Massimo Stella
Education 

PhD in Complex System Simulation, University of Southampton, UK, 20142018. Focus on cognitive science and psychology. Specialisation School in Complex Systems, Santa Fe Institute, USA, 2014. MSc in Complex Systems Simulation, University of Southampton, UK, 20132014. Focus on cognitive science and psychology. MSc in Fisica, Università del Salento, Italy, 20092011. Final project about mathematical physics, encompassing complex networks and random matrix theory. BSc in Fisica, Università del Salento, Italy, 20062009. Final project about Hopfield networks in computational physics. 

Academic career and teaching activities 

My teaching style combines the mathematical background of a data scientist with the attention to the cognitive processing of a cognitive scientist. During lectures, I boost attention through emotional contagion and promote positive learning environments, which in turn boost creativity and reduce STEM anxiety. Where possible, I use educational technologies to foster student engagement. In 2022, I received an “Excellence in Teaching” award from the College of the University of Exeter for the high quality of my students’ feedback. I have a semester of University training in Pedagogia e Tecniche Didattiche at the Università Dante Alighieri (27 CFU, 2018). In 2022, I completed a 2yrs postgraduate Academic Professional Programme for Teaching in Higher Education (60 CFU, University of Exeter) and became an ASPIRE Fellow for teaching at the University level. For a.y. 2022/2023 I am teaching: Metodi Quantitativi per le Scienze della Vita  9 CFU  CdLT in Scienze e Tecniche di Psicologia Cognitiva (100%). Syllabus: Introduction to computational thinking, Calculus, Probability theory, Vectors and matrices in psychology, Numerical simulations for cognitive scientists. Teorie e Tecniche di Riconoscimento  6 CFU  CdLT in Scienze e Tecniche di Psicologia Cognitiva (50%, with Prof. Nicola De Pisapia). Syllabus: Introduction to artificial neural networks, soft computing, model training and assessment. Previously, my teaching duties included: COM1012 – Data Science Group Project 1 – 15 CFU – BSc in Data Science – 2022, Uni of Exeter  Students’ Feedback: Excellent. Syllabus: Descriptive and inferential statistics, Linear regression, Crossvalidation, humancentric AI for creativity assessment. ECMM447 – Social Networks and Text Analysis – 15 CFU – MSc in Data Science – 2022, Uni of Exeter  Students Feedback: Excellent. Syllabus: Intro to complex networks, Distributions on networks, Semantic network analysis, Latent Dirichlet Allocation, Sentiment Analysis. ECMM466 – Social Networks and Text Analysis – 15 CFU – Professional MSc in Data Science – 2021, Uni of Exeter  Students' Feedback: Excellent. Syllabus: Intro to complex networks, Distributions on networks, Semantic network analysis, Latent Dirichlet Allocation, Sentiment Analysis. COM3012 – Data Science Individual Project 1 – 15 CFU – BSc in Data Science – 2021, University of Exeter – Students' Feedback: Excellent. Syllabus: Coordinator for the final projects of BSc students in Data Science. COM2013 – Data Science Group Project 2 – 15 CFU – BSc in Data Science – 2021, Uni of Exeter – Students’ Feedback: Excellent. Syllabus: Missing data imputation, Crossvalidation, Data ethics, Sentiment analysis on texts, GloVe and similarity in vectorial embeddings. COM1012 – Data Science Group Project 1 – 15 CFU – BSc in Data Science – 2021, Uni of Exeter  Students’ Feedback: Outstanding. Syllabus: Descriptive statistics, Linear regression, Crossvalidation, Forward Flow and creativity assessment, Bias in machine learning. COM2909 – Academic Group Tutorials – University of Exeter. Syllabus: Tutoring students over scientific writing and data visualisation. Android Developer and Lecturer in DataDriven Language Learning. In 2019, at CSC I held a datadriven course on English learning for adults that mixed lectures and Android Apps using gamification to facilitate vocabulary acquisition through phonographic similarities in memory. Guest Lecturer in Machine Learning and Text Analysis (led by Prof. Nicole Beckage), Spring Term, University of Kansas, US (May 2017). Syllabus: Inferential statistics, Stochastic Calculus, Random walks and spectral clustering for cognitive data. Demonstrator in Computer Science, Intelligent Agents and Optimisation, University of Southampton, UK (Feedback: Excellent): aa 2014/2015: Statistical inference, Probability and Bayesian inference, Generalised linear models and Gradient descent methods; aa 2013/2014: Probability and Bayesian inference, Gradient descent methods, Generalised linear models. Physics Teacher. I worked as a Physics expert between June 2012 and May 2013 in Italian high schools with extracurricular projects. 

Research interests 

My research is in artificial psychometrics, e.g. combining AI, network modeling, and psychometrics to measure, infer and understand psychological constructs out of mixed and multivariate data. The weapons of choice in my research endeavors include complex networks, natural language processing, and mathematical methods of data manipulation over discrete structures. The methods I introduced in my research activity include the following quantitative frameworks for investigating and measuring psychological phenomena:
My current research interests aim at bolstering psychometric measures of psychological constructs through complex networks, in synergy with other techniques I learned about during my studies, ranging from network psychometrics to IRT models (which nicely map into Ising models in statistical physics). 

Memberships in societies and scientific committees 

Executive Committee Member of the Complex Systems Society (20212024) Cognitive Science Society (Member since 2021) Psychonomics Society (Member since 2022) Steering Committee Member of the Winter Workshop on Complex Systems series (2016  2019) Alumnus of the Santa Fe Institute (since 2014) 