8th IEEE International Conference on BioInspired Processing

Universidad de Costa Rica, Recinto de Guápiles, Pococí, Costa Rica

November 11th to 13th 2026

The 2026 8th IEEE International Conference on BioInspired Processing (BIP) is an event specialized in computational application to natural sciences and biologically inspired computational sciences. The host is rotated among the public universities in Costa Rica: Universidad de Costa Rica, Instituto Tecnológico de Costa Rica, Universidad Nacional, Universidad Estatal a Distancia, Universidad Técnica Nacional, and Centro Nacional de Alta Tecnología; supported by IEEE Costa Rica, as well as its different sections, chapters and affinity groups.

In 2026 the conference will be hosted by Universidad de Costa Rica, Recinto de Guápiles, Pococí, Limón Costa Rica, from November 11th to 13th.

BIP 2026 encourages authors in these areas to submit their original work for conference consideration.

Important dates:

It's BIP time in

Keynote Speakers

Dr. Thomas Jarmer

Senior Scientist in Remote Sensing and Digital Image Analysis,  Osnabrück University, Germany

Dr. Justin Dauwels

Associate professor and researcher specializing in signal processing systems, data analytics, and autonomous systems.

Dr. Francisco Siles

Professor and researcher at the University of Costa Rica specializing in artificial intelligence and pattern recognition. He leads several research and academic programs and has conducted postdoctoral research in computational biology and computational optics. His work applies AI to physics, robotics, and biomedical sciences.

Workshops

Hands-on Workshop on Multispectral UAV-Data Analysis for Functional and Species-Level Biodiversity Estimation using Python

Maren Pukrop

Research Associate & PhD Candidate, Institute of Computer Science, Osnabrück University, Germany

This hands-on workshop introduces participants to the use of multispectral UAV imagery and geospatial analysis for biodiversity monitoring in Central European grasslands. Participants will explore vegetation indices such as NDVI, estimate functional biodiversity through flower colour classification and potentially vegetation heterogeneity measures, and apply machine learning techniques for plant species identification and mapping.

Introduction to Large Language Model Engineering

Dr. Saúl Calderón Ramírez, ITCR

Estefanía Delgado Castillo, ITCR

Sarah Priscilla Quesada Chaves, ITCR

Óscar Andrés Obando Umaña, ITCR

M.Sc Danny Xie Li, University of Luxembourg

This hands-on workshop provided a practical introduction to the full lifecycle of building applications powered by large language models (LLMs), from Transformer architecture, tokenization, and embeddings to model adaptation and production deployment. Participants will explore efficient fine-tuning techniques such as LoRA and QLoRA, prompting strategies, retrieval-augmented generation (RAG), and orchestration tools such as LangChain and vector databases.