Mir Hassan
Research Areas: Federated Learning · Edge Computing · Trustworthy ML · Distributed Systems
PhD Candidate, University of Trento (Italy) · Supervisor: Prof. Giovanni Iacca
📍 Currently based in Trento, Italy
Academic Experience & Teaching
🎓 Currently Teaching: EMAI4EU Program (EIT Digital)
Starting 2025/26 — Teaching cutting-edge AI modules in the European Master in AI program
📚 Two Specialized Modules: Ethics for Trustworthy AI & Introduction to Emotion AI
Current Teaching (2025/26)
🛡️ Ethics for Trustworthy AI
Program: EMAI4EU (EIT Digital)
Format: 1-week intensive sprint
- Principles & frameworks (OECD, HLEG)
- EU AI Act: risk tiers, conformity, documentation
- Bias, robustness, privacy: hands-on assessments
- Accountability & reproducibility in FL/Edge AI
🧠 Introduction to Emotion AI
Program: EMAI4EU (EIT Digital)
Format: 1-week intensive sprint
- Signals: audio, video, physiological sensors
- Dataset design, labels, and leakage prevention
- Edge AI modeling (TinyML, Federated Learning)
- Ethics, consent, and privacy-aware deployment
Student Supervision
Master's Thesis Co-Supervisor
University of Trento, Italy 2024
- Guided research on model compression techniques for resource-constrained FL environments
- Supervised implementation and evaluation of novel compression algorithms
- Mentored student through publication preparation and defense
Teaching Assistant Experience
Computer Architectures (Undergraduate)
University of Trento, Italy 2023-2024
- Conducted hands-on lab sessions on processor design and assembly programming
- Created tutorial materials on pipeline architectures and memory hierarchies
- Evaluated student assignments and provided comprehensive feedback
- Held office hours for one-on-one student consultations
Embedded Software for Internet of Things (Graduate)
University of Trento, Italy 2023-2024
- Supervised capstone projects involving microcontrollers (Arduino, ESP32, Raspberry Pi)
- Guided students in sensor integration and real-time data processing
- Mentored teams on wireless communication protocols (MQTT, CoAP, LoRaWAN)
- Evaluated project demonstrations and technical reports
Visiting Research & Teaching Appointments
Visiting Researcher
Yildiz Technical University, Istanbul, Turkey Apr-Sep 2024, Oct 2023
- Host: Prof. Nihan Kahraman
- Conducted collaborative research on federated learning in edge computing environments
- Delivered guest lectures on privacy-preserving machine learning
- Co-authored research publications with local faculty and students
Specialist (Part-Time)
Dept. of Biomechanical Engineering, Vilnius Tech University, Lithuania May 2022-Aug 2023
- Contributed to research projects on AI applications in biomechanics
- Developed machine learning models for biomedical signal processing
- Collaborated on interdisciplinary research publications
Remote Visiting Researcher
School of Computing Science, University of Glasgow, United Kingdom Jan-Mar 2020
- Conducted research on distributed machine learning systems
- Participated in research seminars and group discussions
- Established international research collaborations
Teaching Philosophy
My teaching approach emphasizes hands-on learning and real-world applications. I believe in bridging the gap between theoretical concepts and practical implementation, especially in rapidly evolving fields like AI and edge computing. Through project-based learning and close mentorship, I help students develop both technical skills and critical thinking abilities needed for research and industry careers.