Central for Applied Research and Development (CARD)

Call for Application in Erasmus Learner Mobility Program at University of Sannio, Italy

2025-05-29

Central for Applied Research and Development

The Institute of Engineering, in collaboration with the University of Sannio, Benevento, Italy (https://www.unisannio.it/en), under the Erasmus Learner Mobility Project KA1712022, invites applications from graduate students of Pulchowk Campus to conduct research at the University of Sannio. The program includes support for travel and living expenses. Graduate students will gain global exposure, an exceptional learning environment, and the opportunity to work in world-class laboratories alongside renowned professors.

Students currently pursuing or planning to pursue research in areas closely related to instrumentation and the activities listed below are eligible to apply. Interested candidates are encouraged to prepare their proposals based on the following research activities at Prof. Pasquale Daponte’s laboratory.

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1. Marker-based vision system for static and dynamic tests for civil infrastructures
Co-supervisors: Eulalia Balestrieri and Francesco Picariello

Structural health monitoring is essential for maintaining the safety and durability of civil infrastructure such as bridges, buildings, and historic structures. These systems are exposed to static and dynamic loads, including environmental factors, traffic, and seismic events, that can lead to deterioration or failure. Recent advances focus on low-cost, non-contact technologies using marker-based tracking enhanced by deep learning. These systems enable precise measurement of displacements and rotations in both static and dynamic tests. Applied to scaled models and real structures, this approach supports early damage detection, informed maintenance, and improved resilience, marking a key step toward smart, data-driven infrastructure management.
Reference to the application context: https://ieeexplore.ieee.org/document/10721566

2. Methods for detection of damages and eavesdropping in data cables
Co-supervisors: Luca De Vito and Francesco Picariello

The aim of the work is the development of a microcontroller-based instrument for the detection of anomalies (damages or taps) in data cables, by analysing the amplitude histogram of the received signal. The work required programming of 32-bit microcontrollers (STM32) in C language.

Reference to the application context: https://ieeexplore.ieee.org/abstract/document/10884898

3. Characterizing resilience of GNSS synchronization to jamming and spoofing (Luca)
Co-supervisors: Luca De Vito and Ioan Tudosa

The objective of this work is to characterize the resilience of GNSS receivers to jamming and spoofing. It consists of generating proper interfering waveforms and verifying the eventual loss of time synchronization accuracy of the GNSS receiver due to the interference. Waveform should be generated on a personal computer in MATLAB and downloaded to a RF signal generator. MATLAB programming for automatic instrumentation control is required.

4. Experiment server for a network of extended reality laboratories
Supervisor: Luca De Vito

The aim of this work is to develop an experiment server for a remote laboratory supporting the remote control of instrumentation via several interfaces, such as HTTP, VNC, Remote Desktop or LXI. The work needs web development in javascript.

5. Optimizing Fatigue Level Estimation Through Multi-Source Measurements and Efficient Classification
Co-supervisors: Ioan Tudosa and Francesco Picariello

Abstract:
This activity focuses on the analysis of physiological and motion-related measurements to estimate muscle fatigue levels in assembly line operators. The student will work with datasets containing electromyography (EMG), electrocardiography (ECG), and orientation measurements, and will implement machine learning classifiers to infer fatigue levels. A key aspect of the activity is to explore how the performance of different classification algorithms varies depending on the combination and number of input measurements. The ultimate goal is to identify the most informative and minimal set of measurements that allows accurate fatigue estimation with low computational overhead, enabling quasi-real-time deployment in industrial settings. Special attention will be given to evaluating trade-offs between accuracy, latency, and the complexity of the acquired measurements.

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Eligibility and Required Documents
Support seeking applicants must be enrolled in any Master’s degree program within IOE, TU. Interested candidates should submit this google form with the mentioned documents by 30th June, 2025.

Selection
The selection procedure among the number of applicants will be based on the merits of their scores obtained on their study program and the quality of the proposal submitted. The proposal will be directly evaluated by a team comprising of members from the University of Sannio, Benevento, Italy and IoE.

For confusion, please contact
Asst. Prof. Dr. Basanta Joshi (basanta@ioe.edu.np)

Call for Application in Erasmus Learner Mobility Program at University of Sannio, Italy

Call for Application in Erasmus Learner Mobility Program at University of Sannio, Italy

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