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SKA Labs is a research and development business focused on computational sensing, simulation, and uncertainty-aware inference. The company is built around a simple idea: many important measurement problems cannot be solved well with black-box methods and standard AI/ML alone. They require mechanistic modeling, careful treatment of uncertainty, and tools that stay useful when data are sparse, noisy, biased, or expensive to collect.
How we work
Mechanistic, first principles, and reduced-order modeling of real-world systems
Synthetic data generation and surrogate modeling for speed and scale
Machine learning, AI, and Bayesian approaches for inference and uncertainty quantification
Validation planning tied to real use cases
Who we are
Kiran Bhattacharyya, PhD
CEO and Principal
Kiran Bhattacharyya, PhD
CEO and Principal
Kiran Bhattacharyya is a biomedical engineer and computational scientist whose work sits at the intersection of physiological modeling, biosignal processing, inverse problems, synthetic data, computer vision, and deployable machine learning. His background spans computational neuroscience, optical and physiological sensing, simulation, Bayesian inference, and safety-critical AI development.
His experience includes research in biomedical engineering and computational neuroscience, applied modeling work at NASA Glenn Research Center, and machine learning leadership and science in healthcare technology at Intuitive Surgical and Beacon Biosignals. Across these roles, a consistent theme has been building systems that connect sensor physics and mechanistic modeling to practical AI tools.
Sara Milkes Espinosa
COO and Research Manager
Sara Milkes Espinosa
COO and Research Manager
Sara Milkes Espinosa is a mixed-methods researcher whose background spans human-computer interaction, digital media, AI/automation studies, and complex sociotechnical systems. Her work includes research at Georgia Tech on how people navigate platform environments and adopt AI tools in everyday decision-making, along with UX research experience at Meta and MilliporeSigma.
Her publication record includes work in venues such as CSCW, DIS, and CHIWORK, where she co-authored award-winning work. At SKA Labs, she strengthens projects through research operations, validation workflow coordination, documentation, reporting, visualization, and stakeholder-facing communication that helps translate technical work into clear and usable deliverables.
What makes us different
What makes us different
SKA Labs is especially well suited to projects that need:Â
Physics-informed or physiology-informed ML and AI
Synthetic data for rare events or underrepresented conditions
Robust sensor design across diverse users and environments
Inverse modeling and uncertainty-aware estimation
Technical work that must support proposals, validation, and decision-making
We develop computational methods for sensing, simulation, and uncertainty-aware AI with a focus on healthcare, biosensors, human performance, and other mission-critical applications.
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