cv

Basics

Name Tiernan Kennedy
Label PhD Candidate in Computer Science and Engineering
Email tiernan7@cs.washington.edu
Summary PhD candidate in Computer Science and Engineering with a strong foundation in chemistry and computational modeling. Experienced in molecular programming, sequence design, advanced experimental design, and interdisciplinary research. Seeking opportunities to advance impact of molecular programming through robust design and engineering foundations.

Work

  • 2024.05 - 2024.09
    Assay Optimization Intern
    Global Health Labs Inc.
    Developed predictive models and novel assays for LAMP production kinetics.
    • Developed a computationally tractable surrogate for predictive modeling of production kinetics in loop mediated isothermal amplification (LAMP)
    • Engineered and optimized a novel ELISA assay for validating the surrogate model
  • 2021.08 - Present
    Research Assistant
    University of Washington, Thachuk Lab
    Conducting research on DNA strand displacement circuits, non-standard base-pairs, and kinetic optimization.
    • Systematically optimized leakless DNA circuits using sequence-level motifs to improve reaction kinetics without compromising robustness
    • Pioneered the incorporation of non-standard Hachimoji base-pairs into strand displacement reactions to improve operational fidelity
    • Assisted in micro-kinetic optimization of strand displacement reactions for DNA:RNA hybrids
  • 2020.03 - 2020.10
    Summer Research Fellow
    Caltech, Rothemund Lab
    Developed coarse-grained force-fields for molecular dynamics studies.
    • Developed and tested a coarse-grained force-field for molecular dynamics studies of emergent behavior in microtubules in DNA-based active liquids
  • 2019.05 - 2019.08
    Research Intern
    Waters Corporation, Accelerated Research Division
    Evaluated novel multi-dimensional liquid chromatography instrumentation.
    • Independently evaluated novel multi-dimensional liquid chromatography instrumentation
    • Designed protocols for detecting USP-relevant targets and advanced a new project to next R&D project stages
  • 2018.01 - 2021.05
    Undergraduate Research Assistant
    UMass Amherst, Thompson Lab
    Developed DNA-scaffolded assemblies of bacterial protein complexes.
    • Developed DNA-scaffolded assemblies of bacterial protein complexes; designed and analyzed experiments
    • Led aspects of project design and data analysis, contributing original direction for future work

Education

  • 2021.01 - 2023.06

    Seattle, Washington

    M.S.
    University of Washington
    Computer Science
  • 2021.01 - Present

    Seattle, Washington

    PhD
    University of Washington
    Computer Science and Engineering
  • 2017.01 - 2021.05

    Amherst, Massachusetts

    B.S.
    University of Massachusetts, Amherst
    Chemistry, Minor: Mathematics, Certificate: Biomedicine
    • Integrated Concentrations in Science Program (Biomedicine Track)
    • Commonwealth Honors College, Multidisciplinary Honors, Summa cum laude

Awards

Publications

Skills

Programming
Python
C++
Java
R
LaTeX
Biochemical
Gel electrophoresis
Protein purification and analysis assays
RNA production
Computational
DNA sequence design
Molecular dynamics simulation
Nucleic acid thermodynamic analysis (NuPack)
Image analysis and quantification
High-performance computing
Analytical
Single/multidimensional chromatography
LC-MS
Modeling
Optimal design of experiments
Model discovery
Classical and neural models for kinetic simulation
Inference with uncertainty estimation
Automation
Custom scientific software development
ECHO Acoustic Liquid Handler expert
Industrial scale Hamilton liquid handling robots
Iterative model-based design and experimentation

Languages

English
Native speaker

Interests

Molecular Programming
DNA computing
Strand displacement circuits
Non-standard base-pairs
Computational Modeling
Kinetic optimization
Experimental design
Model discovery

Projects

  • 2021.08 - Present
    Fast and Robust DNA Circuits
    Systematically optimized DNA circuits using sequence-level motifs to improve reaction kinetics without compromising robustness.
    • Improved operational fidelity
    • Enhanced kinetic reliability
  • - Present
    Non-standard Bases for Strand Displacement
    Pioneered incorporation of non-standard Hachimoji base-pairs into strand displacement reactions for improved performance in complex environments.
    • Improved operational fidelity
    • Maintained kinetic reliability with interfering background nucleic acids
  • - Present
    Energy landscape engineering for DNA:RNA hybrid nanotechnology
    Previous research has shown that the binding energy for DNA:RNA hybrids is highly dependent on sequence composition. I contributed to work that uses sequence-level motifs in DNA:RNA hybrid circuits to maintain fast kientics regardless of sequence composition
    • Improved kinetics in DNA:RNA hyrbids
    • Systematic optimization with sequence motifs
  • - Present
    Reaction network optimization for dynamic nanotechnology
    While much previous research has focused on improving primitives and motifs for achieving particular outcomes in nucleic acid nanotechnology, this work focuses on imprving fidelity by changign the structure of the reaction netowrk itself.
    • Reaction network optimization
    • Improving single nucleotide variant descrimination
  • - Present
    Model based desing of expeiments for optimizing molecular computing
    I have previously worked on strategies that operate at the level of molecules or reactions. This work, in constrast, shows how we can leverage models of systematic archectectures to target performance metric and robusetness by optimizing design of expeirments
    • Applying robust model based design of expriments to molecular computing
    • Transationing DNA nanotechnology to a robust engineering technology