Profile Details

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Hire Dr. Jaime D.

Switzerland

USD 95 /hr

PhD AI Architect & Full-Stack Developer | Bridging Complex Biomedical Research with Deployable Software

Profile Summary

I am an AI Scientist and Software Architect with a PhD and extensive postdoctoral experience specializing in the intersection of machine learning, biomedical signal processing, and medical imaging. My core expertise lies in transforming complex, noisy biological data into robust, deployable AI models and software applications. Through my technical consulting agency, Scifork, I have successfully developed end-to-end projects ranging from machine learning pipelines to complete backend/frontend software architectures and blockchain systems. I bridge the gap between rigorous academic research and market-ready technological solutions. Current & Previous Research Focus - Digital Pathology & Cancer Diagnostics (Current): I am currently developing state-of-the-art AI architectures to analyze and classify H&E (Hematoxylin and Eosin) slides. This involves advanced computer vision and deep learning techniques to assist pathologists in highly accurate cancer diagnostics. - Biomedical Signal Processing (Postdoctoral Research): During my postdoctoral tenure, I focused on applying advanced AI and statistical modeling to process complex biomedical signals, extracting clinical insights and biomarkers from raw physiological data. Core Competencies & Skills: - Artificial Intelligence & Machine Learning: Deep Learning, Computer Vision (specifically medical imaging), Predictive Modeling, and Algorithm Optimization. - Biomedical Data Analysis: Signal processing, handling complex healthcare datasets, and building diagnostic support tools. - Full-Stack Software Development: Designing and deploying scalable backend infrastructures and intuitive frontend interfaces to make AI models accessible to end-users. - Blockchain Architecture: Designing secure, decentralized systems and smart contracts (highly applicable for healthcare data security and Web3 projects). Whether you are a research lab needing to process large sets of biomedical data, a MedTech startup requiring a custom machine learning pipeline, or a company needing a full-stack architect to build a platform from scratch, I bring both the academic depth and the engineering pragmatism to deliver high-quality results. I am highly adaptable and accustomed to solving complex, multidisciplinary problems.

Subject Matter Expertise

• ☆ Python
• ☆ Tensorflow
• ☆ Scikit-learn
• ☆ Peer Review

Services

• Research
• Consulting
• Data & AI

Research Scientific and Technical Research

Consulting Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Image Processing, Image Analysis, Algorithm Design-ML, Data Visualization, Big Data Analytics, Data Mining

Work Experience

Founder, Director

Tsebix SA

May 2025 - Present

Director and Technical lead

SciFork

June 2022 - Present

Postdoctoral Reseracher

Universite de Geneve

June 2016 - Present

Chief Technical Officer

Liti Capital

June 2021 - March 2022

Postdoctoral Researcher

University of Geneva

May 2016 - January 2020

Assistant Professor

Universidad del Norte

July 2014 - July 2019

Education

Ph.D in Electronics Engineering (Faculty of Engineering and Natural Sciences)

Sabanci Universitesi

August 2009 - July 2014

MSc in Electronics Engineering (Electrical and Electronics Engineering)

Universidad del Norte

January 2008 - July 2009

Specialist in Computer Networks

Universidad del Norte

August 2002 - September 2003

Ingeneer (Electrical and Electronics Engineering)

Universidad del Norte

January 1998 - October 2002

Certifications

• Certification details not provided.

Publications

JOURNAL ARTICLE

Delgado Saa, J.F., De Pesters, A., Cetin, M.(2016). Asynchronous decoding of finger movements from ECoG signals using long-range dependencies conditional random fields . Journal of Neural Engineering. 13. (3).

Saa, J.F.D., Pesters, A.D., McFarland, D., Çetin, M.(2015). Word-level language modeling for P300 spellers based on discriminative graphical models . Journal of Neural Engineering. 12. (2).

Delgado Saa, J.F., Cetin, M.(2013). Discriminative methods for classification of asynchronous imaginary motor tasks from EEG data . IEEE Transactions on Neural Systems and Rehabilitation Engineering. 21. (5). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 716-724.

Saa, J.F.D., Çetin, M.(2012). A latent discriminative model-based approach for classification of imaginary motor tasks from EEG data . Journal of Neural Engineering. 9. (2).

CONFERENCE PAPER

Delgado Saa, J.F., Çetin, M.(2011). Hidden conditional random fields for classification of imaginary motor tasks from EEG data . European Signal Processing Conference. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1377-1381.