Sync.Bio.Optics

RESEARCH AREAS

1. Optics & Photonics applications 

Our work here includes optical tweezers with deep-learning autofocus, Bessel beam microscopy without moving parts, an aberrated segmented telescope corrected with an SLM, and metamaterial FDTD simulation. The upcoming eQUIP-PH quantum-photonics testbed, validated through a Hong–Ou-Mandel configuration, is the frontier. We draw on optics, signals, and machine learning for this work. 

2. Synchronization & signals in real systems 

The escape-panic work is our landmark result. Real and simulated crowd egress shows self-organized queuing, streaming, and scale-free, self-organized critical statistics. This order emerges without anyone in the crowd intending it. We verified this with mice experiments and 2-D cellular-automata models. A second thread manipulates motile cells with electric fields (galvanotaxis), as a controllable "crowd," where we can turn the coupling up and down at will. We draw on synchronization, spectral analysis, and complexity for this work. 

3. Networks of language & society 

Texts become word-adjacency graphs and syntactic graphs. The metrics from these graphs classify prose against poetry, and they survive translation. This shows the modelling choice captured something real, not an artefact of one language. We use the same toolkit to map co-authorship networks, cofunding networks, and congressional networks. We draw on networks and information theory for this work. 

4. Human mobility & tourism analytics 

We run SEIR epidemic dynamics on the mobility network itself, not on a well-mixed population. Multiplex spatial networks, shortest-path cutting, and traffic prediction feed the upcoming SPROUT project (Filipino-language sentiment analysis, QR-code mobility tracking) and the NAMIT project (foodnetwork analytics). We draw on networks and machine learning for this work. 

5. Digital bioacoustics 

Acoustic indices, computed from soundscape recordings, act as proxies for bird-species richness. You can hear how biodiverse a place is, cheaply and continuously --- including through the COVID anthropause, when human noise fell away. The pipeline runs largely in R. We draw on spectral analysis, information theory, and machine learning for this work. 

6. Digital taphonomy / ARCHAEOVISION 

Assemblages like the tens of thousands of Callao Cave microvertebrate specimens are too large to classify by hand within any reasonable time. The group builds an imager, a datastore, a digital reference collection, and an inference engine --- plus a citizen-science website --- to classify them with ML instead. This includes Vision-Transformer identification of small skeletal remains. We draw on machine learning, imaging, and mathematical foundations for this work.

7. Digital medicine 

Our work here spans several projects: photodynamic-therapy photosensitizers, tested on cancer cell lines; DNAResonate's label-free, resonant-acoustic DNA detection; and FIND MiDAS's portable multi-virus lab-on-a-chip for low-resource settings. RESPOND-TNBC's RNA-signature work for chemotherapy response is next in the pipeline. We draw on machine learning and optics for this work. 

8. Digital agriculture & environment 

We build a people-centered harmful-algal-bloom early-warning system, with fisher partnerships --- an early-warning system that nobody trusts is not an early-warning system. We also build CATFish's swarm-capable mini-AUVs, and ENMESH's sensor mesh for marine and forest monitoring. We draw on machine learning and networks for this work 

9. Earth observation & geophysics 

The group validated and blended satellite and ground rainfall data. This work showed that a widely used near-real-time product underestimates Philippine rain. We could only detect this finding against independent, in-house ground-gauge truth. If left uncorrected, this error propagates into every downstream flood-warning and agriculture decision. We draw on machine learning and spectral analysis for this work 

10. Education technology 

VISSER is both research and mission. The group builds the instrument, deploys it to schools in Basilan and Cebu, and measures whether it actually improved cognitive learning and higher-order thinking. This is an unusual case: the group evaluates its own extension work, rather than only delivering it. We draw on machine learning and instrumentation for this work.

11. Complex systems & materials 

Our work here spans several unrelated systems, read through one nonlineardynamics lens: light-switchable anthracene photochemistry and lithography; ionic liquids for CO2 capture; stock-market and oil-price network structure; and the Cellular-Potts modelling behind CB-MEAT's scaffolded-versusnon-scaffolded cell growth. We draw on nonlinear dynamics, machine learning, and optics for this work 

Recent Publications