About
About Fitila Labs
Our goal is to shorten the time it takes for scientific research to become software that engineers and scientists use in their daily work.
Fitila Labs is a research and software company in Chicago's Fulton Market District. It was founded by Babajide (Jide) Kolade, Ph.D., PE, who previously built simulation and data systems at Gamma Technologies, ConocoPhillips and the Gas Technology Institute. He holds a Ph.D. in mechanical engineering from Stanford and chaired the ASME subcommittee on verification, validation and uncertainty quantification of machine learning.
Our team includes applied mathematicians, mechanical and civil engineers, and data scientists. We work on data engineering, simulation, machine learning and decision analysis, and we deliver that work through three product lines: TerraNavitas for energy and Earth resources, Curasynth for drug discovery, and Fitila Agents for science and engineering.
Values
- Rigor
- We publish results we have verified and state what we have not tested.
- Usefulness
- We build for the engineers and scientists who are accountable for a decision.
- Focus
- We announce a capability once it works in production or in tests we can show.
Recognition and programs
- U.S. Department of Energy SBIR Phase I (completed)
- NVIDIA Inception member
- ASME standards subcommittee on verification, validation and uncertainty quantification of machine learning (founder, chair)
Principles
- 01
Physics first
We use a learned model only where it has been tested against simulation or measured data, and we state the range in which it holds.
- 02
Verification
We test each solver against analytic solutions and published benchmarks before applying it to new problems.
- 03
Traceable results
Each result records its inputs, its data sources and the software version that produced it, so that it can be reproduced.
Team
Our team of applied mathematicians, engineers and data scientists works in the Fulton Market District, Chicago.
Babajide Kolade, Ph.D., PE
Founder and Technical Director
Simulation, verification and AI for energy systems; Stanford Ph.D. in mechanical engineering.
Keneth M. Kwayu, Ph.D.
Senior Data Scientist
Geospatial AI, machine vision and large-scale data pipelines.
Yemisi Popoola
Cloud DevOps Engineer
Cloud infrastructure, data pipelines and delivery automation.
Akshara Subramaniasivam
Data Scientist
Statistical modeling, graph data and optimization.
Chengbin Zhu, Ph.D.
Data Scientist
Numerical analysis, optimization and geospatial machine learning.
Amal Chebbi, Ph.D.
Data Scientist
Machine learning, control and language models for energy and industry.
Fatou K. Ndow, Ph.D.
Bioinformatics Researcher
Bioinformatics and mathematical modeling of biological systems.
Zirui Li, Ph.D.
Postdoctoral Research Fellow
Statistical learning, uncertainty quantification and numerical methods for PDEs.