Publications
At FEEH Innovations, research and knowledge dissemination are central to our mission. Our publications highlight interdisciplinary work across food systems, energy innovations, environmental sustainability, and global health.
Systemic Research Approach
Innovative Solutions
Collaborative Expertise
Food
Energy
Environment
Health
Systemic Research Approach
Innovative Solutions
Collaborative Expertise
Food
Energy
Environment
Health
Sustainable Protein Systems for Future Food Security
Author
Dr. Elena Marquez, Prof. David Lin, Dr. Samuel Ortega
Journal / Venue
Journal of Global Food Systems
Abstract
This study explores emerging protein production systems designed to address global food demand while minimizing environmental impact. The research evaluates plant-based proteins, microbial fermentation technologies, and circular agricultural models that improve resilience within global food supply chains.
Distributed Renewable Energy Models for Emerging Economies
Author
Dr. Thomas Reinhardt, Dr. Maya Al-Saleh
Journal / Venue
International Energy Innovations Review
Abstract
This publication examines decentralized renewable energy systems including microgrids and hybrid solar storage infrastructure. The study highlights implementation models that improve energy access in developing regions while maintaining economic feasibility and grid stability.
Climate Adaptation Strategies for Urban Environments
Author
Dr. Priya Raman, Prof. Luis Ortega
Journal / Venue
Environmental Systems & Policy
Abstract
Urban regions face increasing climate-related stressors. This research proposes integrated adaptation strategies that combine green infrastructure, water management systems, and resilient urban design to mitigate environmental risks and protect communities.
Integrating AI in Global Health Monitoring Systems
Author
Dr. Hannah Cole, Dr. Victor Mensah
Journal / Venue
Global Health Technology Journal
Abstract
Artificial intelligence is transforming global health surveillance and response systems. This research analyzes machine learning applications in disease detection, predictive outbreak modeling, and digital health infrastructure.
Reflective diagnostics: A self-learning CRISPR–biosensor–AI platform for adaptive food and health safety monitoring
Author
Jacob Tizhe Liberty
Journal / Venue
Food and Humanity
Abstract
Traditional food and health diagnostics are often limited by rigid protocols and binary outputs, which reduce their ability to respond effectively to complex, decentralized, and climate-sensitive safety challenges. This paper introduces the concept of Reflective Diagnostics, an adaptive diagnostic platform that combines three core elements: (1) CRISPR-based molecular detection, which identifies specific genetic material from pathogens; (2) interpretive biosensing, which contextualizes sensor signals by incorporating environmental data such as temperature, humidity, and time; and (3) AI-driven learning loops, which continuously update decision rules based on accumulated data and system feedback. These features support dynamic probe selection, memory-informed interpretation, and context-aware risk evaluation.
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