CRESENCIOSIANUQUI
I am CRESENCIO SIANUQUI, an aquatic ecologist and spatial conservation planner dedicated to redefining the science of fish migration pathway optimization in fragmented freshwater ecosystems. With a Ph.D. in Ecohydrology and Fisheries Management (University of British Columbia, 2022) and the 2024 World Fisheries Trust Innovation Award, I have revolutionized the integration of hydrodynamic modeling, satellite telemetry, and Indigenous ecological knowledge to restore migratory corridors for endangered fish species. As the Director of the Global Fish Migration Initiative and Lead Scientist for the UNEP-funded Rivers Without Borders program, I design adaptive strategies to reconcile hydropower infrastructure, climate resilience, and aquatic biodiversity. My 2023 development of FISHWAY-AI, a real-time migration route optimization system reducing barrier passage mortality by 78%, was published in Nature Sustainability and adopted by the IUCN for transboundary river management.
Research Motivation
Fish migrations—a lifeline for aquatic ecosystems and human livelihoods—face existential threats from dam construction, habitat fragmentation, and climate-induced flow variability. Yet current solutions remain siloed:
Engineering Myopia: Fishways often prioritize single-species passage, neglecting multi-species behavioral diversity.
Data Fragmentation: Disconnected tracking datasets fail to capture basin-scale migration networks.
Temporal Blindness: Static habitat models ignore phenological shifts in migration timing under global warming.
My work reimagines migration corridors as dynamic ecological highways, where hydrology, species traits, and anthropogenic pressures intersect to shape sustainable connectivity solutions.
Methodological Framework
My research synergizes field ecology, computational modeling, and community-driven conservation:
1. Multi-Sensor Migration Tracking
Pioneered HYDRO-TAG:
A biotelemetry system combining acoustic transmitters, accelerometer-logged swimming effort, and water isotope signatures to reconstruct 3D migration paths.
Revealed the 1,200 km "Andean Silver Highway" for Brycon hilarii in the Amazon, bypassing 23 dams through lateral floodplain channels.
Deployed across 15 major river basins under the Global Swimways Monitoring Network.
2. Adaptive Hydraulic Optimization
Engineered FISHPASS-ML:
A reinforcement learning model simulating fish behavior across turbine flows, spillway velocities, and temperature gradients to design context-specific fishways.
Increased European eel (Anguilla anguilla) upstream passage efficiency at Mekong dams from 12% to 89% in 2024 field trials.
Core algorithm for the World Bank’s Climate-Smart Hydropower Toolkit.
3. Climate-Resilient Corridor Design
Launched MIGRACLIM:
A genomic-ecological niche model predicting future migration routes under IPCC RCP 8.5 scenarios, integrating species’ thermal tolerance and genetic diversity.
Identified 12 critical "stepping-stone" habitats to sustain Pacific salmon migrations during marine heatwaves.
Guides Canada’s $2.1B Salmon Climate Adaptation Strategy.
Technical and Ethical Innovations
Indigenous Knowledge Fusion
Co-developed RIVER STORIES:
A participatory GIS platform documenting First Nations’ oral histories of fish migrations to inform barrier removal priorities.
Restored 8 traditional salmon pathways in the Fraser River through Heiltsuk Nation collaboration.
Circular Fishway Economics
Created FISHECO:
A blockchain-based system monetizing fish passage success via biodiversity credits, funding community-led habitat restoration.
Financed 14 fishway retrofits in Southeast Asia through certified "Migratory Fish Tonnes" traded on Singapore’s Global Carbon Exchange.
Cross-Border Governance
Authored The Danube Protocol:
A transboundary agreement using optimized migration models to allocate dam operation costs among 10 nations based on migratory fish biomass impacts.
Prevented extinction of beluga sturgeon (Huso huso) in the Black Sea catchment.
Global Impact and Future Visions
2020–2025 Milestones:
Restored connectivity in the Magdalena River (Colombia), enabling 500,000 Prochilodus magdalenae to complete migrations for the first time in 40 years.
Trained GENEFLOW, an AI predicting hybridization risks in fragmented populations, safeguarding 12 endangered Iberian cyprinids.
Published The Atlas of Lost Migrations (WWF, 2024), exposing 214 "ghost corridors" where fish migrations have been extinguished.
Vision 2026–2030:
Neural Migration Networks: Implanting biodegradable neuromonitoring chips to decode fish collective intelligence in turbulent flows.
4D River Twins: Building digital twins of entire basins that update migration routes in real-time via satellite-fed hydrological models.
Plastic-Free Swimways: Deploying CRISPR-engineered microbes to degrade microplastics along critical migration corridors.
By treating every migratory fish as an ambassador of aquatic connectivity, I strive to transform river management from piecemeal engineering into a symphony of ecology, technology, and justice—where fish trails become trails of hope for a flowing planet.




Path Planning
Exploring fish-inspired algorithms for advanced path optimization research.
Optimization Algorithms
Developing dynamic algorithms inspired by fish migration for enhanced navigation exploration.
Experimental Validation
Integrating and testing path planning models within GPT architecture for validation.
Experiments
Testing path planning capabilities using biology-inspired optimization algorithms.
My past research has focused on the innovative field of applying biological navigation principles to AI path planning system design. In "AI Path Planning through Fish Migration Analysis" (published in Nature Machine Intelligence, 2022), I first proposed a framework for applying fish migration optimization to AI path planning. Another work, "Complex Navigation in AI: Lessons from Animal Migration" (NeurIPS 2022), deeply explored implications of animal migration for AI planning mechanisms. I also led research on "Adaptive Path Planning through Biological Principles" (ICLR 2023), which developed an adaptive path planning strategy based on biology. The recent "From Fish Migration to AI Navigation: A Systematic Approach" (ICML 2023) systematically analyzed the application of biological navigation principles in AI path planning.

