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Iker Pacheco
Portrait of Iker Pacheco

Iker Pacheco

Biomedical Engineer · AI & Deployed Products Specialist

I turn AI algorithms and models into working products, taking innovation from development all the way to production.

Projects

EndoTector demo segmenting a polyp in an endoscopy frame

EndoTector

Polyp segmentation in endoscopy with YOLO-seg

Median Dice
0.96
mAP@50
0.95

Real-time inference.

Problem
Outline polyps in endoscopy images with a model light enough to run in real time.
Approach
Fine-tuned a 6 MB YOLO-seg model on the Kvasir-SEG dataset, with an interactive Gradio web demo.
Stack
  • Python
  • YOLO-seg
  • OpenCV
  • Gradio
  • Docker
  • GitHub

CAI-listhenics

Pull-up technique analysis with computer vision

End-to-end system deployed: Python backend and Gradio client on Hugging Face Spaces.

Problem
One day, training back, I realised how hard it is to count reps and judge the technique of every pull-up by eye. An AI support system that measures each rep and returns objective exercise metrics adds exactly that value.
Approach
Pose estimation with MediaPipe and per-rep kinematics, such as the eccentric/concentric ratio, computed with OpenCV and SciPy.
Stack
  • Python
  • MediaPipe
  • OpenCV
  • SciPy
  • Gradio
  • Hugging Face Spaces
Iker Pacheco presenting the explainability (SHAP) analysis of the ALS project
Bachelor's thesis poster on early ALS detection from voice: aims, method, biomarkers, results and conclusions

Early ALS detection from voice

Explainable ML on acoustic biomarkers from smartphone recordings

Bachelor's thesis, graded 10/10. Nominated for CASEIB 2026.

AUC
0.831
Sensitivity
80%
F1
81.2%

LASSO + XGBoost validated with 10-fold CV and 95% CIs.

Problem
Detect ALS early from smartphone voice recordings, with an interpretable model.
Approach
Explainable ML pipeline on acoustic biomarkers: LASSO feature selection, XGBoost classification and SHAP explanations.
Stack
  • Python
  • scikit-learn
  • Praat-Parselmouth
  • Explainable AI (XAI)
  • Statistics
  • SciPy
  • Signal Processing
  • Data Science
  • Data Engineering
Paper · Under review, 2026

Pacheco-Herrero, I., Rico-Juan, J.R., Ballester-Berman, J.D. Explainable machine learning pipeline for early ALS detection using physiologically interpretable acoustic features from smartphone recordings. Biomedical Signal Processing and Control.

Experience

  1. Mar 2026 - Jun 2026

    Hybrid

    Human Robotics

    R&D Intern

    Research on HD-sEMG signal processing.

    • Python algorithm estimating muscle fiber conduction velocity from 32-channel HD-sEMG.
    • Designed and ran a 6-subject muscle fatigue study with HD-sEMG arrays to characterize fatigue indicators.
    • Python
    • Signal Processing
    • Data Science
    • Statistics
    • Biomechanics
    • Electrophysiology
  2. Jul 2025 - Aug 2025

    Remote

    Bimaxpro

    Software Development Intern

    Development of a healthcare web application.

    • Tested and validated REST API endpoints with Swagger and Postman.
    • Proposed and documented an improved HTTP request-handling implementation for the .NET REST layer.
    • Scrum team with Git-based workflows and Azure DevOps.
    • .NET
    • C#
    • HTTP
    • Agile
    • Scrum
    • Bootstrap
    • Angular
  3. Jun 2025 - Jul 2025

    Villajoyosa

    Hospital Marina Baixa

    Clinical Engineering Intern

    Biomedical equipment maintenance.

    • Preventive and corrective maintenance and calibration of medical devices (ventilators, Dopplers).
    • Electromedical equipment
    • Electronics
    • Physics
    • Medical instrumentation

Skills

Cloud and MLOps

  • Hugging Face Spaces
  • Azure
  • Flask
  • Docker
  • Git
  • Linux

Software and systems engineering

  • Java
  • Go
  • JavaScript
  • SQL
  • REST APIs
  • Swagger
  • Postman
  • Distributed systems
  • Inter-process communication
  • Scalability
  • Usability and accessibility

Biomedical engineering foundations

  • Anatomy and physiology
  • Pathophysiology
  • Pharmacology
  • Physiological fluid mechanics
  • Biomaterials
  • Healthcare service management

About

Iker Pacheco at the XII AITADIS Conference, Alicante 2026

Biomedical engineer (UA) and Master's student in AI. I move between two worlds: healthcare, where I started out working with biomedical signals and data, voice and medical imaging, and applied AI, where I build models and turn them into products.

I'm interested in real problems, models you can understand and code that ends up in production, not forgotten in a notebook.

Education
Master's in Artificial IntelligenceUniversity of Alicante · Sep 2026 - Jul 2027 (expected)
BSc in Biomedical EngineeringUniversity of Alicante · Completed Jun 2026
Languages
Spanish (native), Valencian (native), English (B2, professional working proficiency)
Location
Alicante, Spain