Leonardo Stari

Leonardo Stari

Specially Appointed Research Fellow at Tohoku University

Digital Biosphere Project | MEXT, Japan

About Me

Leonardo Stari

Hi, I am Leonardo (Leo) Stari

I am currently a Specially Appointed Research Fellow at Tohoku University, contributing to the "Digital Biosphere" project funded by MEXT. My research bridges the gap between experimental microbiology and computational modeling, with a focus on bioremediation and microbial community dynamics.

Originally from Santiago, Chile, I moved to Sendai, Japan, in 2016. I hold a PhD in Environmental Chemistry and possess a diverse professional background that spans from IT project engineering to wet-lab research.

Outside of the lab, I enjoy walking, swimming, and reading novels and manga. I am also an avid gamer, enjoying titles like World of Warcraft and Pokémon.

Career Timeline

2026 – Present
Specially Appointed Research Fellow (特任研究員)
Tohoku University
Apr 2026
Moved to Mei Lab (環境科学研究科)
Focus: Selenate reducing bacteria. Visit Lab Website →
April 2022 – March 2026
Assistant Professor (Research)
Tohoku University, Digital Biosphere Project
2018 – Mar 2022
Ph.D., Environmental Studies
Tohoku University
2016 – 2018
Master's degree, Environmental Engineering Technology / Environmental Technology
Tohoku University
Bioremediation of chlorinated methanes
2013 – 2016
IT Project Engineer
Novakem, Santiago, Chile
2006 – 2012
Engineer's degree, Biotechnology
Universidad de Chile
Seishin, Renewable Energies Lab. (2006-2009) | Intro. Japanese course & assistant teacher (2007-2009) | Summer school teacher | Thesis in biofuels
2004 – 2005
Bachelor, Science
Universidad de Chile
Bachelor degree, thesis in bioethics
ORCID ResearchGate LinkedIn

Skills & Languages

🌐 Languages

  • 🇪🇸 Spanish (Native)
  • 🇬🇧 English (Advanced)
  • 🇯🇵 Japanese (Advanced)
  • 🇫🇷 French (Intermediate)

💻 Technical Skills

  • Python (Deep Learning / LSTM)
  • Genomic Analysis & Bioinformatics
  • Java, Matlab
  • Experimental Design & Bioreactors
  • Illumina & Nanopore Sequencing

Research Interests

My academic path is driven by a goal to elucidate and harness microbial processes for environmental benefit. My work combines wet-lab experimentation with data-driven modeling.

Bioremediation & Genomics

I focus on the biodegradation of persistent organic pollutants. A key achievement of my doctoral work was the isolation of Pseudomonas sp. Stari2, a novel strain capable of degrading Carbon Tetrachloride (CT) under aerobic conditions.

I successfully enriched a consortium capable of degrading 30 μM CT within one week and demonstrated that Stari2 tolerates CT concentrations up to 5 mM. Utilizing joint Illumina/Nanopore sequencing, I identified specific dehalogenase enzymes and metabolic pathways essential for these strategies.

Microbial Ecology & Deep Learning

To bridge the gap between isolate characterization and ecosystem function, I study how microbial populations assemble. In the "Digital Biosphere" project, I apply deep learning techniques—specifically LSTM (Long Short-Term Memory) networks—to predict community succession.

Using high-resolution time-series data (522 samples), our models have achieved over 90% accuracy in forecasting OTU profiles. We discovered that carbon sources act as deterministic filters and that the "Rare Biosphere" follows distinct successional trajectories compared to abundant taxa.

Latest Publication

📢 NEW

Carbon Source Acts as a Deterministic Filter Shaping Microbial Succession and Rare-Abundant Decoupling in Soil Bacterial Communities

View Paper →

ISME Communications | Published: April 20, 2026 | DOI: 10.1093/ismeco/ycag108

We investigated how chemically diverse carbon sources act as ecological filters shaping soil bacterial communities. Null model analysis confirmed the carbon source as the primary deterministic filter, enforcing high reproducibility (homogeneous selection governing ~74% of assembly among replicates) and overriding stochastic effects. Crucially, abundant (>1%) and rare (<0.1%) taxa exhibited decoupled assembly mechanisms — while abundant taxa were driven by dispersal limitation (~59%) and variable selection, the rare biosphere displayed a temporal regime shift, transitioning from stochastic isolation to strong deterministic selection (~50%) during later successional stages. This reframes the rare biosphere as a "latent responder" reservoir recruited by metabolic byproducts rather than the primary substrate.

Research Metrics

Citations
23
h-index
3
Publications
8

Metrics based on Scopus / Google Scholar data. Updated via Python script.

Publications

Contact

Feel free to reach out for collaborations or inquiries!

lstari@tohoku.ac.jp

Alternative Email