Building scientific AI systems that integrate biological knowledge, multimodal data, advanced models, intelligent agents, and experimental workflows.
Research → Models → Agents → Experiments / Bioprocess → Real-world Deployment
PAMI develops AI-native systems for life science research and bioprocess development. Instead of adding isolated AI tools to existing workflows, we redesign scientific workflows around AI from the outset.
Our systems enable models and agents to understand scientific objectives, organize heterogeneous data and knowledge, invoke analytical tools, coordinate experimental tasks, and continuously learn from new evidence. We combine research capabilities in machine learning, bioinformatics, multimodal biological modeling, and scientific AI with engineering experience in data infrastructure, agent orchestration, model deployment, and automated experimental systems.
PAMI connects algorithms, biological knowledge, process data, experimental systems, and continuous feedback in one scientific AI architecture.
Our research agenda connects transferable AI methodology with biological systems, bioprocess development, and intelligent experimental execution.
Data-efficient and interpretable AI models for understanding and optimizing complex bioprocesses.
Learning representations that can adapt to new biological systems with limited data.
Integrating imaging, molecular, process, and experimental data to characterize complex biological states.
Connecting scientific knowledge, data, models, tools, and experiments through agent-based workflows.
Selected publications demonstrate both methodological AI capability and the application of AI to biological systems, multimodal data, and scientific discovery.
Selected work in self-supervised learning, robust representation learning, heterogeneous data fusion, temporal modeling, and structured machine learning.
Selected work in AI-enabled biological discovery, scientific imaging, transfer learning, cellular representations, and multimodal biology.
PAMI translates scientific AI into deployable systems that operate on real data, real workflows, and, where appropriate, real experimental equipment.
Scientific data and agent infrastructure for bioprocess research, process-development analysis, knowledge organization, and model/tool orchestration.
Closed-loop AI systems connecting experimental planning, microscopy, device orchestration, image analysis, and structured data feedback.
Research workflows integrating imaging, clinical, experimental, and structured data with machine-learning pipelines and intelligent agents.
PAMI works across biological laboratories, biopharmaceutical companies, and hospitals, providing access to diverse scientific environments for experimental validation, bioprocess translation, and multimodal biomedical research.
Access to experimental expertise, biological samples, microscopy, cell-based research environments, and validation resources for AI-generated hypotheses and models.
Real-world bioprocess environments supporting process-data intelligence, scientific modeling, AI-agent workflows, and validation of process-development methods.
Multimodal biomedical research environments spanning medical imaging, pathology, clinical data, and AI-assisted scientific workflows.
Non-confidential examples across industry, laboratory, and clinical research settings.
Data, knowledge, modeling, and agent infrastructure supporting bioprocess research and process-development workflows.
Closed-loop experimental systems integrating microscopy, AI analysis, device orchestration, and structured feedback.
Scientific AI workflows for imaging, pathology, clinical data, structured analysis, and repeatable research execution.
Collaboration across machine learning, computational biology, multimodal modeling, and scientific AI methodology.
A reusable AI-native architecture connecting scientific knowledge, heterogeneous data, models, intelligent agents, analytical tools, experimental systems, and human experts.
Papers · Patents · SOPs · Domain rules · Expert knowledge
Process · Imaging · Omics · Experimental · Clinical · Sensor data
Knowledge intelligence · Scientific models · Multimodal AI · Optimization
Planning · Model/tool calling · Data workflows · Experiment support
Analytical tools · Experiments · Bioprocess workflows · Human experts
