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At STRATUS Lab, students can participate in research-oriented bachelor’s and master’s theses and internships, working on challenging problems through software development, simulation, experimental evaluation, and hardware prototyping.
Our activities are organized around four research areas. The topics listed below represent broad research directions rather than predefined thesis projects. Specific activities are agreed upon individually based on students’ interests, technical background, and ongoing research.
Secure
Making intelligent and cyber-physical systems safer, more resilient, and verifiable.
Thesis activities may involve identifying vulnerabilities, developing security mechanisms, and experimentally evaluating their effectiveness in connected and cyber-physical systems. Students can also explore advanced cryptographic techniques and methods for assessing the security and robustness of artificial intelligence.
- Cyber-Physical Systems Security
- Post-Quantum Cryptography
- Trustworthy Machine Learning
- Machine Unlearning
Trustless
Building systems where trust is verified rather than assumed.
Students may design and evaluate mechanisms for secure interactions between distributed components, exploring decentralized identity, access control, and verifiable execution. Activities can combine software prototyping, security analysis, and experimental evaluation of architectures that minimize implicit trust.
- Zero-Trust Architectures
- Decentralized Identity
- Trusted Execution Environments
Autonomous
Enabling machines to perceive, learn, reason, and act in the physical world.
Thesis projects may involve developing, training, and evaluating intelligent algorithms through simulation and experimentation with robotic and automotive platforms. Students can explore reinforcement learning, embodied AI, LLMs, and world models, addressing practical challenges in perception, decision-making, and autonomous control.
- Embodied AI
- LLMs for Robotics
- Reinforcement Learning
- Autonomous Driving
- World Models
Ubiquitous
Extending computation from embedded devices to distributed and cloud infrastructures.
Students may design and experimentally evaluate embedded software, reconfigurable computing platforms, and mechanisms for sharing computational resources across distributed systems. Activities can address virtualization, hardware acceleration, and efficient resource management, from resource-constrained devices to cloud infrastructures.
- Embedded AI
- FPGA & Reconfigurable Computing
- RISC-V & Open Hardware
- Distributed Virtualization
- Cloud Continuum
How to Apply
Students interested in a thesis or internship should identify the research areas and topics that best match their interests and contact Prof. Francesco Longo.
When making a request, please indicate your degree programme, academic background, preferred research topics, and expected graduation period.
Thesis topics are defined individually according to students' interests, preparation, and available research opportunities.