Hi, I'm Romina

About Me

I'm Romina Soledad Molina, Ph.D., founder of KaleidoForge, a studio dedicated to connecting machine learning, optimization, and real-world hardware systems. I develop and deploy ML solutions directly on hardware, from edge devices to FPGA/SoC platforms, turning complex algorithms into efficient, deployable systems.

My work covers the full ML-to-hardware stack: model design and training, compression, FPGA and SoC deployment, system profiling, and reproducible workflows for scientific and edge applications.

I hold a joint Ph.D. in Industrial and Information Engineering (Italy) / Computer Science (Argentina), and I've spent years teaching and conducting research in digital signal processing, artificial vision, and embedded AI systems.

Since 2019, I have been collaborating with the Multidisciplinary Laboratory (MLab) at ICTP in Trieste, working on machine learning for advanced scientific instrumentation and contributing as an instructor in multiple international schools and workshops on FPGA, SoC, and embedded AI.

What I enjoy most is making complex systems clear, structured, and practical, so teams can focus on solving problems instead of struggling with the technology.

Why KaleidoForge

KaleidoForge emerged from a simple idea: modern ML systems don't need to be complicated to be powerful. When tools, workflows, and hardware interact coherently, you get systems that are easier to maintain, faster to iterate, and more intuitive to extend.

It's a space focused on clarity, engineering discipline, and thoughtful design, without unnecessary friction.

Why Work With Me

• Ph.D.-level expertise across the ML-to-hardware stack: training, optimization, compression, FPGA/SoC acceleration.
• International research experience: IAEA collaboration, Politecnico di Milano, CNR Pisa, University of Novi Sad, and more.
• Proven track record mentoring Master's and Bachelor's thesis projects on real-world AI applications.
• Ability to make advanced concepts concrete and understandable for multidisciplinary teams.
• Strong focus on documentation, reproducibility, and structured reasoning.

Design Principles

Every project, course, and workflow within KaleidoForge follows principles that keep technology purposeful and human-centered.

• Human-Readable Systems: clarity first, always.
• Hardware-Aware Intelligence: algorithms shaped by real constraints.
• Reproducible by Design: workflows that can be rebuilt and understood.
• Creative Logic: structured engineering guided by curiosity.
• Fast Meaning: efficiency aligned with purpose.