assistant for MIT Media Lab’s Synthetic Biology course “How To Grow Almost Anything”, spring semester 2023 & 2024 where we work on projects spanning computational protein design of MS2 phage lysis protein mutants to be synthesized by Twist Biosciences and tested for structural integrity using Nuclera, bioproduction of biopigment (lycopene & beta-carotene expressed in E. coli), lab automation using OpenTrons robots, biosafety & more.

⌛️ Some previous work includes: software development at SoundCloud, research at MIT Media Lab (Moca/SanaMobile: telemedicine system deployed in developing countries), Hochschule Darmstadt part-time university lecturer for a machine learning elective, Udacity educator/course developer (CoreML course), and other collaborations with academia (e.g. high energy physics - CERN). Recent freelance projects span Kindred a thoughtful network for home sharing based on reciprocity & trust, computer vision/ML-driven app custom eyewear app Topology eyewear, & on-device audio processing/transcription for Clefer.

🌈 Other interests include various sports (cycling, hiking, skateboarding), funk & disco music, piano, discussing ideas across the ideological spectrum (e.g. InterIntellect), cooking vegetarian food, & more.

Recently completed

Molecular networks

Mathematical modeling of metabolism in genome-scale reconstructions of metabolic networks. Flux balance analysis (FBA), flux variability analysis (FVA), flux coupling analysis (FCA), and other industry standard techniques that span static, iterative, and dynamic modeling approaches both with and without gene regulation using programming tools such as cobraPy, coBAMP, and efmtool.

Polymer biophysics

Multiscale modeling of biopolymers. Literature survey of the modeling the fascinating hierarchical structure of structurally strong biomaterials which are composed of a small number of structurally weak building blocks at the atomistic scale. A case study of silk, a biomimetic ideal, was explored more in depth. [paper, slides]

Mathematics of complex social systems

Performed various analyses (e.g sensitivity analyses) on the complex output dataset of the Mobility Transition Model (MoTMo) agent-based model that was developed for a decision theatre in the Global Climate Forum to aid policy-makers on which interventions could be most effective with respect to mobility choices and greenhouse gas emissions. My work with another Freie Universität colleague, Mónica Soto was awarded 1st place by the Einstein Stiftung in the Thematic Einstein Semester dataset challenge culminating in September 2022 (condensed version) .

Biochemical reaction network modeling (gene regulatory networks)

  • Seminar project #1 dynamical systems & graph theory POV: Survey of research showing the equivalence of modeling gene regulatory networks (e.g. in cell differentiation) as feedback vertex sets from graph theory and determining nodes from dynamical systems. Underscores the utility of modeling a problem from multiple perspectives so that subfields can mutually benefit from each other’s gains.

  • Seminar project #2 computational dynamics & stochastic POV: Paper & presentation highlighting how chemical reaction networks are modeled using the chemical master equation (CME), difficulty of finding solutions to the CME, tools for indirectly solving the CME (e.g. Gillespie’s algorithm/ SSA), and Python implementation of Gillepie’s algorithm/SSA with a genetic toggle switch example.

Nonlinear Dynamics: Population dynamics

  • Review of mathematical modeling & analysis of dynamics of Nicholson’s Blowfly Equations for seminar (see presentation slides)

  • Comparative analysis of compartmental disease models (SIR, SEIRS, etc) for seminar

Climate modeling

  • Literature survey, research reproduction & iteration on current research [1][2][3][4] on “Vegetation ecosystems as low-order dynamical systems: Assessing the resilience of the tropical rainforests to deforestation and global warming”

  • key topics: energy balance models, stochastic differential equations

Quantum Computational Methods

  • Literature survey culminating in seminar presentation & paper on the overview of Computational Complexity of Density Functional Theory (electronic structure problems in computational chemistry)