Hello, my name is Mialy (my-lee), I’m a Floridian by birth, a Californian at heart, Seattle based.
My career has evolved from hands-on research to the intersection of data and technology. I began as a research assistant at Stanford, focusing on experimental techniques and data analysis. Over time, I transitioned from a nearly purely experimental role to more collaborative computational modeling and software engineering, working extensively in Python to develop and implement complex models.
Currently, I’m a Technical Product Manager and Data Scientist at Promoted,ai, a startup specializing in using AI to enhance search rank optimization for marketplace companies. I work closely with in-house teams to integrate their systems with ours allowing us to apply advanced AI technologies to improve user experiences. A key part of my role involves communicating customer needs to our engineering team, ensuring our solutions are tailored to meet specific client requirements and drive better search outcomes. I enjoy combining technical skills with strategic thinking to create impactful products.
Before this role, I served as a Research Software Engineering Tech Lead across both front and back end FAIR data products at Sage Bionetworks. My focus was on developing tools for open science and collaboration, including user-friendly schema visualization tools to simplify complex data models.
I hold a Ph.D. in Bioengineering from Stanford University, a master’s in Biology from the University of Rochester, and a bachelor’s in Microbiology from the University of Florida. This academic background laid a strong foundation for my transition into data science and product management.
I’m passionate about turning complex tech into practical solutions and working closely with stakeholders to achieve their goals.
Education
2015- 2021
Ph.D. Bioengineering, Stanford University, Stanford, California
My thesis work, in Markus Covert's lab, was an experimental and computational exploration of the role of operon structure in ensuring the co-expression of sub-generationally expressed genes. I worked with both the the whole-cell modeling and live-cell imaging teams in the lab.
2009-2012
M.S. in Biology, University of Rochester, Rochester, New York
My research within the Culver lab consisted of determining the roles of cis- and trans- acting factors involved in 30S small subunit biogenesis. To study the role of the externally and internally transcribed regions of 16S rRNA I developed a screen and selection system, to easily determine nucleotides within these regions that can affect 30S formation. In addition, I studied the role that RimP, a ribosome biogenesis factor, plays in the formation of a mature ribosomal particle.
2005-2008
B.S. in Microbiology and Cell Science, University of Florida, Gainesville, Florida
Work Experience
May 2024-Present
Technical Product Manager | Data Scientist, Promoted.ai
At Promoted.ai, I work closely with enterprise customers to understand their goals and technical needs, helping them balance revenue optimization with relevance to create a better user experience. I design and implement complex changes, run A/B tests on search ranking algorithms, and tackle a wide range of search and discovery challenges. A large part of my role is setting up, running, and debugging experiments to drive meaningful, data-driven improvements.
Feb 2024-May2024
Senior Research Software Engineer, Sage Bionetworks
Jun 2021 - Feb 2024
Research Software Engineer, Sage Bionetworks
At Sage Bionetworks I work as Tech Lead on FAIR data front and back end products (Schematic, Data Curator App, and Data Flow Apps). Our tools enable data sharing and collaboration among large research projects by allowing easy data modeling (using a CSV interface), metadata validation and ingress. Our goal is to make products that are scalable, reusable, and generalizable to be used across many projects.
April 2020-Nov 2020
Mathematical Modeling Extern, BridgeBio
Worked to make computational models of drug target pathways, for portfolio drugs.
Nov 2019-Aug 2020
Consultant, Evil Genius Llc.
Probe IBM Watson Treatment Pathways data sets to discover insights and provide interactive and animated data visualizations for communication with investors.
2013-2015
Research Assistant, Stanford University, Covert Lab
My project focused on understanding the role of NF-kB dynamics in single cells in response to stimuli.
Skills
Computational
Python
Pandas/Numpy
Data Modeling
Data Analysis
SQL
Amazon Athena
NetworkX
Version Control (Git)
Unit Testing
Data Visualization (observable, D3, seaborn, matplolib, bokeh…)
Bash Scripting
Image Analysis
Cloud Computing (AWS/Google)
Project Management Tools (Jira, Monday)
Experimental
Live single-cell microscopy (E. coli, mammalian cells)
Mother machine
Cloning (E. coli, mammalian)
Tissue Culture
RNA Sequencing
sm-RNA FISH, immuno-histo chemistry
Papers
Sun, Gwanggyu*, DeFelice, Mialy* Gillies, Taryn & Ahn-Horst, Travis & Andrews, Cecelia & Krummenacker, Markus & Karp, Peter & Morrison, Jerry & Covert, Markus. (2024). Cross-evaluation of E. coli’s operon structures via a whole-cell model suggests alternative cellular benefits for low- versus high-expressing operons. Cell Systems. 15. 10.1016/j.cels.2024.02.002.
Derek N. Macklin*, Travis A. Ahn-Horst*, Heejo Choi*, Nicholas A. Ruggero*, Javier Carrera*, John C. Mason*, Gwanggyu Sun, Eran Agmon, Mialy M. DeFelice, Inbal Maayan, Keara Lane, Ryan K. Spangler, Taryn E. Gillies, Morgan L. Paull, Sajia Akhter, Samuel R. Bray, Daniel S. Weaver, Ingrid M. Keseler, Peter D. Karp, Jerry H. Morrison, Markus W. Covert†*"Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation"*. 24 July 2020, Science 369, eaav3751. DOI: 10.1126/science.aav3751
DeFelice, M.*, Clark, H.*, Hughey, J.*, Maayan, I., Kudo, T., Gutschow, M., Covert, M., and Regot, S. "NF-κB signaling dynamics is controlled by a dose-sensing autoregulatory loop". Science Signaling 12, April 30, 2019. eaau3568. DOI: 10.1126/scisignal.aau3568
Lane K*, Van Valen D*, DeFelice MM, Macklin DN, Kudo T, Jaimovich A, Carr A, Meyer T, Pe'er D, Boutet SC, Covert MW, "Measuring signaling and RNA-Seq in the same cell links gene expression to dynamic patterns of NF-kappa B activation". Cell Systems. April 26, 2017. doi: 10.1016/j.cels. 2017.03.010
Van Valen D, Kudo T, Lane K, Macklin DN, Quach N, DeFelice M, Maayan I, Tanouchi Y, Ashley E, Covert MW, "Deep learning automates the quantitative analysis of individual cells in live-cell imaging experiments". PLOS Computational Biology. November 4, 2016. doi: 10.1371/journal.pcbi.1005177
*Authors contributed equally
Honors & Community Engagement
Sibel Scholars Fellowship Class of 2020
Graduate student mentor to First Generation/Low Income Undergraduate Students 2015-2019
McKinsey Stanford Case Competition—3rd Place 2016
Presentations/Posters
April 2019 Stanford Bug Club Seminar -- Talk
“Is operon Structure required for co-expression of sub-generationally expressed genes?”
March 2019 The Paul G. Allen Frontiers Group Site Visit, Allen Discovery Center at Stanford University -- Poster session
“Why do operons persist? Making the case that operon structure enables bet-bet-heating for population survival in fluctuating environments”
January 2019 Gordon Research Conference, Ventura, CA. Stochastic Physics in Biology -- Poster Session
“Why do operons persist? Making the case that operon structure enables bet-bet-heating for population survival in fluctuating environments”
October 2018 Stanford Bioengineering Department Retreat -- Poster Session
“Why do operons persist? Making the case that operon structure enables bet-bet-heating for population survival in fluctuating environments”
May 2018 Stanford Center for Systems Biology Weekly Meeting -- Talk
“Why do operons persist? Making the case that operon structure enables bet-bet-heating for population survival in fluctuating environments”
February 2017 Stanford Bioengineering Department Retreat -- Poster Session
“Exploring the role of acute tolerance in NF-κB signaling dynamics”