Benedetta Picano PhD, Assistant Professor (RTD-A)

Benedetta (Chinese characters 贝尼) received the B.S. degree in Computer Science, as the M.Sc. degree in Computer Engineering, from the University of Florence, where she received the Ph.D. degree in the Department of Information Engineering.

She was a visiting researcher at the University of Houston, at the Prof. Zhu Han’s LAB.

She is a TensorFlow passionate and a Data-scientist-wannabe. As an out-of-the-box thinker, she is committed to using new methodologies and technologies to provide outstanding solutions which meet stringent quality requirements and deadlines.

Her research is in the area of Software Engineering, specifically on solutions involving matching theory and auction theory. Her research fields include nonlinear time seriesanalysis, edge and fog computing architectures supporting digital twin paradigm, and machine learning.

Publication list

[1] Benedetta Picano and Romano Fantacci. “Human-in-the-loop virtual reality offloading scheme in wireless 6G Terahertz networks”. In: Computer Networks 214 (2022), p. 109152. URL: https:/ /www.sciencedirect.com/science/ article/pii/S138912862200264X.

[2] Gabriele Patrizi, Benedetta Picano, Marcantonio Catelani, Romano Fantacci, and Lorenzo Ciani. “Validation of RUL estimation method for battery prognostic under different fast-charging conditions”. In: 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). 2022, pp. 1–6.

[3] Benedetta Picano. “Multi-Sensorial Human Perceptual Experience Model Identifier for Haptics Virtual Reality Services in Tactful Networking”. In: IEEE Access 9 (2021), pp. 147549–147558.

[4] Romano Fantacci, Tommaso Pecorella, Benedetta Picano, and Laura Pierucci. “Martingale Theory Application to the Delay Analysis of a Multi-Hop Aloha NOMA Scheme in Edge Computing Systems”. In: IEEE/ACM Transactions on Networking 29.6 (2021), pp. 2834–2842.

[5] Benedetta Picano. “End-to-End Delay Bound for VR Services in 6G Terahertz Networks with Heterogeneous Traffic and Different Scheduling Policies”. In: Mathematics 9.14 (2021).

[6] Lorenzo Ciani, Marcantonio Catelani, Gabriele Patrizi, and Benedetta Picano. “Remaining Useful Life estimation for Prognostics of Lithium-Ion batteries based on Recurrent Neural Network”. In: IEEE Transactions on Instrumentation and Measurement (2021, In press).

[7] Benedetta Picano, Romano Fantacci, Tommaso Pecorella, and Adnan Rashid. “Federated learning for IoE environments: A service provider revenue maximization framework”. In: ITU Journal on Future and Evolving Technologies 2.5 (2021).

[8] Benedetta Picano, Romano Fantacci, and Zhu Han. “Aging and Delay Analysis based on Lyapunov Optimization and Martingale Theory”. In: IEEE Transactions on Vehicular Technology (2021), pp. 1–1.

[9] Romano Fantacci and Benedetta Picano. “End-to-End Delay Bound for Wireless uVR Services over 6G Terahertz Communications”. In: IEEE Internet of Things Journal (2021), pp. 1–1.

[10] Benedetta Picano and Romano Fantacci. “An Intelligent Radio Buffer-Aided Relaying Scheme With Adaptive Link Selection”. In: IEEE Transactions on Vehicular Technology 70.4 (2021), pp. 3677–3684.

[11] Romano Fantacci and Benedetta Picano. “Performance Analysis of a Delay Constrained Data Offloading Scheme in an Integrated Cloud-Fog-Edge Computing System”. In: IEEE Transactions on Vehicular Technology 69.10 (2020), pp. 12004–12014.

[12] Romano Fantacci and Benedetta Picano. “A Matching Game With Discard Policy for Virtual Machines Placement in Hybrid Cloud-Edge Architecture for Industrial IoT Systems”. In: IEEE Transactions on Industrial Informatics 16.11 (2020), pp. 7046– 7055.

[13] Romano Fantacci and Benedetta Picano. “Federated learning framework for mobile edge computing networks”. In: CAAI Trans. Intell. Technol. 5 (2020), pp. 15–21.

[14] Francesco Chiti, Romano Fantacci, and Benedetta Picano. “A matching game for tasks offloading in integrated edge-fog computing systems”. In: Transactions on Emerging Telecommunications Technologies 31.2 (2020), e3718.

[15] Romano Fantacci and Benedetta Picano. “When Network Slicing Meets Prospect Theory: A Service Provider Revenue Maximization Framework”. In: IEEE Transactions on Vehicular Technology 69.3 (2020), pp. 3179–3189.

[16] Tommaso Pecorella, Romano Fantacci, and Benedetta Picano. “Improving CSI Prediction Accuracy with Deep Echo State Networks in 5G Networks”. In: Sensors 20.22 (2020). URL: https://www.mdpi.com/1424-8220/20/22/6475.

[17] Francesco Chiti, Romano Fantacci, Benedetta Picano, and Laura Pierucci. “A Capacitated House Allocation Game for the Energy Efficient Relays Selection in 5G Multicast Context”. In: Sensors 20.18 (2020). URL: https : / / www . mdpi . com / 1424 - 8220/20/18/5347.

[18] Benedetta Picano, Romano Fantacci, and Zhu Han. “Nonlinear Dynamic Chaos Theory Framework for Passenger Demand Forecasting in Smart City”. In: IEEE Transactions on Vehicular Technology 68.9 (2019), pp. 8533–8545.

[19] Francesco Chiti, Romano Fantacci, Federica Paganelli, and Benedetta Picano. “Virtual Functions Placement With Time Constraints in Fog Computing: A Matching Theory Perspective”. In: IEEE Transactions on Network and Service Management 16.3 (2019), pp. 980–989.

[20] Giulio Bartoli, Francesco Chiti, Romano Fantacci, and Benedetta Picano. “An Efficient Resource Allocation Scheme for Applications in LR-WPANs Based on a Stable Matching With Externalities Approach”.In: IEEE Transactions on Vehicular Technology 68.6 (2019), pp. 5893–5903.

[21] Francesco Chiti, Romano Fantacci, and Benedetta Picano. “A Matching Theory Framework for Tasks Offloading in Fog Computing for IoT Systems”. In: IEEE Internet of Things Journal 5.6 (2018), pp. 5089– 5096.

[22] Benedetta Picano, Romano Fantacci, and Zhu Han. “Price Control for Computational Offloading Services with Chaotic Data”. In: 2020 International Conference on Computing, Networking and Communications (ICNC). 2020, pp. 785–790.

[23] Romano Fantacci and Benedetta Picano. “Performance Analysis of an Edge Computing System for Real Time Computations and Mobile Users”. In: 2019 IEEE Global Communications Conference (GLOBECOM). 2019, pp. 1–6.

[24] Benedetta Picano, Francesco Chiti, Romano Fantacci, and Zhu Han. “Passengers Demand Forecasting Based on Chaos Theory”. In: ICC 2019 - 2019 IEEE International Conference on Communications (ICC). 2019, pp. 1–6.

[25] Giulio Bartoli, Romano Fantacci, Dania Marabissi, and Benedetta Picano. “Efficient Matching for Almost Blank Subframes Allocation in Ultra Dense Networks”. In: 2019 IEEE Wireless Communications and Networking Conference (WCNC). 2019, pp. 1–6.

[26] Francesco Chiti, Romano Fantacci, Benedetta Picano, Yunan Gu, Xunsheng Du, and Zhu Han. “A Low Complexity Matching Game Approach for LTE-Unlicensed”. In: 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall). 2017, pp. 1–5.