I prioritize team collaboration, adaptability and commitment to continuous learning and professional growth
I'm flexible with time zone communications
Problem-Solving & Innovation
Tech enthusiast with a passion for Healthcare and Biochemistry.
Low-code for small business
Currently working on leveraging LLMs to optimize and automate workflows
Interested in working together?
Educational/Professional Background
BSc in Biochemistry
University of Aveiro
Date: 2019-2022
- Competencies in Microbiology, Genetics, Cell Biology, General Physiology, and Molecular Biology, providing a comprehensive foundation in the biological sciences (Biology).
- Expertise development in Biochemistry I & II, Structure and Function of Macromolecules, Food Biochemistry, Energy of Metabolic Processes, Bioinformatics, Secondary Metabolism I, and Molecular Pathology, fostering advanced knowledge in biochemical processes and molecular dynamics (Biochemistry).
- Comprehensive grounding in the Fundamentals of Chemistry, with advanced proficiency in Organic Chemistry I & II, Secondary Metabolism II, and Instrumental Analysis Methods; enhanced by expertise in Physical Biological Chemistry and hands-on experience gained through 'Laboratory Q1' (Chemistry).
- Integrated laboratory experience bridging Biochemistry and Chemistry, with hands-on learning in Laboratory 'Bq-Qo' and Laboratory 'B2-Qf', enhancing interdisciplinary technical capabilities (Biochemistry/Chemistry).
- Strategic introduction to computational methods in scientific and engineering contexts, enhancing problem-solving and technical integration besides robust analytical and quantitative capabilities developed through a comprehensive sequence in Calculus I, II, and III, alongside Numerical and Statistical Methods, enabling data-driven decision-making and mathematical precision reinforced by a solid grounding in the foundational principles of General Physics (Physics and Mathematics).
Erasmus+ in Biochemistry
University of Poznań
Date: 2021-2022
- Completed Bioprocess Technology, Dietetics, Quality and Safety Management, Toxicology, Human Nutrition, and International Economics courses.
- Hands-on involvement with the operation and optimization of Sartorius Biostat B Plus Benchtop Bioreactors, focusing on process control: cell viability and purity (can be applied to biopharmaceuticals and genetics).
- Developed strong cross-cultural communication, adaptability, enhancing teamwork and collaboration in various environments.
Internship
Specko
Date: 2022
- Engineered an eco-friendly, cost-effective solution utilizing cellulose aerogels for targeted hormone adsorption reducing material costs by 55% in collaboration with cross-functional teams at CICECO and CESAM, University of Aveiro.
- Integrated knowledge in organic chemistry, biochemistry, analytical chemistry, and materials science for advanced material development.
- Leveraged advanced analytical techniques including PXRD, FTIR-ATR, zeta potential analysis, and N₂ adsorption-desorption isotherms, while applying HPLC for precise separation and analysis of complex mixtures. Demonstrated capability in interpreting data from solid-state NMR, TGA, elemental analysis, and electron microscopy (STEM/TEM/SEM).
Freelance Job
EXCO (Kreston)
Date: 2022
- Led the strategic planning and implementation of core digital infrastructure, encompassing website development, cloud-hosted file management/collaboration, solutions domain management, and email platform integration.
- Substantially optimized the organization's digital presence by establishing an online ecosystem aligned with overarching business goals.
- Demonstrated a good understanding of the industry best practices, facilitating seamless integration of technological components into the digital framework.
- Focused on delivering a professional and cohesive user experience across all digital platforms.
- Effectively contributed to enhanced operational efficiency while reinforcing the company's brand identity within the competitive digital landscape.
MSc in Biomedical Engineering
University of Porto (FEUP & ICBAS)
Date: 2022-2024
- Competencies in Human Anatomy, Tissue Engineering and Regeneration, Biomaterials and Biological System Interfaces supported by knowledge of human anatomical structures and their integration with tissue engineering principles, regenerative medicine techniques, and biomaterials science followed by pratical laboratory applications
- Expertise in Health Technologies, Digital Healthcare Systems, and Healthcare Management, focusing on the integration of technology, healthcare delivery, and strategic management in corporate settings. Experienced in leading the development and deployment of digital health solutions, such as telemedicine, health data analytics, and smart healthcare technologies, while managing interdisciplinary teams, driving innovation, and executing negotiation strategies across healthcare projects.
- Proficient in Methods and Operational Research with specialization in machine learning, deep learning, and computer-assisted diagnostics for healthcare applications, with expertise in designing and implementing diagnostic systems, predictive modeling, and optimizing healthcare operations.
MSc Thesis
FEUP & UNESP
Date: 2023-2024
- Did project planning and cross-team collaboration efforts, coordinating with external research teams for database construction/access using Pandas while aligning with domain clinicians to define key parameters for the diagnosis and severity assessment of Parkinson's Disease from gait parameters.
- Developed workflows using a wide range of libraries (e.g., Scikit-learn, TensorFlow, Keras, PyTorch, NumPy, Pandas, SciPy, Matplotlib, Seaborn..) for data preprocessing, feature engineering (on traditional machine learning), and model development, evaluation and visualization.
- Implemented several traditional machine learning classifiers (RF, DT, SVM (different kernels), NB, LR, KNN) through Scikit-learn, for binary diagnosis and multiclass severity classification. Additionally, and primarily utilizing TensorFlow, with some PyTorch, developed and experimented different architetures encompassing CNNs, LSTMs, and hybrid CNN-LSTM models for these tasks.
- Performed univariate and multivariate feature selection (machine learning pipeline only) to optimize computational efficiency and model performance.
- Conducted a comparative analysis of different breakthrough data augmentation techniques (SMOTE, BORDERLINE-SMOTE, ADASYN, ROS), addressing challenges in model optimization with limited data and exploring their impact on classification performance, with a focus on how their implementation influences model outcomes—a theme of significant relevance in current literature discussions.
Freelance Job
Shopify Private Store
Date: 2024
- Improved the layout and user experience of a private Shopify store through custom CSS enhancements and responsive design adjustments. Focused on optimizing visual aesthetics, site navigation, and overall functionality to enhance user engagement
Relevant Projects and Certificates
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My Approach
Planning & Strategy
First phase involves a deep understanding of the business or research problem, working closely with stakeholders to ensure alignment between objectives and deliverables. Identification of relevant features and patterns are crucial in order to define the appropriate (ML/DL)) techniques, frameworks, and resources based on the problem’s constraints (e.g., computational power, data availability, etc..) alongside ethical implications, fairness and data privacy.
Data Preparation
In this critical second phase, which is often associated with significant time duration, the data—the foundation of any successful project—undergoes extensive preprocessing to ensure it is clean, relevant, and ready for model training. This stage involves several labor-intensive tasks, including data collection, thorough cleaning, feature engineering, and data augmentation, all of which are essential to producing high-quality input for subsequent analysis.
Modeling and Deployment
In this final phase, the focus shifts to building and/or fitting models. It is essential to follow an iterative workflow to develop or select the appropriate architecture, fine-tune its parameters, and then train, test, and evaluate the model's performance. Additionally, the model must be regularly updated and continuously improved to ensure its effectiveness.