PhD students - cycle 39

Mars is a key target for astrobiological research because of its complex history and potential for harboring signs of extinct or extant life. This possibility drives current and future exploration missions, such as ESA’s ExoMars program and NASA's Mars 2020 mission, which aim to detect the ancient biosignatures that may be preserved in Martian rocks. However, rover payload instruments face severe technical limitations imposed by the environment and flight requirements. The aim of this work is to support the interpretation of Martian surface and subsurface samples, providing data that may help assess analytical strategies for biosignature detection on the planet. To this end, synthetic and natural terrestrial analogues, selected to be representative of Oxia Planum and Jezero Crater surface materials, were characterized using multiple spectroscopic techniques, including infrared, visible Raman, deep-UV Raman and fluorescence, X-ray fluorescence and X-ray diffraction. To provide directly comparable data, some of the employed instruments were analogous to those used on board the ESA ExoMars Rosalind Franklin rover and the NASA Mars 2020 Perseverance rover. This approach contributes to a more robust interpretation of Martian samples and to the evaluation of biosignature detection capabilities in support of current and future Mars exploration missions.

During my PhD, under the supervision of my thesis advisor Prof. Celletti, my supervisor Prof. Lhotka and my co-supervisor Prof. Locatelli, I have focused my research on two main projects: "Heteroclinic connections of first-order MMRs and the chaotic transport of small bodies in the Sun-Jupiter system", in collaboration with Prof. Efthymiopoulos, and "Effective stability estimates close to resonances with applications to rotational dynamics", in collaboration with Prof. Celletti and Anargyros Dogkas, a PhD student at the University of Pisa. With Prof. Efthymiopoulos, we investigate the heteroclinic connections between resonant periodic orbits in a Sun-Jupiter model. We detect direct connections between different types of resonances, which can be useful, for example, for constructing low-energy transfers. On the other hand, it is difficult to obtain stability results for resonances, or close to them, over long periods of time, since instability phenomena can manifest over short or long time scales. In the second work, we propose a procedure to analyze stability in the vicinity of resonances and maximize the stability time through an optimization algorithm, demonstrating its effectiveness and applicability to relevant astronomical systems. Finally, I am currently working with Prof. Guardia on an instability mechanism called Arnold Diffusion in celestial mechanics. Understanding these mechanisms allows us to better model chaotic behavior and predict long-term orbital evolution.

This PhD work focuses on two projects based on the same technology, i.e. plastic scintillators coupled to Silicon Photomultipliers (SiPMs): a compact Radiation Monitor (RadMon) and the Anti-Coincidence Detector (ACD) of the ADAPT mission.
The RadMon is designed to characterize the charged particle background of the LISA mission, whose test mass charging can mimic gravitational wave signals. It measures the integral flux in orbit through a telescopic stack of four scintillator modules and three Cu/W absorbers, read out by the BETA ASIC developed at ICCUB. A prototype was tested in beam tests with low and high energy protons, while during a six-month period at ICCUB the electronics and the sensors of both this prototype and HECTOR, its in-orbit demonstrator, were studied. The response of both detectors is investigated through dedicated Geant4 simulations.
ADAPT, a NASA suborbital mission flying over Antarctica in 2026-2027, will validate key technologies for APT, a future space-based γ-ray telescope. Its segmented ACD, made of plastic scintillator tiles read out by SiPM edge-carrier boards, rejects the charged-particle and atmospheric background. The work covered the single-tile design, validated through beam tests, and the scaling-up of the detector: production, assembly and test of a full quadrant, and finally the construction of the complete ACD, successfully integrated with the rest of the instrument.

The processes responsible for galaxy evolution produce systematic variations between different galaxy properties. The stars in a galaxy encode its evolutionary history like an archaeological record. Mean stellar ages and metallicities scale with galaxy mass, providing fundamental constraints to characterise galaxy evolution. We derived relations of stellar age and metallicity with stellar mass using the largest dataset of Local Universe galaxies from the Sloan Digital Sky Survey (SDSS). We implemented state-of-the-art Stellar Population Synthesis (SPS) models, alongside unprecedented corrections for SDSS aperture-bias. We characterised systematics across different SPS assumptions providing reference scaling relations in the Local Universe. We analysed the dependence of our relations on galaxies' star formation activity. Current progress extends this by analysing the mass-metallicity relation across finer bins of star formation activity. To gain deeper insights about chemical evolution, ongoing work implements SPS models with variable abundance patterns. Our scaling relations  are in agreement with higher redshift studies (z~0.7) and provide fundamental observational constraints for theoretical models of galaxy formation and evolution. Our scaling relations establish a local benchmark to explore the processes governing the baryon cycle, paving the way for comparisons with upcoming data from higher-redshift spectroscopic surveys (e.g., WEAVE-StePs, 4MOST-StePs, MOONRISE).

My PhD research focuses on the design, fabrication, and experimental validation of hierarchical micro- and nanostructured surfaces for phase-change control, with applications in anti-frosting, dew harvesting, anti-icing for UAVs, and condensation heat transfer. Using photolithography and tapered reactive ion etching at Fondazione Bruno Kessler, we developed microcone and microgroove architectures combined with tailored nano-coatings to manipulate droplet nucleation, coalescence, and detachment. For anti-frosting, we demonstrated that truncated microcones enabling Single Droplet Self-Ejection significantly reduce frost propagation velocity by suppressing ice-bridging events, approaching an order-of-magnitude improvement over state-of-the-art passive surfaces. For dew harvesting, cactus-inspired microgrooves with hydrophilic nano-coatings promote Laplace-driven distant coalescence and rapid droplet shedding, enhancing collected yield and reducing retention. In collaboration with terraXcube@EURAC, I conducted extensive centrifugal adhesion tests on micro-structured surfaces applied to UAV propellers, achieving ice adhesion strengths below 20 kPa, a key threshold for passive de-icing. Current work includes statistical modeling, fracture-mechanics-based interpretation of detachment mechanisms, and the development of nanostructured flexible replicas to extend performance toward scalable, energy-efficient thermal management systems.

In recent decades, large-scale Earth Observation (EO) data have been generated from multiple sensors at different spatial and temporal resolutions. However, the use of these data for informing economic policies related to inclusion, competitiveness, and socio-economic and environmental resilience remains limited. On the one hand, the high computational requirements associated with processing EO data, coupled with the costs of data acquisition and infrastructure, have hindered their widespread use in economic and policy analysis. On the other hand, the lack of effective translation of EO data into tools that are accessible and relevant for economic analysis has further widened this gap.
This research aims to bridge this divide by developing new methods to integrate EO data into economic and policy analysis, with a particular focus on urbanization and environmental resilience.
Rapid urbanization in many developing countries across Africa and Asia, combined with weak urban infrastructure and inadequate planning, has led to the proliferation of informal settlements, commonly referred to as slums. Addressing this phenomenon requires policymakers to adopt effective urban planning strategies and proactive measures to ensure sustainable urban growth. Effective urban planning depends on consistent, reliable, and up-to-date information about the location and expansion of informal settlements. This research begins by developing scalable, reliable, and reproducible methods to detect informal settlements in areas with limited ground-truth data. And to further use the econometrics techniques to understand the spatial dynamics and economic consequences of informal settlements.

My work focuses on the development of artificial intelligence algorithms for space data analysis. I specialize in machine learning techniques applied to both in situ measurements and numerical simulations, with particular emphasis on velocity distribution functions. These distributions contain fundamental information about kinetic processes in space plasmas. I aim to design efficient models to automatically characterize the structure and complexity of these distributions. By quantifying deviations from local thermodynamic equilibrium, the algorithms identify regions associated with relevant physical processes, including shocks, turbulence, and magnetic reconnection. This approach enables automated selection of regions of interest in the data, reducing reliance on manual inspection and maximizing onboard memory usage. A key objective of my research is to ensure that these methods are optimized to operate directly onboard future spacecraft, where computational resources are limited. 

My research focuses on planetary geophysics, with the objective of constraining the internal structure of planetary bodies through gravity field analysis. Analysing the gravity field and corresponding gravity anomalies, I investigate the distribution of mass within the interior, decomposing the relative contributions of the internal differentiation (e.g. core-mantle-crust or potential subsurface oceans). My current work focus mainly on Mercury and Ganymede, prime targets of ESA’s BepiColombo and JUICE missions, respectively. For these purposes, I developed an algorithm, called SynthGen, which compute the gravitational response of a custom planetary physically self-consistent interior model and assess the most probable internal structure compared to the observed real data. In parallel, I apply the Spherical Iterative Filtering (SIF) method to perform spectral separation of gravity signals at different spatial scales, enabling a data-driven discrimination between deep and shallow sources without imposing any priori assumptions. This approach is particularly effective for the icy moons characterization, being able to distinguish the rocky interior from the overlying hydrosphere, and eventually, the subsurface ocean.

This PhD research project focuses on the design and optimisation of a W-band Folded Waveguide Travelling Wave Tube (FW-TWT) for space applications, operating at very low voltage and current conditions. While initial investigations were in the 95-100 GHz range, the activity was subsequently redirected to the 86–92 GHz band, which is currently more required for space and high-data-rate applications and offers improved manufacturability. Starting from a conventional FW configuration characterised by an interaction impedance of approximately 4 Ω at the centre frequency, several variations of the fundamental cell were investigated through eigenmode dispersion analysis and Particle-In-Cell (PIC) simulations. The optimised designs achieved interaction impedance values up to 5 Ω, corresponding to a 25% improvement maintained across the entire 86–92 GHz band. This enhancement enables higher gain and efficiency while allowing operation at reduced beam voltage. Comparative studies were conducted between circular and sheet electron beams. The sheet-beam configuration showed better performance, significantly reducing the total number of periods and increasing electronic efficiency from 24% to 27%. A key objective is operation at 10–11 kV, which is a significant achievement for FW TWTs in this frequency range. A MATLAB-based regression model was developed to quantify performance degradation under geometric tolerances. The best-performing configuration will be fabricated as a single-section prototype and experimentally validated through cold measurements. Future activities will include the design of a Periodic Permanent Magnet (PPM) focusing system and a dedicated electron gun.

Particles at the highest end of the cosmic-ray spectrum (E > 1 EeV) are known as ultra-high-energy cosmic rays (UHECRs). Even more than 60 years after their discovery, the origin of these particles remains a mystery. The Pierre Auger Observatory and the Telescope Array are the current generation of observatories responsible for detecting such particles on Earth, providing valuable information about their energy spectrum, arrival direction distribution, and mass composition. 
From an observational point of view, starburst galaxies (SBGs) are interesting environments for studying the propagation of UHECRs, since the Pierre Auger Collaboration has reported a correlation between the arrival directions of events above 39 EeV and the directions of some starburst galaxies. From a theoretical perspective, ultra-fast outflows (UFOs) from active galactic nuclei have recently emerged as promising candidates for accelerating particles, mainly below the ankle of the cosmic ray spectrum.
This work is structured around distinct research projects, focusing on both the acceleration and propagation of UHECRs. In the case of UFOs, the acceleration of nuclei up to the highest energies was investigated, taking into account both acceleration and energy losses in simulations performed using the framework CRPropa. On the other hand, the energy spectrum and mass composition of UHECRs originating from the same set of SBGs considered in the reported correlation analysis were also studied.

My research explores the complex dynamics of the solar photosphere, focusing on two core areas: the mechanisms linking the Sun's global dynamo to small-scale magnetic variability, and advanced space weather applications.
A central part of my ongoing work involves leveraging continuous satellite observations to detect and track small-scale magnetic structures across the solar surface. Through large-scale statistical analysis, my research investigates how the global solar dynamo modulates the evolution and dynamics of these localized magnetic fields. In parallel, I study photospheric wave spectra and umbral oscillations to better understand energy transport in the solar atmosphere.
Equally central to my PhD is the study of solar flares and their predictability. I actively work on space weather forecasting by contributing to the creation of comprehensive archival solar flare catalogs and developing novel deep learning models for robust flare prediction. Ultimately, my research aims to bridge the gap between microscopic plasma dynamics, macroscopic space weather events, and global solar behavior.

My research activity mainly focuses on constraining astrophysical and cosmological parameters through gravitational wave (GW) data. GWs are typically emitted by coalescing binary black holes (BBHs) and I have been working on modelling their merger rate since the beginning of my PhD. Specifically, I am developing a parametric model that integrates results of galaxy evolution and population synthesis codes. This allows to have a tight control over the involved astrophysical parameters. The current goal is to fit this model to GW data, to investigate the influence of metallicity on the BBH mergers and to estimate the contribution of different BBH formation channels.
Alongside this, with the aim of deepening my knowledge in galaxy evolution, I have been involved in a project developing a semi-empirical framework to study the evolution of the progenitors of local quiescent galaxies. Since these systems could host a significant number of GW events, a detailed understanding of their cosmic history can have a meaningful impact on GW science.
I am also a member of the GW working group of the Square Kilometre Array Observatory (SKAO) experiment. My goal is to study how maps of GW events cross-correlate with SKA galaxy surveys to analyse the clustering properties of BBHs.

Thanks to the data collected in situ by the Perseverance rover on the delta in martian crater Jezero, we now know more about the stratigraphy, geomorphology and sedimentology of this delta. This in situ data can be coupled to high resolution orbital imagery to have a broad vision of the sedimentary structure. The idea of this PhD is to have a look at other deltaic deposits on Mars for which we only have orbital data with a new perspective thanks to what was understood in Jezero, and see if the type of delta that emplaced in this crater - a Gilber-type delta, formed in deep water lake - is the predominant architecture on Mars. The results so far of this research have shown that there are other types of deltas on Mars; the Eberswalde delta for instance, emplaced in shallow water settings, as a shoal-water type delta. All of this gives us insights regarding the availability of liquid water at the surface of Mars in the distant past. The final aim of the thesis is to establish a sedimentological classification of martian deltas. To implement this study, a work on terrestrial analogues is also performed, with for instance a field trip that was conducted in Greece, to study Gilbert-type and shoal-water type deltas, to better understand the sedimentological distinctions between the two delta types.
 

My PhD research investigates turbulence characteristics in space weather phenomena, with a particular focus on coronal mass ejections (CMEs). I employ a combined framework of Empirical Mode Decomposition (EMD) and Hilbert Spectral Analysis (HSA) to analyse nonlinear CME signals. This approach decomposes CME time series into intrinsic mode functions (IMFs), ordered from high to low frequencies. Applying the Hilbert transform to each IMF yields instantaneous amplitudes and frequencies, enabling the construction of Hilbert spectra. These spectra facilitate the study of key CME properties—such as amplitude, power, intermittency, and helicity—as functions of both time and frequency.

The analysis is extended using multi-spacecraft observations, providing a unique opportunity to examine CME evolution across different heliocentric distances. Data from NASA’s ACE spacecraft (1 sec resolution at 1 AU) and Solar Orbiter (0.0156 sec resolution at 0.37 AU) are used to investigate the spatial and temporal variability of turbulence during CME propagation in interplanetary space. A further component of this work incorporates higher-order turbulence spectra to examine intermittency and multiscaling behaviour, offering deeper insight into nonlinear energy transfer processes.

Overall, this framework combines the EMD–HSA methodology with multiple CME parameters, evolutionary stages, multi-spacecraft observations, and higher-order spectral diagnostics to advance our understanding of CME turbulence and dynamics.

I hold a Master’s degree in Physics with a specialization in Particle Physics and I am currently pursuing a PhD focused on the characterization of the readout chain of the LiteBIRD satellite mission. The project targets high-precision mapping of the microwave sky at tens of GHz through advanced superconducting detector and cryogenic technologies. Its primary scientific goal is the precise measurement of polarization anisotropies in the Cosmic Microwave Background, a key observable that can shed light on the earliest moments of the Universe and probe physics at extremely high energy scales.
My research spans detector physics, cryogenics, superconducting electronics, low noise measurements techniques, and also includes space qualification aspects such as environmental and functional testing of instrumentation. If I am not easy to reach, chances are I am in the lab.

In this research project, slope instability processes on Mars are investigated through a multi-scale geomorphological and geotechnical approach integrating orbital and rover-derived datasets. At the regional scale, landslide susceptibility mapping is conducted in Valles Marineris region using geomorphological and morphometric parameters derived from digital elevation data acquired by the Mars Orbiter Laser Altimeter (MOLA) onboard Mars Global Surveyor (MGS), allowing the identification of areas potentially affected by mass wasting processes and the recognition of large-scale geomorphological patterns. At the local scale, slope stability analyses of a landslide in Iani Chaos region are performed using high-resolution orbital datasets acquired by the Context Camera (CTX) and High Resolution Imaging Science Experiment (HiRISE) instruments onboard Mars Reconnaissance Orbiter (MRO) together with reconstructed two-dimensional models that allow a detailed characterization of slope stability and morphological features. Rock mass investigations are carried out in Gale Crater using images acquired by the Curiosity rover and three-dimensional reconstructions derived from rover observations. The integration of datasets acquired at different spatial scales provides a consistent framework for investigating slope processes on Mars and contributes to a better understanding of landscape evolution on planetary surfaces.

Space research provides a unique opportunity to understand human physiology by revealing how the body adapts when the fundamental environmental constrain of gravity is altered. My aim is to investigate how microgravity reshapes sensorimotor function, and focus on the underlying neural mechanisms.
First, I contributed to research on visual and vestibular estimates of vertical motion duration on Earth, establishing gravity as a perceptual reference. Extending the investigations to spaceflight, I’m working directly with a dataset of NASA astronauts to examine the recalibration of internal models of gravity during missions, using motor imagery paradigms conducted before, during, and after flight aboard the International Space Station.
I’ve also explored adaptation beyond behavioral performance. As a visiting researcher at LEIA (University of Antwerp), I worked with a unique dataset of cosmonauts who completed four different and complementary space experiments, integrating functional brain connectivity, vestibular function, gait, and balance to characterize post-flight recovery as a coordinated, multilevel process.
Lastly, the space-derived insights are being translated to clinical research, uncovering previously unexamined alterations in functional connectivity networks in patients diagnosed with Mal de Débarquement Syndrome. 
By shifting research beyond Earth, space science opens new perspectives for both fundamental discovery and translational impact in human health.

The focus of my PhD is the study of astronomical radio transients, with particular attention to the exciting field of fast radio bursts (FRBs). 

During my PhD, I used all the Italian radio telescopes to investigate the nature of FRBs, collecting more than 2000 hours with the Northern Cross transit radio telescope and a total of ~200 hours with the single dishes of Medicina, Noto and Sardinia Radio Telescope.

Moreover, I am the principal investigator of an accepted proposal with the MeerKAT radio telescope located in South Africa that will observe the globular clusters in the galaxy Centaurus A looking for FRBs.

I also collaborated with foreign universities such as the University of Bielefeld (where I spent one month), working on a pipeline for the detection of pulsars in the Galactic globular cluster NGC 6624, and the University of Oxford (where I will spend 6 months) exploring the cutting-edge field of long period transients (LPTs) using the MeerKAT radio telescope.

Both FRBs and LPTs signals have been recently discovered (in 2007 and 2021, respectively) thanks to the development of new telescopes and computing capabilities.

This growing field will be supported, in the next years, by the deployment of new amazing observatories (such as CHORD and SKAO) that will deeply investigate the radio astronomy domain and revolutionize our understanding of different phenomena in the Universe.

My PhD research investigates the dynamics of geomagnetic storms and the energy transfer from the solar wind to Earth's magnetosphere. Traditional models often struggle to capture the causal mechanisms driving these extreme events. To address this, I combine causal analysis with physics-informed machine learning.

First, I apply an information-theory approach using the Liang information flow. By analyzing a set of geomagnetic storms, I tested several solar wind-magnetosphere coupling functions, showing that those representing magnetic flux opening at the magnetopause exert the strongest causal influence on the ring current. This provides a solid physical basis for selecting solar wind drivers (Lacal et al., in preparation).

Second, I develop Physics-Informed Neural Networks (PINNs) to model geomagnetic disturbances. I modeled the SMR index during the severe May 2024 Gannon storm with this technique. By embedding physical equations into the neural network, these PINNs successfully reproduce the storm dynamics. Furthermore, this method yields valuable physical insights into the underlying processes, which can help improve current forecasting models (Lacal et al., submitted).

Ultimately, my research bridges space physics and artificial intelligence. By identifying key physical drivers and integrating physical laws into deep learning, I aim to build interpretable models to advance space weather prediction.

My research aims at developing innovative antenna array architectures and synthesis methods for long-range wireless power transmission (WPT), with a broad range of  applications including space-based solar power systems, satellite platforms, and distributed energy networks. The main objective is to maximize the fraction of transmitted power effectively collected by a remote receiver while ensuring scalability and architectural simplicity of the transmitting system. During the first phase of my PhD, I focused on the survey of state-of-the-art literature about the useful array architecture for WPT and the key performance indicators to be considered in the synthesis phased. Afterwards, I developed a modular “domino-tiled” array synthesis approach, where the antenna aperture is partitioned into optimized subarrays in order to maximize the Beam Collection Efficiency (BCE). Numerical validations demonstrated that tiled configurations can achieve performance very close to ideal/fully populated array solution while reducing the number of required control points (i.e., amplifiers and phase shifters) by up to 50%. The current phase of my research investigates Time-Modulated Arrays (TMAs), which introduce controlled on/off switching to dynamically reshape the radiated field, thus also generating multiple simultaneous beams. A multi-objective optimization framework has been implemented for the TMA synthesis to enable adaptive and multibeam power delivery using a single aperture. Overall, my work contributes to the design of scalable, programmable, and energy-efficient antenna systems for next-generation WPT systems and applications.

My research focuses on the astrophysics of extreme mass ratio inspirals (EMRIs), which occur when a small compact object (a stellar-mass black hole or neutron star) orbits and gradually spirals into a massive black hole at the center of a galaxy. These systems produce gravitational waves, ripples in spacetime, making EMRIs key targets for the upcoming Laser Interferometer Space Antenna (LISA) mission. I use a combination of numerical simulations and theoretical modeling to study how EMRIs form and evolve in dense star clusters around central black holes, accounting for both stellar interactions and relativistic effects. I investigate how orbital parameters, cluster dynamics, and black hole properties shape EMRI formation and characteristics, providing realistic predictions for their detectability. Additionally, I characterize EMRI populations and parameter distributions to guide waveform modeling, support the LISA data analysis community, and enable robust interpretation of future gravitational-wave observations. My work connects the astrophysical formation of EMRIs to the signals we will observe, advancing our understanding of black holes and the structure of galactic nuclei. I carry out my research at the University of Milano-Bicocca.

Near-space is the atmospheric region between the upper troposphere and the Kármán Line. Although inaccessible to conventional aircraft and unsuitable for satellites, it can be reached by high-altitude balloons. Above 30 km, environmental conditions approach those experienced by satellites LEO and VLEO, including reduced atmospheric heat exchange, exposure to the full solar spectrum, and minimal attenuation for space observations. These characteristics make near-space a valuable environment for technology demonstration, remote sensing, and component qualification.
This research focuses on attitude control for miniaturised platforms. The work contributes to the development of µHAPS, a balloon-borne stratospheric platform by SpaceLab (University of Pisa), which provides active attitude stabilisation in the 20–40 km altitude range. A prototype integrating a reaction-wheel-based control system, telemetry, and environmental sensing was successfully flown, demonstrating initial azimuth stabilisation and providing flight data. A dynamic model of the balloon launch chain to simulate disturbances and evaluate control strategies is being developed.
In parallel, the research contributes to the attitude determination and control subsystem of the EXCITE CubeSat mission, a 12U CubeSat mission for IOV/IOD of five innovative technologies. µHAPS platform is also conceived as a cost-effective testbed for validation and qualification of CubeSat components in a relevant near-space environment.

Francesco Marzari’s research focuses on micrometric engineering in challenging environments, applied first to the release and launch lock mechanism of LISA. He tested a breadboard model to characterize the trajectory of the mechanism end effector and the friction and wear of its guiding system. These results helped establish the design baseline for the engineering model of the mechanism addressing the release anomalies observed in the LISA Pathfinder mission. Focusing on the release dynamics, he investigated the adhesion impulses from abrupt separation of preloaded metallic surfaces in vacuum. The technique used to measure the impulse amplitude and duration leverages the multi-mode steady-state response characteristics of the released body, combining experimental data with finite element model and optimal filtering approaches. He contributed to extending this approach to the development and experimental validation of a multi-vibration mode framework for impact force reconstruction in dynamical systems. The modes collectively encode information about the shape, the amplitude and duration of the impacting force. Leveraging the analogies between space engineering and synchrotron science, he is currently working at the Lawrence Berkeley National Laboratory with the Advanced Light Source Photon Science Development Group to adapt and extend his mechatronics research tools to the development of X-ray monolithic piezoelectric bimorph mirrors.

My research examines the transformation of commercial space activities and its implications for contract law and risk governance. In contemporary space activities, risk is no longer episodic or peripheral: it is structural. Launch failures, orbital congestion, space debris, cybersecurity threats, and dual-use infrastructures create a complex risk environment in which private operators, governments, and defense actors are tightly interconnected.

My research argues that commercial space contracts must be reconceptualized as instruments of systemic risk governance rather than mere transactional tools. The allocation of risk, the design of liability clauses, the regulation of acceptance and transfer of risk, and the incorporation of preventive obligations (particularly in relation to STM) play a central role in ensuring resilience and sustainability. Special attention is devoted to the legal limits of risk-transfer clauses, the structural nature of contractual alea, and the hybrid configuration of space contracts, which integrate manufacturing, launch, and in-orbit operations.

By combining civil law analysis, comparative perspectives with common law systems, and broader theories of risk governance, the project contributes to an emerging understanding of contractual architecture as a key component of space governance. The research seeks to clarify how private law mechanisms can support secure, accountable, and sustainable space activities in an era of rapid commercialization and strategic interdependence.

This research addresses the chemical erosion of spacecraft materials in Low Earth Orbit (LEO), where exposure to O⁺ ions degrades thermal and mechanical properties. While traditional studies are often empirical, this project adopts an atomistic approach by deconstructing materials such as Kapton, graphite, and polystyrene into molecular moieties. Using Guided Ion Beam-Mass Spectrometry (GIB-MS), single-collision experiments were conducted to derive absolute reaction cross sections and product branching ratios. From two beamtime sessions at the SOLEIL synchrotron and a six-month research period at ICP Paris Saclay, we investigated the reactivity of O⁺ with 15 molecular systems serving as proxies for spacecraft materials. For example: Representative molecules for 1) Graphite: Benzene, naphthalene, and phenanthrene. 2) Polystyrene: Styrene, 3) Kapton: N-methylmaleimide, diphenyl ether, aniline, and phenol.
Methodology and Key Results:
To achieve state-selective control, O⁺ ions were generated via VUV photoionization( at SOLEIL synchrotron) and  Electron Ionization (EI) of gaseous precursors, CO₂ and H₂O ( at ICP Paris-Saclay). The work validates CO₂ as a precursor for generating high-purity (>98%) ground-state populations (⁴S) and H₂O for predominantly (90%) metastable excited states (²D, ²P).  The state-specific absolute reaction cross sections corresponding to the ground state and first excited state of O⁺ were obtained for each system. Results demonstrate that reactivity is highly sensitive to the electronic state of O⁺, with metastable ions exhibiting significantly enhanced cross sections for endothermic fragmentation channels, such as producing C₅H₃⁺ and C₄H₂⁺ in benzene, compared to the ground state.

The focus of my research is on space debris mitigation, using so-called “green” propulsion technologies and supported by satellite vision-based navigation techniques, in case of active debris removal scenarios. For the first part, my work has focused on electrodynamic tether satellites, where I contributed to the development and testing of a deployment mechanism for an electrodynamic tether within the E.T.PACK-F project (https://etpack.eu/e-t-pack-f/). The goal was to design and validate a reliable system capable of deploying the tether in orbit. Regarding vision-based navigation, I have investigated different techniques for satellite pose estimation using image data, also supported by convolutional neural networks (CNNs). Part of these activities were carried out abroad at the University of Würzburg, and in particular the research focused on repurposing a star tracker, using it as the camera for performing operations of proximity navigation.

What are the genetic components that confer resistance to space? The aim of my research is to answer this question through genomics, transcriptomics and proteomic analysis by subjecting extreme-tolerant Chroococcidiopsis cyanobacteria strains to different stress conditions.
Hence, I performed a comparative genomic analysis of space-resistant Chroococcidiopsis strains using a pangenome framework to characterize stress-resistance genes and assess their potential to produce UV-protective compounds such as scytonemin and mycosporine. Our results show strong conservation of enzymatic and non-enzymatic antioxidant systems involved in reactive oxygen species detoxification and DNA protection. A conserved biosynthetic gene cluster for scytonemin production and export was identified in strains Chroococcidiopsis sp. 029, 057, and 064, as well as a mycosporine-like amino acid gene cluster present in 057 strain.
Furthermore, I investigated adaptive responses to perchlorates, chaotropic salts ubiquitously present on Martian soil through a proteomic analysis of Chroococcidiopsis sp. 029 was conducted using LC-MS/MS after 21-day exposure experiments. Results indicate metabolic reprogramming consistent with methylotrophy, secondary metabolism and activation of ROS defense pathways, osmotic balance mechanisms, and membrane remodeling. Perchlorate stress also induced a metallophore-related biosynthetic cluster and proteins linked to polyhydroxybutyrate synthesis.

My research focus within the National PhD in Space Science and Technology involves leveraging multi-source satellite observations to monitor the hydrological cycle and enhance the accuracy of hydrological modeling. The primary objective is to develop a robust framework that integrates remote sensing data to overcome the limitations of sparse ground-based monitoring networks. To ensure the reliability of satellite products, I first developed a high-resolution (1km), long-term (30-year) meteorological time series by synthesizing ground station records. This dataset serves as a critical benchmark for validating satellite-derived precipitation and temperature products. I have successfully completed a comprehensive uncertainty analysis of these satellite products, identifying systematic errors and bias patterns. These findings are being prepared for Open Access publication to provide a reference for the broader scientific community. I am currently finalizing the integration of satellite-driven parameters into a hydrological modeling framework. This involves processing land surface characteristics (vegetation, soil properties, and DEM) and meteorological forcing data. While precipitation and temperature datasets are ready, I am currently finalizing the solar radiation components. Completion of this phase will lead to the full implementation of satellite-based hydrological simulations to improve water resource management and climate impact studies.

The GAPS (General Anti-Particle Spectrometer) experiment is a balloon-borne mission launched from McMurdo Station, Antarctica, in December 2025. Its primary scientific goal is to search for low-energy cosmic antinuclei, specifically antideuterons, antihelium, and antiprotons, in the energy range below 0.25 GeV/n. Particles like antideuterons are particularly compelling as they represent an exceptionally clean and distinctive signature of dark matter annihilation or decay, offering a powerful and complementary approach to traditional dark matter searches. The expected background from conventional astrophysical processes is extremely low, meaning that even the detection of a single low energy antideuteron could provide compelling evidence for physics beyond the Standard Model. 
Beyond its primary science objectives, the GAPS instrument also serves as a valuable platform for studying atmospheric muons at ground level. During the pre-flight campaign in Antarctica in December 2024, extensive ground-based long muon runs were conducted, enabling precise measurements of the sea-level muon flux. Studying muons with GAPS is particularly important because they behave primarily as non-interacting, minimum-ionizing particles (MIPs) within the detector, producing clean tracks with minimal secondary particles. These characteristics make muons ideal for validating single-track reconstruction algorithms and for developing methods to handle the more abundant cosmic ray nuclei expected during flight. Furthermore, the muon spectrum serves as an excellent proxy for assessing the long-term stability of the instrument's response. 
The study of atmospheric muons also holds significant importance for understanding space weather activity. Variations in solar activity directly influence the flux of low-energy primary cosmic rays entering Earth's atmosphere, which in turn produces observable changes in the muon flux at ground level. Continuous muon monitoring thus provides an indirect but sensitive probe of solar effects such as solar energetic particles. This research is critical for understanding solar-terrestrial interactions, protecting satellite infrastructure, and ensuring the safety of astronauts and aviation operations during solar energetic events. 
With the basic calibration work completed, my current research focuses on estimating the muon flux at sea level using GAPS ground data. To extract a clean muon sample, a minimal set of primary criteria is applied: events must have hits in both the umbrella and cube detectors, with at least four consecutive hits across detector layers. This ensures a high probability for successful track reconstruction. Lever-arm definitions—based on consecutive layers spanned and the distance between the first and last hit layers—are used to calculate efficiencies as functions of particle energy. Hit distribution analysis across layers, modules, and rows serves as a benchmark for muon behavior in the tracker and confirms proper detector functionality. At sea level, the muon flux is dominant; however, a small fraction of fast protons can still mimic muons, requiring careful discrimination between protons and muons. 
I am currently conducting part of my research abroad at the Laboratoire de Physique Subatomique et de Cosmologie (LPSC) in Grenoble, where I am working on the reconstruction of the solar modulation parameter, ϕ. Reconstructing ϕ is fundamentally important for several reasons. It enables the study of temporal variations in galactic cosmic-ray fluxes due to solar activity. Building upon the methodology developed at LPSC, neutron monitor count rates provide a powerful tool for studying solar modulation. Neutron monitors, operational since the 1950s, measure the secondary neutron flux generated by cosmic ray interactions in the atmosphere, serving as stable, indirect proxies for the primary cosmic ray flux. Through an inversion procedure—which involves modelling the detector response via yield functions and empirical calibration against space-based measurements—these count rates allow for the reconstruction of a continuous time series of the solar modulation parameter, ϕ, within the force-field approximation. Furthermore, reconstructing ϕ from both neutron monitors and muons allows for cross-validation of these independent measurement techniques and provides a calibrated baseline for testing more complex numerical models of cosmic ray transport in the heliosphere.

My research focuses on observational extragalactic astronomy, specifically on the role of dual and strongly lensed Active Galactic Nuclei (AGN) in galaxy evolution and supermassive black hole (SMBH) growth within the Λ-CDM framework. Galaxy mergers can trigger simultaneous accretion onto two SMBHs, forming dual AGN systems that are progenitors of gravitational-wave emitting SMBH binaries. I am building the first large, homogeneous sample of sub-arcsec AGN pairs using the Gaia Multi-Peak method. 
Extensive spectroscopic campaigns at TNG, NTT, and VLT enabled a catalog of ~600 candidates, providing the first measurement of the dual AGN fraction below 7 kpc as a function of redshift. High-resolution VLT/MUSE observations allow the characterization of dual and strongly lensed AGN, including SMBH masses, separations, and host galaxy properties, offering key constraints on black hole growth, merger timescales, feedback processes, and the inner mass distribution of lens galaxies.

My PhD research focuses on planetary surface composition using X-ray and gamma-ray spectroscopy for space exploration. I work on the modelling, simulation, and calibration needed to convert fluorescence spectra into quantitative elemental abundances.
A major part of my work supports the TASTE mission to Deimos, a small satellite mission designed to study the Martian moon through orbital observations and surface investigations. I study the expected performance of solar-induced X-ray fluorescence measurements and the calibration strategy for the orbiter spectrometer. I developed analytical methods based on the fundamental-parameter approach to predict fluorescence line intensities, and I am extending this work with Monte Carlo simulations to cross-check results and study the effects of geometry and observing conditions.
In parallel, I contribute to lunar spectroscopy studies within the HARLOCK mission for in situ characterization of lunar rocks and regolith. In this context, I work on PROGReX, the X-ray and gamma-ray spectrometer, with a focus on X-ray fluorescence modelling, measurement geometry, calibration planning, and the preparation of laboratory validation activities on analogue materials to benchmark the models.
 

In the context of planetary missions, the optimization of the scheduling of payload instrument acquisitions is of great importance in order to maximize the scientific return. To this end, specific acquisition plans are defined, deciding which instruments can operate at different times. These plans aim to optimize coverage while respecting both the physical constraints imposed by the instrumentation and the mission resources. Despite some automatic/semi-automatic approaches have been developed for scheduling activities of Earth observation satellites, only few studies have considered the case of space missions based on other planets, where the longer temporal duration of the schedule and the many constraints make the problem more complex. This research work attempts to address the problem of instrument acquisition optimization through the use of new methodologies based on AI and specifically on deep learning. To address the high dimensionality of the solution space, we developed a method based on latent space optimization (LSO) that maps the problem into a lower-dimensional latent space. This space is learned through the joint training of an autoencoder and a value network, enabling efficient search in high-potential solutions regions. The study is developed with respect to the operations of radar instruments, even if the methodology is general.

My PhD research focuses on the analysis of Cosmic Microwave Background (CMB) data, in particular on noise modeling in Bayesian component separation using the Commander software framework. Upmost characterization of the noise is crucial for measuring faint CMB polarization signals, orders of magnitude weaker than temperature anisotropies and heavily contaminated by astrophysical foregrounds.
The first part of my work focuses on the implementation of a frequency-correlated noise model in Commander2. This generalizes the software architecture to handle noise contributions across frequency channels. I statistically validated the code by means of an independent component separation pipeline, demonstrating improved parameter reconstruction and reduced uncertainties. The generalized code was then applied to simulated data from the QUBIC experiment, where I studied the impact of taking into account noise frequency correlations in spectral imaging.
The second part of my research is within the OpenHFI project, which aims to reprocess Planck High Frequency Instrument raw data using the time-domain Bayesian framework of Commander3. My contribution includes the correction of a high-frequency roll-off in the noise power spectrum, the implementation of a generalized correlated noise model based on spline interpolation, and the characterization and removal of 4K cooler-induced spectral spikes. These implementations improve the noise description and the quality of the reconstructed sky maps.

My research examines how changes in body afferent signaling (e.g., those occurring in microgravity) influence emotion and decision-making through alterations in the interoceptive system. By combining  behavioral measures (e.g., heartbeat counting and discrimination tasks), self-report questionnaires, and neurophysiological indices (e.g., heartbeat-evoked cortical potentials), I aim to characterize individual differences in interoceptive processing and learning. I experimentally test interventions designed to counteract interoceptive alterations, including interoceptive attention training, false interoceptive feedback delivered through vibrotactile stimulation, and mental imagery of interoceptive signals. A particular focus of my work is whether hypnotizability (i.e., a stable psychophysiological trait predicting responsiveness to hypnotic suggestions), can serve as a model of attenuated interoceptive precision and predict the efficacy of the tested interventions. These findings may inform the development of personalized trainings with potential relevance for clinical applications and for improving adaptive functioning in extreme contexts, such as space environments.