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Position: Biology is the Challenge Physics-Informed ML Needs to Evolve
Julien Martinelli
arXiv·2025
Physics-Informed Machine Learning (PIML) has successfully integrated mechanistic understanding into machine learning, particularly in domains governed by well-known physical laws. This success has motivated efforts to apply PIML to biology, a field rich in dynamical systems but shaped by different constraints. Biological modeling, however, presents unique challenges: multi-faceted and uncertain prior knowledge, heterogeneous and noisy data, partial observability, and complex, high-dimensional networks. In this position paper, we argue that these challenges should not be seen as obstacles to PIML, but as catalysts for its evolution. We propose Biology-Informed Machine Learning (BIML): a principled extension of PIML that retains its structural grounding while adapting to the practical realities of biology. Rather than replacing PIML, BIML retools its methods to operate under softer, probabilistic forms of prior knowledge. We outline four foundational pillars as a roadmap for this transition: uncertainty quantification, contextualization, constrained latent structure inference, and scalability. Foundation Models and Large Language Models will be key enablers, bridging human expertise with computational modeling. We conclude with concrete recommendations to build the BIML ecosystem and channel PIML-inspired innovation toward challenges of high scientific and societal relevance.
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View paper →International migration, remittances and development: myths and facts
Hein De Haas
Third World Quarterly·2005·372 citations
The debate on international South–North labour migration tends to focus on the receiving end of migration. This bias obscures a proper understanding of the developmental causes and consequences of migration at the sending end. The reciprocal migration–development relationship is examined through the discussion of seven migration ‘myths’. Because of its profound developmental roots, it is useless to think that migration can be halted or that aid and trade are short-cut ‘solutions’ to immigration. Migrant remittances contribute significantly to development and living conditions in sending countries. Nevertheless, the recent ‘remittance euphoria’ is not justified, because unattractive investment environments and restrictive immigration policies which interrupt circular migration patterns prevent the high development potential of migration from being fully realised. Although specific policies can enhance this potential through facilitating remittance transfers and investments, the key lies in encouraging circular migration. Instead of uselessly and harmfully trying to stop inevitable migration, immigration policies allowing for freer circulation can, besides increasing migration control, enhance the vital contribution of migrants to the development of their home countries.
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