At the Institute of Applied Artificial Intelligence and Robotics (IAAIR), our research philosophy is rooted in applied AI. We bridge the gap between foundational academic research and real-world application. While the AI community continues to make breakthroughs in theory and modelling, our mission is to translate that openly available fundamental research into solutions that address complex business challenges and pressing societal needs.
One of our key initiatives is OpenAg, a large-scale research effort to democratize agricultural intelligence and create a path toward Artificial General Intelligence (AGI) in agriculture. This initiative brings together our non-profit foundation, the World Food Bank, and a growing network of more than 150,000 farmers. Together, we explore how advanced AI can help improve food systems, sustainability, and the livelihoods of smallholder farmers.
Our work also covers a wide range of research areas. These include enterprise AI adoption, operational challenges when deploying AI, AI security and privacy, detecting AI-generated content, improving AI conversations, gemstone analysis, and the emerging field of quantum machine learning. We also study issues that come up when moving AI systems from the lab into production, such as technical debt, data drift, and model degradation.
At IAAIR, we also place a strong emphasis on Responsible AI and Ethical AI. Our work considers fairness, transparency, accountability, and societal impact from the ground up. We believe that AI must be designed and deployed with an awareness of its implications, ensuring that it serves the broader public good and remains aligned with human values.
Research at IAAIR
“Our mission is to create a future where AI is not only powerful and efficient but also secure, ethical, and beneficial for all.”
OpenAG: Democratizing Agricultural Intelligence
OpenAG is our flagship initiative focused on building intelligent tools for the agriculture sector. Through the use of domain-specific AI models, multi-agent systems, and neural knowledge graphs, the initiative delivers real-time, context-aware insights to farmers. It is being field-tested in partnership with thousands of farmers and supported by global organizations committed to innovation in agriculture and food security.
For more details, read our OpenAg Whitepaper
Our Research Focus Areas
Conversational AI
We are working to make human-AI interactions more natural, emotionally aware, and context-sensitive. This includes designing dialogue systems that can understand user intent, respond appropriately in real time, and avoid the robotic feel often associated with AI. Our goal is to close the gap between human and machine communication by addressing issues such as tone, empathy, and the uncanny valley.
AI in Enterprise Systems
Enterprises often face unique challenges when adopting AI, particularly due to legacy infrastructure and complex data environments. Our research examines how AI can be integrated into existing enterprise resource planning (ERP) systems, and how to create scalable architectures that bridge old and new technologies. We also investigate the organizational and cultural changes required to support successful AI adoption across departments and processes.
Detecting AI-Generated Content
The rise of generative AI has created new challenges in verifying the authenticity of content. Our team is developing tools to detect deepfakes, identify AI-written text, and authenticate digital media across video, audio, and text formats. This work is critical for supporting trust in communication, journalism, and content moderation, and it plays a growing role in public policy and security.
AI in Production
We focus on the practical realities of deploying AI systems in production environments. Our research looks at how to build systems that remain reliable over time, especially in the face of changing data, evolving use cases, and limited technical resources. We study how to monitor and manage these systems effectively and how to design machine learning pipelines that can adapt to real-world conditions without requiring constant manual intervention.
AI for Gemstone Grading
Our researchers apply computer vision and machine learning techniques to evaluate gemstone quality. By identifying and extracting fine-grained visual features, we can provide consistent and accurate assessments that support industries where manual grading has traditionally been subjective. This work opens new opportunities for automation, quality assurance, and digital traceability in the gemstone market.
AI Security and Privacy
As AI systems process increasingly sensitive data, ensuring privacy and security is a top priority. We explore techniques such as federated learning, differential privacy, and secure model sharing to reduce risks while maintaining performance. Our research also looks at how to build AI systems that are robust against adversarial attacks and that can be trusted to behave as intended, even under challenging conditions.
Quantum Machine Learning
We are exploring how the principles of quantum computing can be combined with machine learning to solve problems more efficiently. Our research includes early-stage work on quantum-classical hybrid models, quantum-enhanced optimization, and the application of quantum methods to enterprise-scale AI problems. Although the field is still emerging, we believe that quantum AI holds long-term potential for accelerating model performance and solving complex data problems.
See where we think the future of QML is heading in the next decade here.
IAAIR Internships
We believe that hands-on research experience is essential to developing the next generation of AI leaders. Our Applied AI Research Internship Program offers students and early-career professionals the opportunity to work on real-world problems alongside our core research team. Interns contribute to active research streams that span agriculture, enterprise AI, AI safety, quantum machine learning, and more.
Each project is designed to expose interns to both technical development and practical deployment challenges. We encourage interdisciplinary thinking, curiosity, and a focus on producing work that creates real-world impact.
We welcome interest in internships, subject matter expert roles, and external supervision. Check our current availability here.
Current Internship Projects: