Alejandro Gutiérrez Alcoba

Edinburgh, UK | Senior Software Engineer & Computational Mathematician

Professional Summary

Senior Software Engineer with a PhD in Computer Science and an academic background in mathematics, specializing in the intersection of complex systems architecture, simulation, and data analysis. I bridge the gap between theoretical research and applied engineering, bringing deep expertise in C++ and Python to large-scale, highly regulated environments and entrepreneurial ventures.

My technical background spans a wide array of domains, including high-performance computing (HPC), dynamic decision-making, and applied machine learning. Recently, my work has focused heavily on precision instrumentation and medical diagnostics—specifically architecting hardware-software integrations, developing digital twins to simulate complex physical systems, and deploying predictive diagnostic pipelines.

Whether designing optimization algorithms for resource management and renewable energy logistics, or refactoring critical legacy infrastructure for high-throughput laboratory equipment, I focus on transforming complex requirements into reliable, robust, and mathematically sound software solutions.

Professional Experience

Senior Software Engineer

Arrayjet · Full-time Apr 2024 – Present Edinburgh, Scotland, United Kingdom

  • System Architecture & Fail-Safe Recovery: Architected a unified hardware error-handling framework for a C++/MFC application, centralizing communication with PLCs and motion controllers. Replaced silent application failures with robust fail-fast serialization and state-restoration protocols to enable interactive recovery from transient timeouts and mid-print crashes.
  • Hardware Simulation & CI/CD: Developed a modular digital twin of key instrument subsystems by creating mock PLC, FPGA, and camera interfaces. This abstraction facilitated offline validation of complex print runs and enabled a Jenkins and Docker-based Continuous Integration pipeline for automated testing.
  • Data Analysis & Bioinformatics Pipelines: Engineered a containerized Python-based automated analysis pipeline for high-throughput microarray screening. Developed a Streamlit web interface to automate statistical hit-calling, dynamic Z-score thresholding, and specificity cross-checking, replacing manual workflows and ensuring experimental reproducibility.
  • Diagnostic & Predictive Modeling: Deployed an automated diagnostic tool to monitor fluidic aspiration quality, utilizing feature extraction from time-series pressure sensor data to train a predictive model for air bubble anomaly detection.
  • High-Level Instrument Control: Built a Finite State Machine (FSM) engine to drive prototype hardware, translating low-level firmware instructions into automated, complex fluidic operations.
  • Core Print Engine Refactoring: Led the redesign of the core printing logic for high-density layouts. Delivered full-stack feature implementations including automated tray offset calibration, leveraging camera integration and existing computer vision algorithms.

Algorithm Software Engineer

Waire Health · Full-time Aug 2023 – Feb 2024 Edinburgh, Scotland, United Kingdom

  • Algorithm Development: Designed state-of-the-art algorithms for Heart Rate (HR), Blood Oxygen Saturation (SpO2), and Respiration Rate measurement for a wearable medical device, utilizing Digital Signal Processing (DSP) techniques on photoplethysmography (PPG) signals.
  • Signal Processing Accuracy: Developed a robust adaptive filtering algorithm to derive SpO2 in the presence of motion artifacts, leveraging accelerometer signals and advanced DSP to achieve highly reliable measurements.

Senior Software Engineer

DYSIS Medical · Full-time · Remote Oct 2022 – Aug 2023 Edinburgh, Scotland, United Kingdom

  • Manufacturing Tooling Architecture: Architected and deployed an end-to-end Python calibration suite used directly by production engineers, standardizing the tuning process for diagnostic hardware and reducing operational overhead.
  • Hardware Abstraction: Engineered a core C++ hardware interface with complete Python bindings, enabling precise, cross-platform control over low-level physical device parameters.
  • Pipeline Automation: Integrated Continuous Integration (CI) practices into the development workflow by configuring automated testing pipelines with Catch2 (C++) and pytest (Python), establishing a more reliable release process.
  • Application Maintenance: Investigated and resolved critical bugs within the primary Linux-based desktop application, improving overall software stability and device performance.

Marie Skłodowska-Curie Research Fellow (TRAIN@Ed COFUND)

University of Edinburgh | Industrial Partner: Costain Group Nov 2019 – Oct 2022 Edinburgh, UK

  • Awarded a highly competitive European Horizon 2020 fellowship to lead a joint academic-industrial project on the decarbonization of heavy road freight via Electric Road Systems (ERS).
  • Created a novel mathematical framework (the Stochastic Inventory Routing Problem on Electric Roads) utilizing isochrone graphs to accurately model dynamic energy consumption, battery states, and the continuous charging of hybrid vehicles in transit.
  • Engineered Mixed-Integer Linear Programming (MILP) heuristics and Stochastic Dynamic Programming (SDP) models to solve NP-hard routing and lot-sizing problems under non-stationary stochastic demand.
  • Collaborated directly with Costain Group to analyze the economic and environmental feasibility of catenary-based electric roads, translating complex stochastic models into actionable strategies for low-carbon infrastructure roll-outs.

AI Software Engineer

DYSIS Medical · Full-time Sep 2018 – Oct 2019 Edinburgh, Scotland, United Kingdom

  • Diagnostic AI Solutions: Delivered AI solutions for assessing cervical precancerous lesions from colposcopy images, advancing diagnostic accuracy.
  • Deep Learning Architecture: Developed an ensemble of deep learning and LSTM neural networks that achieved 92% sensitivity and 87% specificity for biopsy areas with known histopathological results.
  • Application Development: Contributed to the foundational development of the Linux-based desktop application, rapidly adapting to new technologies including C++ and Qt.
  • Technologies: Python, scikit-learn, TensorFlow, C++, Qt, Git

Founder and Project Lead

Kinwatt (Málaga University Spin-Off Project) Sep 2017 – Jul 2018 Málaga, Spain

  • Team Leadership & Product Development: Founded and managed a team of four to develop innovative Android applications and tools for cyclists using Java.
  • Simulation Algorithms: Directed the implementation of algorithms to simulate indoor cycling dynamics based on real-time power exertion.
  • Machine Learning Applications: Applied mathematical models and machine learning to create solutions such as real-time air drag resistance estimation for track cyclists utilizing power meter data.
  • Technologies: Java, Python, Git

Doctoral Researcher (PhD in Computer Science)

University of Málaga | Málaga, Spain Jan 2014 – Feb 2018

  • Conducted four years of rigorous, full-time academic research at the intersection of high-performance computing and operations research.
  • Engineered highly concurrent, multi-GPU and MPI-PTHREADS software architectures to radically accelerate complex optimization algorithms for large-scale dynamic decision-making systems.
  • Designed advanced workload-balancing heuristics for heterogeneous computing platforms, modeling computational distribution via bin-packing algorithms to maximize system efficiency and throughput.
  • Developed dynamic heuristics and Stochastic Programming (SP) models for perishable inventory control, solving complex fill-rate constraints under non-stationary stochastic demand for fresh food supply chains.
  • Built simulation-backed optimization models for the renewable energy sector, delivering decision-support frameworks to determine cost-efficient vessel fleet compositions for offshore wind farm maintenance under extreme uncertainty.

Education

PhD in Computer Science

University of Málaga, Spain | Jan 2014 – Feb 2018

  • Thesis: Computational Methods and Parallel Strategies in Dynamic Decision Making
  • Supervisors: Dr. Eligius M.T. Hendrix, Dr. Gloria Ortega
  • Summary: Researched and applied high-performance computing (HPC) techniques to dynamic optimization problems, including perishable inventory control and decision-support systems for offshore wind farm maintenance.

MSc in Software Engineering and Artificial Intelligence

University of Málaga, Spain | 2012 – 2013

  • Thesis Title: Procedural Content Generation for a New Game Based on the N-body Problem
  • Designed and developed a physics-based video game in Java and implemented evolutionary algorithms to automate content generation.
  • Supervisor: Antonio J. Fernández-Leiva

MSc in Mathematics

University of Málaga, Spain | 2012 – 2013

  • Thesis Title: Invertibility in Path Algebras
  • Characterised invertible elements in finite-dimensional path algebras and proved that the group of invertible elements forms a connected algebraic group with notable topological properties.
  • Supervisor: Cándido Martín González

Licenciatura in Mathematics

University of Málaga, Spain | 2004 – 2009

  • Equivalent to a Bachelor of Science (BSc) + Master’s Degree.

Technical Footprint

  • Languages & Frameworks: C++, Python, C, Qt, MFC, Boost
  • Systems & DevOps: Docker, Jenkins, Git, SVN, Multi-GPU, MPI-PTHREADS
  • Hardware & Integration: PLC Systems, Firmware Interfaces, Hardware Simulation, Digital Twins
  • Mathematics: Operations Research, MILP, SDP, Heuristics