Metaheuristics and research
A track focused on formulation, optimization, and experimentation, connected to your academic path and your capstone work within the INF context.
About
Applied research with product intent.
I work at the intersection of applied research and product execution: recommendation systems, machine learning, and optimization for high-impact decisions.
I contribute across government, startups, and digital products with legible architecture, objective experimentation, and operationally grounded delivery.
How I help
Research and modeling
Recommendation, ranking, metaheuristics, interpretability, and trade-off evaluation.
Technical consulting
Product diagnosis, architecture definition, and acceleration of complex AI decisions.
Principle
Technique as leverage, not decoration.
The aim is to build intelligence that is useful, auditable, and decision-oriented without turning the interface into an internal manifesto.
Two core tracks
Research in metaheuristics and an applied background in recommendation systems.
These two lines reinforce each other: on one side, technical investigation into optimization and search; on the other, the construction of systems that must turn imperfect signal into useful decisions.
Recommendation systems
A track applied to ranking, matching, personalization, and prioritization, reflecting your professional background and real-world work in this domain.