Eduardo Pérez, PhD
Senior Software Engineer at KDIS Research Group
Cordova, Andalusia, Spain
Summary
👤
Senior🎓
Top SchoolEduardo Pérez, PhD is a Senior Software Engineer and AI researcher with six years of professional experience combining academic rigor and industry delivery across full-stack, data engineering, and ML/LLM projects. He has bridged university research and commercial products—authoring papers in top journals while building production systems using Python, JavaScript, Kubernetes, AWS/Azure, Kafka/Redpanda, and orchestration tools like Dagster. His work spans deep learning and NLP research (TensorFlow, PyTorch, Hugging Face, LangChain) to hands-on mobile and web development (React, React Native, Android/iOS), enabling end-to-end ML solutions from model design to scalable deployment. At organizations from IMIBIC and Universidad de Córdoba to FMIT and Launch4, he has contributed to medical AI, automotive partnerships, and LLM-driven tooling, combining reproducible research practices with robust testing. Notably, he has served as peer reviewer for leading Elsevier journals and maintained editorial and conference roles, reflecting a rare blend of publication leadership and product-focused engineering. Based in Córdoba, Spain, he brings a multidisciplinary perspective—equally comfortable mentoring teams, leading research efforts, and shipping production-grade ML systems.
6 years of coding experience
11 years of employment as a software developer
MSc, Master's degree in Applied Mathematics and Informatics for Administration, Artificial Intelligence, MSc, Master's degree in Applied Mathematics and Informatics for Administration, Artificial Intelligence at University of HolguínPh.D. in Computer Science, Artificial Intelligence, Ph.D. in Computer Science, Artificial Intelligence at Universidad de Córdoba
Spanish, English
Github Skills (7)
dynamic-routing6
convolutional-neural-networks5
lstm-model4
deep-learning3
lstm2
machine-learning1
ranking1
Programming languages (1)
Github contributions (5)
kdis-lab/Review-CNN-Melanoma
Oct 2019 - Sep 2020
Convolutional neural networks for the automatic diagnosis of melanoma: an extensive experimental study
Contributions:22 commits, 16 PRs, 9 pushes in 11 months
deep-learningconvolutionalneural-networksmelanomaconvolutional-neural-networks
kdis-lab/SkinCancerRecognition-CapsNet
Oct 2019 - Sep 2021
Melanoma recognition via dynamic routing between capsules
Contributions:21 commits, 4 PRs, 8 pushes in 1 year 11 months
recognitionroutingcapsulesmelanomamelanoma-recognition
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