Dr Giacomo Nalli
| Name | Dr Giacomo Nalli |
|---|---|
| Job title | Lecturer in Computing Science |
| Research institute | |
| Primary appointment | Computer Science |
| Email address | g.nalli@mdx.ac.uk |
| ORCID | https://orcid.org/0000-0002-5667-3429 |
| Contact category | Academic staff |
Biography
Biography I am Lecturer in Computing Science, and Programme Leader in IT&BIS (top up) and Information System (top up) DE.
Teaching Teaching Programme Leader : BSc Information Technology & Business Information Systems (top up) BSc Information Systems (top up) DE Module Leader: CST1330 Information Technology Applications CST3391 Independent Professional Development Portfolio in BCDA CST3395 IT Solution Deployment Planning Previously Programme Leader : BSc Information Technology & Business Information Systems (top up) DE Module Leader : CST3390 Undergraduate Individual Project CST4125 Blockchain Development
Supervision
| Doctoral Researcher | Award | Status | Role | |
|---|---|---|---|---|
| Ariadni Tsiakara | PhD | Enrolled Student | Supervisor | Jan 2024 - Present |
| Mohammad Hashimyar | PhD | Research Project final stages | Supervisor | Jan 2021 - Jan 2026 |
Employment
Lecturer in Computing Science
Middlesex University
03 Mar 2023
Education and qualifications
Grants
Prizes and Awards
Research outputs
Blockchain in e-learning platform to enhance trustworthy and sharing of micro-credentials
Bigiotti, A., Bottoni, M. and Nalli, G. 2024. Blockchain in e-learning platform to enhance trustworthy and sharing of micro-credentials. 36th International Conference on Advanced Information Systems Engineering Workshops. Limassol, Cyprus 03 - 07 Jun 2024 Cham, Switzerland. Springer. https://doi.org/10.1007/978-3-031-61003-5_1Application of machine learning to the learning analytics of the Moodle platform to create heterogeneous groups in on-line courses
Nalli, G., Mostarda, L., Perali, A., Pilati, S. and Amendola, A. 2019. Application of machine learning to the learning analytics of the Moodle platform to create heterogeneous groups in on-line courses. Italian Journal of Educational Research. p. 156–173.Il Blended Learning per migliorare l’efficacia della didattica universitaria: il corso di Computer Ethics
Amendola, D., Nalli, G. and De Vivo, M. 2017. Il Blended Learning per migliorare l’efficacia della didattica universitaria: il corso di Computer Ethics. EMEMITALIA 2017. Bolzano, Italy 30 Aug - 01 Sep 2017 Genova University Press.Tool per la classificazione dei sentimenti degli studenti Implicati in moduli didattici universitari in modalità e-learning
Nalli, G., Amendola, D., Schettini, C. and Galassi, R. 2019. Tool per la classificazione dei sentimenti degli studenti Implicati in moduli didattici universitari in modalità e-learning. MoodleMoot Italia 2019. Verona, Italy 05 - 07 Dec 2019 MediaTouch 2000. pp. 29-32Chatbot per Moodle: un assistente virtuale per i corsi universitari ad alto numero di studenti
Nalli, G. and Amendola, D. 2020. Chatbot per Moodle: un assistente virtuale per i corsi universitari ad alto numero di studenti. MoodleMoot Italia 2020. Online 26 - 28 Nov 2020 MediaTouch 2000. pp. 64-67Online tutoring system for programming courses to improve exam pass rate
Nalli, G., Culmone, R., Perali, A. and Amendola, D. 2023. Online tutoring system for programming courses to improve exam pass rate. Journal of E-Learning and Knowledge Society. 19 (1), pp. 27-35. https://doi.org/10.20368/1971-8829/1135704Machine Learning model for student drop-out prediction based on student engagement
Brezočnik, L., Nalli, G., De Leone, R., Val, S., Podgorelec, V. and Karakatič, S. 2023. Machine Learning model for student drop-out prediction based on student engagement. Karabegovic, I., Kovačević, A. and Mandzuka, S. (ed.) 9th International Conference on New Technologies, Development and Application. Sarajevo, Bosnia and Herzegovina 22 - 24 Jun 2023 Cham Springer. pp. 486–496 https://doi.org/10.1007/978-3-031-31066-9_54Hybrid educational environments – using IoT to detect emotion changes during student interactions
Nalli, G., Dafoulas, G., Tsiakara, A., Langari, B., Mistry, K. and Tahmasebi Aria, F. 2023. Hybrid educational environments – using IoT to detect emotion changes during student interactions. Interaction Design and Architecture(s). 58 (1), pp. 39-52. https://doi.org/10.55612/s-5002-058-001Comparison of the effectiveness and performance of student workgroups in online wiki activities with and without AI
Nalli, G. and Smith, S. 2023. Comparison of the effectiveness and performance of student workgroups in online wiki activities with and without AI. 4th International Electronic Conference on Applied Sciences. Online 27 Oct - 10 Nov 2023 MDPI. https://doi.org/10.3390/ASEC2023-16273Machine-learning-based software to group heterogeneous students for online peer assessment activities
Amendola, D., Nalli, G. and Miceli, C. 2023. Machine-learning-based software to group heterogeneous students for online peer assessment activities. Fulantelli, G., Burgos, D., Casalino, G., Cimitile, M., Lo Bosco, G. and Taibi, D. (ed.) 4th International Conference on Higher Education Learning Methodologies and Technologies Online. Palermo, Italy 21 - 23 Sep 2022 Cham Springer. https://doi.org/10.1007/978-3-031-29800-4_2Artificial Intelligence to improve learning outcomes through online collaborative activities
Nalli, G., Amendola, D. and Smith, S. 2022. Artificial Intelligence to improve learning outcomes through online collaborative activities. Fotaris, P. and Blake, A. (ed.) 21st European Conference on e-Learning. Brighton, UK 27 - 28 Oct 2022 Academic Conferences International (ACI). pp. 475-479 https://doi.org/10.34190/ecel.21.1.661Comparative analysis of clustering algorithms and moodle plugin for creation of student heterogeneous groups in online university courses
Nalli, G., Amendola, D., Perali, A. and Mostarda, L. 2021. Comparative analysis of clustering algorithms and moodle plugin for creation of student heterogeneous groups in online university courses. Applied Sciences. 11. https://doi.org/10.3390/app11135800From anxiety to agency: the DUE learning design model for pre-service teachers facing uncertainty
Capolla, L.M., Giannandrea, L., Gratani, F., Rossi, P.G., Nalli, G., Kapetanakis, S. and Dafoulas, G.A. 2026. From anxiety to agency: the DUE learning design model for pre-service teachers facing uncertainty. Adamoli, M., Amato, D., Schicchi, D., Fulantelli, G., Rondonotti, M., Taibi, D., Ciasullo, A. and Santoianni, F. (ed.) 7th International Conference on Higher Education Learning Methodologies and Technologies Online. Naples, Italy 23 - 25 Sep 2025 Springer. pp. 396-411 https://doi.org/10.1007/978-3-032-31850-3_25A multimodal investigation of learner attention and cognitive load in linear and non-linear educational content
Mistry, K., Dafoulas, G., Nalli, G., Aria, F.T., Langari, B. and Tsiakara, A. 2026. A multimodal investigation of learner attention and cognitive load in linear and non-linear educational content. E-Learning Innovations Journal. 4 (2), pp. 25-47. https://doi.org/10.57125/elij.2026.09.25.02Leveraging generative AI, knowledge graphs and personalised learning paths to improve the learning experience of neurodivergent students in e-learning courses
Nalli, G., Malaise, Y., Kapetanakis, S. and Signer, B. 2026. Leveraging generative AI, knowledge graphs and personalised learning paths to improve the learning experience of neurodivergent students in e-learning courses. Barolli, L., Seah, W.K.G. and Woungang, I. (ed.) 40th International Conference on Advanced Information Networking and Applications. Wellington, New Zealand 08 - 10 Apr 2026 Springer. pp. 231-242 https://doi.org/10.1007/978-3-032-23260-1_20Towards a news authenticity predictor (NAP AI)
Wali, A., Kapetanakis, S. and Nalli, G. 2026. Towards a news authenticity predictor (NAP AI). 6th International Electronic Conference on Applied Sciences. Virtual 09 - 11 Dec 2025 MDPI. https://doi.org/10.3390/engproc2026124089Investigating the VR rollercoaster experience by applying AI models to biometric data
Nalli, G., Dafoulas, G.A., Tsiakara, A., Mistry, K., Walker, B., Margolis, M. and Melton, N. 2026. Investigating the VR rollercoaster experience by applying AI models to biometric data. Palaiahnakote, S., Palit, R., Saraee, M., Atrey, P.K., Bai, X. and Raman, B. (ed.) 1st International Conference on Data Science, Artificial Intelligence and Applications. Dhaka, Bangladesh 18 - 19 Jul 2025 Springer. pp. 429-440 https://doi.org/10.1007/978-3-032-11355-9_30AI and wearable sensors in higher education to investigate public speaking skills
Giannandrea, L., Gratani, F., Capolla, L.M., Dafoulas, G., Tsiakara, A., Kapetanakis, S. and Nalli, G. 2026. AI and wearable sensors in higher education to investigate public speaking skills. Revista de Educación a Distancia (RED). 26 (83). https://doi.org/10.6018/red.670031Predicting London’s precipitation: a spatio-temporal neural network approach
Zafar, H., Kapetanakis, S., Nalli, G. and Nguyen, K. 2025. Predicting London’s precipitation: a spatio-temporal neural network approach. Bramer, M. and Stahl, F. (ed.) 45th SGAI International Conference on Artificial Intelligence. Cambridge, UK 16 - 18 Dec 2025 Springer. pp. 179-189 https://doi.org/10.1007/978-3-032-11442-6_13Towards a systematic approach to memory safety: a case study integrating techniques and practices over the software development life cycle (SDLC)
Tonini, I., Nalli, G., Piras, L., De Matteis, P., Kapetanakis, S. and Ranise, S. 2025. Towards a systematic approach to memory safety: a case study integrating techniques and practices over the software development life cycle (SDLC). Barolli, L., Ishida, T. and Dantas, M. (ed.) 20th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing. Sharjah, United Arab Emirates 12 - 14 Nov 2025 Springer. pp. 147-159 https://doi.org/10.1007/978-3-032-10344-4_14CodeTutor: personalized programming learning through automated feedback and clustering
Mogianesi, L., Amendola, D., Culmone, R. and Nalli, G. 2025. CodeTutor: personalized programming learning through automated feedback and clustering. De Santis, A., Caldirola, E. and Carretta, P. (ed.) 2024 Italian Symposium on Digital Education. University of Pavia, Italy 19 - 21 Jun 2024 Pearson. pp. 454-459AI intelligent tutoring system tailored to the students’ personality and neurodiversity
Nalli, G., Kapetanakis, S. and Nguyen, K.A. 2025. AI intelligent tutoring system tailored to the students’ personality and neurodiversity. 24th European Conference on e‑Learning. Technical University of Denmark (DTU), Denmark 23 - 24 Oct 2025 Academic Conferences International (ACI). https://doi.org/10.34190/ecel.24.1.3792Pre-service teachers and public speaking anxiety. Insights and possible interventions through AI and IoT
Giannandrea, L., Capolla, L.M., Gratani, F., Nalli, G. and Kapetanakis, S. 2025. Pre-service teachers and public speaking anxiety. Insights and possible interventions through AI and IoT. Ardimento, P., Di Fuccio, R., Fulantelli, G., Pecori, R., Raviolo, P., Rondonotti, M., Schicchi, D., Taibi, D. and Zaza, G. (ed.) 6th International Conference on Higher Education Learning Methodologies and Technologies Online. Rome, Italy 25 - 27 Sep 2024 Cham, Switzerland Springer. pp. 120-133 https://doi.org/10.1007/978-3-031-93999-0_8Leveraging digital twin technology for traffic optimization: a pathway to sustainable urban transportation
Basheer, Z., Karthick, S., Pichhika, H.-C., Yerra, R.V.P., Venkataraman, H., Shah, P., Nalli, G., Trestian, R. and Comsa, I.-S. 2025. Leveraging digital twin technology for traffic optimization: a pathway to sustainable urban transportation. 20th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting. Dublin, Ireland 11 - 13 Jun 2025 IEEE. https://doi.org/10.1109/BMSB65076.2025.11165643Signature-based security analysis and detection of IoT threats in advanced message queuing protocol
Hashimyar, M.E., Aiash, M., Khoshkholghi, A. and Nalli, G. 2025. Signature-based security analysis and detection of IoT threats in advanced message queuing protocol. Network. 5 (1). https://doi.org/10.3390/network5010005Online application for the early detection of students at risk of failing through Artificial Intelligence
Nalli, G., Marconi, A., Karakatič, S., Brezočnik, L., Montagna, A., Amendola, D. and De Leone, R. 2024. Online application for the early detection of students at risk of failing through Artificial Intelligence. Minerva, T. and De Santis, A. (ed.) 2023 Italian Symposium on Digital Education. Reggio Emilia, Italy 13 - 15 Sep 2023 Pearson. pp. 56-624315
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