The 2025 Blavatnik Regional Awards Laureates are:

Life Sciences: Veena Padmanaban, PhD, nominated by The Rockefeller University

Recognized for discovering a molecular mechanism allowing sensory neurons to communicate with breast cancer cells to drive metastasis and uncovering novel actionable therapeutic targets.

Physical Sciences & Engineering: Valentin Crépel, PhD, nominated by the Flatiron Institute

Recognized for advancing theories describing stacked, single-atom-thick materials, enabling easier control of their behaviors for applications in quantum technology and opening up new avenues for developing materials useful in novel quantum computing platforms.

Chemical Sciences: Xiao Xie, PhD, nominated by Princeton University

Recognized for pioneering chemical biology tools to map protein phase separation and copper signaling, which uncover molecular mechanisms underlying cancer and neurodegenerative diseases. Xie is a postdoctoral fellow in the lab of 2015 Blavatnik National Awards Laureate, Christopher Chang, PhD.

The Finalists are:

LIFE SCIENCES

Maria Cecilia Campos Canesso, PhD, nominated by The Rockefeller University

Recognized for advancing our understanding of food allergies and inflammatory bowel disease by developing new tools to uncover how immune cells communicate in the intestine, laying the foundation for more effective treatments.

Ipshita Zutshi, PhD, nominated by New York University

Recognized for discovering how the brain integrates dynamic goals with sensory inputs (sound, vision) to guide memory and decision-making — providing a framework for understanding cognitive dysfunction in psychiatric disorders.

PHYSICAL SCIENCES & ENGINEERING

Ore Gottlieb, PhD, nominated by the Flatiron Institute

Recognized for shifting the paradigm describing neutron star mergers, giving scientists a roadmap for finding and studying these rare events.

Viraj Pandya, PhD, nominated by Columbia University

Recognized for groundbreaking discoveries on early galaxy evolution, reshaping our understanding of how galaxies formed and challenging longstanding theories of the early universe.

CHEMICAL SCIENCES

Lucien Dupuy, PhD, nominated by Rutgers University, Newark

Recognized for developing quantum-classical and machine learning simulations that elucidate how molecules respond to light, crucial to understanding diverse topics like DNA stability, photocatalysis, and energy conversion. Dupuy is the first Blavatnik Awards honoree from Rutgers University, Newark, NJ.

Yunjia Lai, PhD, nominated by Columbia University

Recognized for pioneering mass spectrometry innovations to map and screen environmental exposures and biological changes that drive neurodegenerative diseases including Parkinson’s and Alzheimer’s.

A new white paper: “From Knowledge to Solutions: Science, Technology and Innovation in Support of the UN SDGs”, published in the open-science scholarly journal Research Ideas and Outcomes (RIO), brings together leading voices from Europe’s biodiversity and data science communities to deliver a clear message: protecting biodiversity is not just an environmental issue. It is essential for food security, public health, climate stability, and the global economy. The authors make a call for a decisive shift: from fragmented initiatives to a holistic, global approach to biodiversity research and policy.

Depression is often linked to changes in facial expressions. However, the link between mild depression, known as subthreshold depression, and changes in facial expressions remains unclear. Now, researchers have investigated whether subthreshold depression shows changes in facial expressions in Japanese young adults using artificial intelligence. The findings reveal distinct muscle movement patterns related to depressive symptoms which may help detect depression early, paving the way for timely and preventative mental health care.

The geometry of standard multi-well cell culture plates restricts oblique illumination angles, preventing matched illumination condition required for accurate tomographic reconstruction. To overcome this limitation, researchers developed the DF-FPDT technique, which leverages non-matched illumination and harnesses it as an intrinsic mechanism for dark-field-like contrast enhancement. By selectively updating high-frequency components using Phase Transfer Function (PTF) filtering, DF-FPDT effectively addresses low-frequency loss, enabling high-resolution, high-contrast live-cell imaging and dynamic screening, making DF-FPDT a powerful tool for biomedical research under realistic laboratory conditions.