Natural Language Processing
Language understanding, information extraction, multilingual systems, evaluation, and domain adaptation.
Applied AI research
Research Areas
Biom RG explores frontier AI through a practical research lens, bringing together people working on language, agents, retrieval, knowledge systems, data infrastructure, and responsible deployment.
Focus themes
Technical forums with interdisciplinary reach.
These areas guide event programming, discussion themes, speaker invitations, and partnership opportunities.
Deep Learning
Neural architectures, model training, representation learning, and applied machine intelligence.
Agentic AI
Autonomous workflows, tool-using agents, planning, evaluation, and human oversight.
Retrieval Augmented Generation
Retrieval pipelines, grounded generation, enterprise knowledge systems, and evaluation.
Vector Databases
Semantic search, embeddings, hybrid retrieval, indexing, and scalable knowledge infrastructure.
Responsible AI
Safety, privacy, governance, bias, transparency, and trustworthy deployment.
Discussion themes
What we explore together.
Biom RG sessions are shaped around concrete technical questions: how systems are evaluated, how data is retrieved, how human oversight is designed, and how innovation communities can share knowledge responsibly.
- Evaluation methods for language systems and AI agents.
- Grounded generation, vector search, and knowledge infrastructure.
- Responsible governance for applied AI in health, industry, and sustainability.
- Research-to-prototype collaboration between founders and domain experts.
