Sofia Yfantidou Email & Phone Number

Greece

Early Stage Researcher and Marie Skłodowska-Curie fellow at the Innovative Training Network "Real-time Analytics for the Internet of Sports" (RAIS) in the field of "Human-centered Machine Learning for Mobile Sensing Data".▪ Conducted research and led a team of 3 in the intersection of Human-centered Machine Learning and Human-Computer Interaction for mobile and wearable computing in health and well-being▪ Designed, managed and delivered a real-world, GDPR-compliant data collection study spanning 4 countries over 4 months and 71 users, amounting to 71M data samples, digested into MongoDB▪ Performed exploratory data analysis and visualization of multimodal data in Tableau and Python using Pandas, Matplotlib, Seaborn, Plotly and DataPrep libraries▪ Developed machine and deep learning models for mobile and wearable computing use cases in Python using scikit-learn, PyTorch and Tensorflow and fine-tuned them via TensorBoard▪ Engaged in science communication efforts through publishing webinars, and creating animation explainer videos for the general public▪ Coached and supervised 3 BSc students, 6 MSc students, and 1 PhD student during their thesis work and streamlined the thesis onboarding process for the lab▪ Member of the Data and Web Science Laboratory (Datalab)

Cambridge, England, United Kingdom

Human-centered Machine Learning for personal sensing devices. Tasks include:▪ Specialized in self-supervised learning fairness for mobile and wearable computing, quantifying and mitigating biases across the entire machine learning project’s lifecycle utilizing IBM’s AIF360▪ Conducted a literature review in the unexplored field of mobile and wearable computing fairness

Stockholm, Stockholm County, Sweden

Human Activity Recognition using Deep Learning techniques. Tasks include:▪ Developed deep learning models for Human-Activity Recognition in Python and Tensorflow▪ Performed exploratory analysis of raw sensor, time-series data in Python and Jupyter Notebooks

Berlin Area, Germany

Online anomaly prediction on data streams for the railroad industry. Tasks included:▪ Developed anomaly prediction models on railroad data streams in Python and Keras▪ Extracted data working with libraries from Amazon AWS▪ Performed exploratory data analysis with Python and Tableau▪ Awarded 4 innovation disclosure applications

Thessaloniki

Crowd-sourcing in Social Media (e.g., Twitter, Youtube, etc.) during various Erasmus+ projects in the domain of Digital Sports. Tasks included:▪ Mined social media data via APIs and web scraping (Twitter, YouTube)▪ Simplified data storage and handling on the cloud with NoSQL databases▪ Performed natural language processing and sentiment analysis in Python▪ Developed web platforms for the presentation of research outcomes using Bootstrap

Doctor Of Philosophy - Phd, Computer Science

Master'S Degree, Big Data Management And Analytics (Semester Iii), 1.0/5.0 (1.0 Best)

Scalable Data Science - Management of Heterogeneous Information - Big Data Analytics Project - Big Data Analytics Seminar - Spanish.

Master'S Degree, Big Data Management And Analytics (Semester Ii), 8.12/10.0 (10.0 Best)

Big Data Management - Semantic Data Management - Cloud Computing - Big Data Seminars - Viability of Business Projects - Social and Ethical.

Master'S Degree, Big Data Management And Analytics (Semester I), 18.0/20.0 (20.0 Best)

Advances Databases - Database System Architecture - Data Warehouses - Data Mining - Business Process Management - French Language Course

Bachelor'S Degree, Informatics, 9.47/10.0 (10.0 Best)

Activities and Societies: ACM-W Student Chapter AUTh | START Hack 2017 Top 10 Finalists , St. Gallen, Switzerland.

Erasmus+ Exchange Student, Computing Science, 8.75/10.0 (10.0 Best)

Activities and Societies: Groningen Start-up Weekend