Projects

Academic Projects (2017–2025)

Research projects completed during my PhD and postdoctoral positions, focusing on astrophysics and computational modeling.

During my time as a researcher, my academic work focused on cosmic dust — the tiny solid particles that pervade our galaxy and play crucial roles in star formation, planet building, and chemical enrichment of the Universe. Below, I present four key projects that illustrate my approach to solving complex, data-driven problems in astrophysics. Through these projects, I developed a strong expertise in radiative transfer modelling — the computational simulation of how light interacts with matter — which is essential for interpreting astronomical observations and constraining physical properties from complex datasets. Beyond the scientific domain knowledge, these projects honed my skills in Python code development, collaborative code development with international teams, parallelisation of computations on university clusters, machine learning techniques to reduce computational time, and visualisation techniques for complex, multi-dimensional datasets.

Project 1: Decoding the Winds of a Dying Star

Constraining Dust Properties in the Atmosphere of R Doradus
R Doradus dust clouds
Dust clouds reflect starlight around the star R Doradus. This image combines polarised visible light taken with the Very Large Telescope in Chile, and an image of the star's surface taken with ALMA. Credit: ESO/T. Schirmer/T. Khouri; ALMA (ESO/NAOJ/NRAO)

The scientific context: why understanding stellar winds matters

Most of the heavy elements in the Universe — carbon, oxygen, silicon, iron — are forged inside stars and then released into space. This "cosmic recycling" is essential: without it, there would be no rocky planets, no organic molecules, and ultimately no life as we know it. But how exactly do these elements escape from stars and spread through the cosmos?

The answer lies largely with Asymptotic Giant Branch (AGB) stars — evolved, dying stars that have exhausted their core hydrogen and helium. These stellar giants are cosmic dust factories, producing massive quantities of dust grains in their extended atmospheres. The standard theory suggests that stellar light pushes on these dust grains (a phenomenon called radiative pressure), which then drag the surrounding gas along with them, creating powerful stellar winds that eject material into space.

R Doradus is one of the closest AGB stars to Earth (~55 parsecs, roughly 180 light-years away), making it an ideal laboratory to study these processes in detail. Its proximity allows us to resolve spatial structures in its atmosphere that would be impossible to see in more distant stars. R Doradus is also an oxygen-rich star, meaning it produces silicate dust grains — the same type of material found in rocky planets like Earth.

The research question: can dust drive the wind?

The central question was both fundamental and challenging: Can we determine the properties of dust grains forming around R Doradus, and assess whether these grains are capable of driving the observed stellar wind through radiative pressure alone?

This required solving a complex inverse problem: from observations of light at multiple wavelengths, we needed to infer the physical characteristics of dust grains (their size, composition, and spatial distribution) and then test whether the physics of radiation pressure could explain the mass loss rate we observe. The challenge was that the problem involves many coupled variables — dust properties affect how light propagates, which in turn affects the temperature structure, which affects where dust can form.

My approach: combining observations with computational modeling

Data integration from multiple observatories: I combined observations from three major facilities: the VLT/SPHERE/ZIMPOL instrument (providing high-resolution polarimetric images in visible light), ALMA (radio interferometry revealing the gas density structure), and archival photometric data spanning from optical to mid-infrared wavelengths. Each dataset provided complementary constraints — the polarization data is sensitive to scattering by dust grains, ALMA traces the gas distribution, and the spectral energy distribution (SED) constrains the overall dust mass and temperature.

Radiative transfer modeling: I used a sophisticated Monte Carlo radiative transfer code called RADMC-3D to simulate how light interacts with dust in the circumstellar environment. This code traces millions of photon packets as they scatter, absorb, and re-emit through the dusty medium, allowing us to compute synthetic observables (images, polarization maps, SEDs) for any given dust model.

Parameter space exploration with physical constraints: Rather than blindly searching a high-dimensional parameter space (dust composition, grain sizes, spatial distribution, mass-loss rate — a 6-dimensional problem), I implemented physics-based filtering to eliminate unphysical parameter combinations before running expensive simulations. For example, some parameter combinations would produce an optically thick medium — meaning light could not travel through it. But we clearly observe starlight from R Doradus, so such solutions are ruled out immediately. This pre-filtering saved an estimated several weeks of computation time while ensuring we explored only physically plausible scenarios.

Iterative fitting and validation: I compared synthetic observables from thousands of model runs against the real data, iteratively refining the parameter constraints. The model predictions were validated against multiple independent observations to ensure consistency.

Key findings: challenging the dust-driven wind paradigm

Tight constraints on dust properties: I successfully constrained the dust grain properties: a mixture of magnesium-iron silicates (MgFeSiO₄, specifically Mg₀.₅Fe₀.₅SiO₃) and transparent alumina (Al₂O₃) grains, with sizes around 0.3–0.5 micrometers. This is significantly larger than typical interstellar dust grains (~0.1 μm), suggesting that grain growth occurs efficiently in the dense inner atmosphere.

A fundamental puzzle: The most striking result was negative in a scientific sense, but extremely important: the dust grains we observe cannot drive the wind through radiative pressure alone. The momentum transfer from starlight to dust is insufficient by a significant factor. This challenges the long-standing paradigm of dust-driven winds for oxygen-rich AGB stars.

New directions: This finding opens exciting avenues for future research. Alternative mechanisms — such as giant convective bubbles in the stellar atmosphere, stellar pulsations, or episodic dust formation events — may play crucial roles in launching these winds. The result forces the astrophysical community to rethink the mass-loss mechanism for a significant fraction of AGB stars.

Impact: The paper was published in Astronomy & Astrophysics (2025) and was featured in a Chalmers press release.

Monte Carlo Simulations Radiative Transfer Multi-wavelength Analysis Parameter Optimization Physical Constraint Modeling Python International Collaboration

Project 2: Tracking Dust Evolution Under Extreme Radiation

Constraining Dust Properties in Photon-Dominated Regions
Horsehead Nebula
The Horsehead Nebula, imaged here by the Hubble Space Telescope, is just one small part of an enormous cosmic cloud that's currently giving birth to young stars. Credit: NASA, ESA, and the Hubble Heritage Team (STScI/AURA)

The scientific context: where starlight shapes dust

Photon-Dominated Regions (PDRs) are cosmic laboratories where intense ultraviolet (UV) radiation from massive stars sculpts the surrounding gas and dust. These regions are found at the interfaces between hot ionized gas (near the star) and cold molecular clouds — the birthplaces of new stars and planets. Think of them as the "weather zones" of the interstellar medium, where energetic stellar light creates dynamic, layered structures.

Dust grains in PDRs play multiple critical roles in astrophysics: they catalyze the formation of molecular hydrogen (H₂, the most abundant molecule in the Universe), they absorb UV photons and re-emit energy in the infrared (affecting the thermal balance of the gas), and they heat the gas through the photoelectric effect — UV photons eject electrons from grain surfaces, and these energetic electrons collide with gas atoms, transferring energy. All of these processes depend sensitively on the dust properties: size distribution, composition, and structure.

Understanding how dust evolves in different physical environments is therefore essential for interpreting observations across the electromagnetic spectrum and for modeling the chemistry and physics of star-forming regions. However, dust properties are not universal — they change depending on the local conditions of radiation intensity and gas density.

The research question: how does dust evolve under extreme radiation?

The primary objective was to constrain the dust grain properties (size distribution, composition, structure) across multiple PDRs with different physical conditions, and then understand how dust responds to changes in UV irradiation and gas density.

This required studying not just one object, but a systematic sample of PDRs spanning a range of conditions: from the iconic Horsehead Nebula (a relatively moderate PDR) to more intensely irradiated regions like Orion and Carina. By comparing dust properties across these environments, we could disentangle intrinsic variations from environment-driven evolution.

My approach: systematic comparison across multiple environments

Multi-wavelength observational campaigns: I analyzed data from multiple space and ground-based observatories: Herschel (far-infrared), Spitzer (mid-infrared), and ground-based facilities. Each wavelength range probes different aspects of the dust population — mid-infrared emission traces warm, small grains near the illuminated surface, while far-infrared emission probes the bulk of the cold dust mass deeper in the cloud.

Spatially-resolved analysis: Rather than treating each PDR as a single point, I performed spatially-resolved analysis to track how dust properties change with depth into the cloud (i.e., with distance from the illuminating star). This required careful handling of the varying spatial resolution across different instruments and wavelengths.

Sophisticated dust modeling: I used state-of-the-art dust models (THEMIS — The Heterogeneous dust Evolution Model for Interstellar Solids, and DustEM) that treat dust as a population of grains with different sizes, compositions, and optical properties. These models can predict emission spectra for any given dust mixture, allowing forward modeling from dust properties to observables.

Radiative transfer in PDR environments: I coupled the dust models with PDR codes (Meudon PDR code, DustPDR) that self-consistently compute the UV radiation field, gas temperature, and chemistry as functions of depth into the cloud. This was essential because the local radiation field determines which grains are destroyed and which survive.

Systematic comparison across objects: By applying the same methodology to multiple PDRs, I could identify which variations in dust properties were robust across environments and which were specific to local conditions. This comparative approach is analogous to studying the same phenomenon across multiple datasets to distinguish signal from noise.

Key findings: small dust grains destroyed by UV radiation

Depletion of nano-grains in irradiated regions: A key finding was that the smallest dust grains (nano-grains, with sizes below ~10 nanometers) are systematically depleted in the UV-illuminated zones of PDRs. This depletion increases with the intensity of the radiation field — the more intense the UV, the fewer small grains survive. This is consistent with theoretical predictions that small grains are destroyed by UV photons through processes like photodissociation and sputtering.

Evolution with physical conditions: I quantified how the dust size distribution changes as a function of both UV intensity and gas density. Higher-density regions provide some shielding for small grains, while low-density, highly-irradiated zones show the most dramatic depletion. This has important implications for understanding dust evolution in galaxies with different star formation intensities.

Implications for future observations: These results were instrumental in preparing for observations with the James Webb Space Telescope (JWST). I was an extended core team member of the PDRs4All Early Release Science program, and my work helped the collaboration secure this successful program and interpret the unprecedented JWST data of the Orion Bar.

Publications: This work resulted in two first-author papers in Astronomy & Astrophysics (2020, 2022), establishing a framework for interpreting dust emission in PDRs that continues to be applied to JWST observations.

Multi-wavelength Data Analysis Radiative Transfer Modeling Statistical Comparison Feature Engineering Spatial Data Analysis Python JWST Preparation

Project 3: When Dust Changes, Gas Feels It

Impact of Dust Evolution on Gas Heating in PDRs

The scientific context: linking dust and gas physics

In the previous project, I established that dust properties evolve significantly in PDRs — particularly that small grains are depleted in UV-irradiated zones. But dust and gas in the interstellar medium are not isolated systems; they are intimately coupled through multiple physical processes.

One of the most important coupling mechanisms is the photoelectric effect: when UV photons hit dust grains, they can eject electrons from the grain surface. These energetic "photoelectrons" then collide with gas atoms and molecules, transferring their kinetic energy and heating the gas. This is the dominant heating mechanism for neutral gas in many astrophysical environments.

Here's the critical link: the photoelectric heating rate depends strongly on the dust grain surface area. Small grains have much more surface area per unit mass than large grains (geometry dictates this — surface area scales as r², volume as r³). If small grains are depleted, as I found in Project 2, then the total grain surface area decreases, and so does the photoelectric heating rate. This could have profound implications for gas temperatures throughout PDRs and beyond.

The research question: how does dust evolution affect gas heating?

The goal was to quantify how the dust evolution observed in PDRs affects the thermal balance of the gas, specifically the photoelectric heating. This required propagating the dust property constraints from Project 2 through gas physics models to predict observable consequences.

A secondary objective was to test whether this could help resolve a long-standing problem: models of PDRs have historically struggled to reproduce the observed gas temperatures — they often predict temperatures that are too low, suggesting that some heating mechanism is missing or underestimated.

My approach: integrating dust properties into gas models

Coupling dust and gas models: I integrated the evolved dust properties (from Project 2) into PDR codes that compute the gas thermal balance. This required modifying how the photoelectric heating rate is calculated, using the actual constrained dust size distributions rather than standard assumptions.

Self-consistent modeling: The calculation is non-trivial because dust properties, UV field, and gas temperature are all coupled. The UV field determines which grains survive; the surviving grains determine the heating rate; the heating rate determines the gas temperature; and the gas temperature affects chemistry and dynamics. I implemented an iterative approach to achieve self-consistency.

Predictions for gas emission lines: The gas temperature directly affects the intensity of emission lines from atoms and molecules. I computed predicted line intensities for key diagnostic species (like [C II] at 158 μm) that can be compared with observations from facilities like Herschel and SOFIA.

Key findings: a puzzle that deepens, pointing to missing physics

Reduced gas heating: As expected, accounting for the depletion of small grains leads to significantly reduced photoelectric heating rates — by factors of 2-5 in the most irradiated zones. This reduction is substantial and has measurable consequences for predicted gas temperatures and emission line intensities.

A puzzle deepens: Interestingly, this result actually worsens the long-standing "heating problem" in PDRs. If anything, models already predicted too little heating; now, with evolved dust, they predict even less. This is not a failure — it's a valuable result that points toward missing physics. The finding motivates the search for additional heating mechanisms (mechanical heating from turbulence, cosmic ray heating, or others) that must be operating in these environments.

JWST preparation: This work was directly relevant for the PDRs4All collaboration. By quantifying how dust evolution affects gas observables, we could better interpret the combined dust and gas observations from JWST. The predictions I made are now being tested against actual JWST data of the Orion Bar.

Publication: Published in Astronomy & Astrophysics (2021), this paper bridges dust physics and gas physics, demonstrating the importance of treating the interstellar medium as a coupled system rather than studying dust and gas in isolation.

Physical Modeling Coupled Systems Iterative Algorithms Prediction & Validation Scientific Communication Hypothesis Testing

Project 4: Finding Hidden Patterns in the Milky Way

Detecting Kinematic Structures with Wavelet Analysis
Gaia spacecraft and Milky Way
Artist's impression of the Gaia spacecraft, with the Milky Way in the background. Gaia, operated by the European Space Agency (ESA), surveys the sky from Earth orbit to create the largest, most precise, three-dimensional map of our Galaxy. The Gaia mission has enabled transformational studies in many fields of astronomy, addressing the structure, origin and evolution of the Milky Way. Credit: ESA/ATG medialab; background image: ESO/S. Brunier

The scientific context: hidden structures in stellar motions

The solar neighborhood — the region of the Milky Way within a few hundred parsecs of the Sun — contains thousands of stars moving in all directions. But these motions are not random. Hidden within the apparent chaos are kinematic structures: groups of stars that share similar velocities, indicating a common origin or dynamical history.

These structures are fossils of the Galaxy's past. Some are remnants of dissolved star clusters; others are caused by resonances with the rotating spiral arms or the central bar of the Milky Way. Detecting and characterizing these structures tells us about galactic dynamics, star formation history, and the gravitational potential of our galaxy.

The challenge is that these structures are subtle overdensities in velocity space, embedded in a noisy background of field stars. Detecting them requires sophisticated statistical techniques that can identify localized features at multiple scales while accounting for observational uncertainties and Poisson noise.

The research question: can we detect kinematic structures robustly?

The objective was to apply wavelet analysis to the largest available stellar kinematic dataset (combining Gaia DR1/TGAS and RAVE surveys, over 55,000 stars with precise 3D velocities) to detect and validate kinematic structures in the solar neighborhood.

A key requirement was statistical rigor: any detected structure needed to be validated against the possibility of being a spurious detection due to noise. The previous studies had used smaller datasets or less robust validation methods.

My approach: wavelet analysis with Monte Carlo validation

Data preparation and quality control: I worked with a catalog of stellar positions and velocities, but not all measurements are equally reliable. I implemented quality cuts based on velocity uncertainties (keeping only stars with σ_U and σ_V < 4 km/s) and parallax quality, resulting in a clean sample of 55,831 stars with well-determined space velocities. Proper data cleaning was essential — including unreliable measurements would have introduced spurious features.

Wavelet decomposition: I applied the "à trous" (with holes) wavelet algorithm — a multi-scale analysis technique that decomposes the 2D velocity distribution into different spatial scales. Unlike simple histogram binning, wavelets can detect structures of varying sizes simultaneously and provide information about both the location and scale of features. The algorithm is implemented in the MR software developed by J.L. Starck and F. Murtagh.

Poisson noise filtering: Because we have a finite sample of stars, the velocity histogram contains Poisson noise. I used the auto-convolution histogram method to filter out noise-induced features, keeping only structures that are statistically significant at the 3σ level (99.86% confidence that the structure is not due to Poisson fluctuations).

Monte Carlo validation: This was a crucial innovation. Even after Poisson filtering, structures could be artifacts of velocity measurement uncertainties — if a star's true velocity is uncertain, it might be assigned to the wrong bin, potentially creating or destroying apparent structures. I developed a Monte Carlo approach: generate 2,000 synthetic datasets by randomly perturbing each star's velocity according to its measurement uncertainty, run the full wavelet analysis on each realization, and track which structures appear consistently. Only structures detected in >50% of realizations were considered robust.

Structure characterization: For each validated structure, I extracted parameters: position in velocity space (U, V), size, number of member stars, and statistical significance. I compared detected structures with the literature to identify known moving groups and flag potentially new discoveries.

Key findings: validating known structures and discovering a new one

Robust detection of known structures: The analysis successfully recovered all major kinematic structures previously identified in the solar neighborhood: the Pleiades, Hyades, Sirius, Coma Berenices, Hercules, and others. The positions and sizes matched literature values, validating the methodology.

Discovery of a new kinematic structure: Among the robust detections was a previously unreported overdensity at (U, V) ≈ (37, 8) km/s. This structure passed all validation tests — it appears consistently across Monte Carlo realizations and is statistically significant at >3σ. Its origin remains to be explained, possibly linked to resonances with the Galactic bar or a dissolved cluster.

Methodological contribution: The Monte Carlo validation framework I developed provides a template for future studies using improved data (Gaia DR2, DR3, and beyond). The approach of propagating measurement uncertainties through the entire analysis pipeline is now standard practice in kinematic studies.

Impact: Published in Astronomy & Astrophysics (2017), this paper has been cited 33+ times and contributed to the foundation for subsequent studies using Gaia data. The wavelet + Monte Carlo methodology has been adopted by other groups studying galactic dynamics.

Signal Processing Wavelet Analysis Monte Carlo Methods Statistical Validation Large Dataset Analysis Pattern Recognition Data Quality Control

Publications

Here is a list of the papers I have written or co-written during my career in academia from 2017 to 2025. My PhD thesis is also available at the end of this list.

First Author

An empirical view of the extended atmosphere and inner envelope of the asymptotic giant branch star R Doradus: II. Constraining the dust properties with radiative transfer modelling

Schirmer, T., Khouri, T., Vlemmings, W., Nyman, L.-Å., Maercker, M., Unnikrishnan, R., Bojnordi Arbab, B., Knudsen, K. K., and Aalto, S.

A&A, 704, A4 (2025)

DOI Link arXiv

JWST observations of photodissociation regions: III. Dust modeling at the illuminated edge of the Horsehead nebula

Elyajouri, M., Abergel, A., Ysard, N., Habart, E., Schirmer, T., Jones, A., Juvela, M., Tabone, B., Verstraete, L., Misselt, K., Gordon, K. D., Noriega-Crespo, A., Guillard, P., Witt, A. N., Baes, M., Bouchet, P., Brandl, B. R., Kannavou, O., Dell'ova, P., Klassen, P., Trahin, B., and Van De Putte, D.

A&A, 704, A203 (2025)

DOI Link arXiv

ALMA Lensing Cluster Survey: Dust mass measurements as a function of redshift, stellar mass, and star formation rate from z = 1 to z = 5

Jolly, J.-B., Knudsen, K., Laporte, N., Guerrero, A., Fujimoto, S., Kohno, K., Kokorev, V., Lagos, C. del P., Schirmer, T.-A., Bauer, F., Dessauge-Zavadsky, M., Espada, D., Hatsukade, B., Koekemoer, A. M., Richard, J., Sun, F., and Wu, J. F.

A&A, 693, A190 (2025)

DOI Link

PDRs4All. VIII. Mid-infrared emission line inventory of the Orion Bar

Van De Putte, D., Meshaka, R., Trahin, B., Habart, E., Peeters, E., Berné, O., Alarcón, F., Canin, A., Chown, R., Schroetter, I., Sidhu, A., Boersma, C., Bron, E., Dartois, E., Goicoechea, J. R., Gordon, K. D., Onaka, T., Tielens, A. G. G. M., Verstraete, L., Wolfire, M. G., Abergel, A., Bergin, E. A., Bernard-Salas, J., Cami, J., Cuadrado, S., Dicken, D., Elyajouri, M., Fuente, A., Joblin, C., Khan, B., Lacinbala, O., Languignon, D., Le Gal, R., Maragkoudakis, A., Okada, Y., Pasquini, S., Pound, M. W., Robberto, M., Röllig, M., Schefter, B., Schirmer, T., Tabone, B., Vicente, S., Zannese, M., and others (80+ authors)

A&A, 687, A86 (2024)

DOI Link

PDRs4All: II. JWST's NIR and MIR imaging view of the Orion Nebula

Habart, E., Peeters, E., Berné, O., Trahin, B., Canin, A., Chown, R., Sidhu, A., Van De Putte, D., Alarcón, F., Schroetter, I., Dartois, E., Vicente, S., Abergel, A., Bergin, E. A., Bernard-Salas, J., Boersma, C., Bron, E., Cami, J., Cuadrado, S., Dicken, D., Elyajouri, M., Fuente, A., Goicoechea, J. R., Gordon, K. D., Issa, L., Joblin, C., Kannavou, O., Khan, B., Lacinbala, O., Languignon, D., Le Gal, R., Maragkoudakis, A., Meshaka, R., Okada, Y., Onaka, T., Pasquini, S., Pound, M. W., Robberto, M., Röllig, M., Schefter, B., Schirmer, T., Tabone, B., Tielens, A. G. G. M., Wolfire, M. G., Zannese, M., and others (100+ authors)

A&A, 685, A73 (2024)

JWST near- and mid-infrared imaging of the Orion Nebula, providing a comprehensive view of the dust and gas structures in this iconic star-forming region and photon-dominated environment.

DOI Link

An empirical view of the extended atmosphere and inner envelope of the asymptotic giant branch star R Doradus. I. Physical model based on CO lines

Khouri, T., Olofsson, H., Vlemmings, W. H. T., Schirmer, T., Tafoya, D., Maercker, M., De Beck, E., Nyman, L.-Å., and Saberi, M.

A&A, 685, A11 (2024)

A detailed study of the extended atmosphere and inner envelope of the AGB star R Doradus using CO line observations, providing insights into the physical conditions and mass-loss processes in evolved stars.

DOI Link

PDRs4All: III. JWST's NIR spectroscopic view of the Orion Bar

Peeters, E., Habart, E., Berné, O., Sidhu, A., Chown, R., Van De Putte, D., Trahin, B., Schroetter, I., Canin, A., Alarcón, F., Schefter, B., Khan, B., Pasquini, S., Tielens, A. G. G. M., Wolfire, M. G., Dartois, E., Goicoechea, J. R., Maragkoudakis, A., Onaka, T., Pound, M. W., Vicente, S., Abergel, A., Bergin, E. A., Bernard-Salas, J., Boersma, C., Bron, E., Cami, J., Cuadrado, S., Dicken, D., Elyajouri, M., Fuente, A., Gordon, K. D., Issa, L., Joblin, C., Kannavou, O., Lacinbala, O., Languignon, D., Le Gal, R., Meshaka, R., Okada, Y., Robberto, M., Röllig, M., Schirmer, T., Tabone, B., Zannese, M., and others (100+ authors)

A&A, 685, A74 (2024)

Near-infrared spectroscopic analysis of the Orion Bar using JWST, providing detailed insights into the molecular and atomic gas components in this archetypal photon-dominated region.

DOI Link

PDRs4All. IV. An embarrassment of riches: Aromatic infrared bands in the Orion Bar

Chown, R., Sidhu, A., Peeters, E., Tielens, A. G. G. M., Cami, J., Berné, O., Habart, E., Alarcón, F., Canin, A., Schroetter, I., Trahin, B., Van De Putte, D., Abergel, A., Bergin, E. A., Bernard-Salas, J., Boersma, C., Bron, E., Cuadrado, S., Dartois, E., Dicken, D., El-Yajouri, M., Fuente, A., Goicoechea, J. R., Gordon, K. D., Issa, L., Joblin, C., Kannavou, O., Khan, B., Lacinbala, O., Languignon, D., Le Gal, R., Maragkoudakis, A., Meshaka, R., Okada, Y., Onaka, T., Pasquini, S., Pound, M. W., Robberto, M., Röllig, M., Schefter, B., Schirmer, T., Vicente, S., Wolfire, M. G., Zannese, M., and others (100+ authors)

A&A, 685, A75 (2024)

Comprehensive spectroscopic analysis of aromatic infrared bands in the Orion Bar using JWST observations, revealing unprecedented detail in the molecular complexity of photon-dominated regions.

DOI Link

PDRs4All. V. Modelling the dust evolution across the illuminated edge of the Orion Bar

Elyajouri, M., Ysard, N., Abergel, A., Habart, E., Verstraete, L., Jones, A., Juvela, M., Schirmer, T., Meshaka, R., Dartois, E., Lebourlot, J., Rouillé, G., Onaka, T., Peeters, E., Berné, O., Alarcón, F., Bernard-Salas, J., Buragohain, M., Cami, J., Canin, A., Chown, R., Demyk, K., Gordon, K., Kannavou, O., Kirsanova, M., Madden, S., Paladini, R., Pendleton, Y., Salama, F., Schroetter, I., Sidhu, A., Röllig, M., Trahin, B., and Van De Putte, D.

A&A, 685, A76 (2024)

Comprehensive dust modeling study of the Orion Bar PDR using JWST observations, investigating dust evolution processes across the illuminated edge where stellar radiation drives complex dust-gas interactions.

DOI Link

OH as a probe of the warm-water cycle in planet-forming disks

Zannese, M., Tabone, B., Habart, E., Goicoechea, J. R., Zanchet, A., van Dishoeck, E. F., van Hemert, M. C., Black, J. H., Tielens, A. G. G. M., Veselinova, A., Jambrina, P. G., Menendez, M., Verdasco, E., Aoiz, F. J., Gonzalez-Sanchez, L., Trahin, B., Dartois, E., Berné, O., Peeters, E., He, J., Sidhu, A., Chown, R., Schroetter, I., Van De Putte, D., Canin, A., Alarcón, F., Abergel, A., Bergin, E. A., Bernard-Salas, J., Boersma, C., Bron, E., Cami, J., Dicken, D., Elyajouri, M., Fuente, A., Gordon, K. D., Issa, L., Joblin, C., Kannavou, O., Khan, B., Languignon, D., Le Gal, R., Maragkoudakis, A., Meshaka, R., Okada, Y., Onaka, T., Pasquini, S., Pound, M. W., Robberto, M., Röllig, M., Schefter, B., Schirmer, T., Vicente, S., and Wolfire, M. G.

Nature Astronomy, 8, 577–586 (2024)

DOI Link

A far-ultraviolet–driven photoevaporation flow observed in a protoplanetary disk

Berné, O., Habart, E., Peeters, E., Schroetter, I., Canin, A., Sidhu, A., Chown, R., Bron, E., Haworth, T. J., Klaassen, P., Trahin, B., Van De Putte, D., Alarcón, F., Zannese, M., Abergel, A., Bergin, E. A., Bernard-Salas, J., Boersma, C., Cami, J., Cuadrado, S., Dartois, E., Dicken, D., Elyajouri, M., Fuente, A., Goicoechea, J. R., Gordon, K. D., Issa, L., Joblin, C., Kannavou, O., Khan, B., Lacinbala, O., Languignon, D., Le Gal, R., Maragkoudakis, A., Meshaka, R., Okada, Y., Onaka, T., Pasquini, S., Pound, M. W., Robberto, M., Röllig, M., Schefter, B., Schirmer, T., Simmer, T., Tabone, B., Tielens, A. G. G. M., Vicente, S., Wolfire, M. G., and others (100+ authors)

Science, 383, 988–992 (2024)

DOI Link

Formation of the methyl cation by photochemistry in a protoplanetary disk

Berné, O., Martin-Drumel, M.-A., Schroetter, I., Goicoechea, J. R., Jacovella, U., Gans, B., Dartois, E., Coudert, L. H., Bergin, E., Alarcon, F., Cami, J., Roueff, E., Black, J. H., Asvany, O., Habart, E., Peeters, E., Canin, A., Trahin, B., Joblin, C., Schlemmer, S., Thorwirth, S., Cernicharo, J., Gerin, M., Tielens, A., Zannese, M., Abergel, A., Bernard-Salas, J., Boersma, C., Bron, E., Chown, R., Cuadrado, S., Dicken, D., Elyajouri, M., Fuente, A., Gordon, K. D., Issa, L., Kannavou, O., Khan, B., Lacinbala, O., Languignon, D., Le Gal, R., Maragkoudakis, A., Meshaka, R., Okada, Y., Onaka, T., Pasquini, S., Pound, M. W., Robberto, M., Röllig, M., Schefter, B., Schirmer, T., Sidhu, A., Tabone, B., Van De Putte, D., Vicente, S., and Wolfire, M. G.

Nature, 621, 56–59 (2023)

DOI Link

Editorial: Cosmic dust—its formation, processing, and destruction

Gobrecht, D., Das, A., Baeyens, R., and Schirmer, T.

Frontiers in Astronomy and Space Sciences, 10, 1242545 (2023)

DOI Link

The extremely sharp transition between molecular and ionized gas in the Horsehead nebula

Hernández-Vera, C., Guzmán, V. V., Goicoechea, J. R., Maillard, V., Pety, J., Le Petit, F., Gerin, M., Bron, E., Roueff, E., Abergel, A., Schirmer, T., Carpenter, J., Gratier, P., Gordon, K., and Misselt, K.

A&A, 677, A152 (2023)

DOI Link arXiv

The Origin of Dust Polarization in the Orion Bar

Le Gouellec, V. J. M., Andersson, B.-G., Soam, A., Schirmer, T., Michail, J. M., Lopez-Rodriguez, E., Flores, S., Chuss, D. T., Vaillancourt, J. E., Hoang, T., and Lazarian, A.

ApJ, 951, 97 (2023)

DOI Link arXiv

High-angular-resolution NIR view of the Orion Bar revealed by Keck/NIRC2

Habart, E., Le Gal, R., Alvarez, C., Peeters, E., Berné, O., Wolfire, M. G., Goicoechea, J. R., Schirmer, T., Bron, E., and Röllig, M.

A&A, 673, A149 (2023)

DOI Link arXiv
First Author

Nano-grain depletion in photon-dominated regions

Schirmer, T., Ysard, N., Habart, E., Jones, A. P., Abergel, A., and Verstraete, L.

A&A, 666, A49 (2022)

DOI Link

PDRs4All: A JWST Early Release Science Program on Radiative Feedback from Massive Stars

Berné, O., Habart, E., Peeters, E., Abergel, A., Bergin, E. A., Bernard-Salas, J., Bron, E., Cami, J., Dartois, E., Fuente, A., Goicoechea, J. R., Gordon, K. D., Okada, Y., Onaka, T., Robberto, M., Röllig, M., Tielens, A. G. G. M., Vicente, S., Wolfire, M. G., Alarcón, F., Boersma, C., Canin, A., Chown, R., Dicken, D., Languignon, D., Le Gal, R., Pound, M. W., Trahin, B., Simmer, T., Sidhu, A., Van De Putte, D., Cuadrado, S., Guilloteau, C., Maragkoudakis, A., Schefter, B. R., Schirmer, T. et al. (100+ authors)

Publications of the Astronomical Society of the Pacific, 134(1035), 054301 (2022)

DOI Link
First Author

Influence of the nano-grain depletion in photon-dominated regions. Application to the gas physics and chemistry in the Horsehead

Schirmer, T., Habart, E., Ysard, N., Bron, E., Le Bourlot, J., Verstraete, L., Abergel, A., Jones, A. P., Roueff, E., and Le Petit, F.

A&A, 649, A148 (2021)

DOI Link
First Author

Dust evolution across the Horsehead nebula

Schirmer, T., Abergel, A., Verstraete, L., Ysard, N., Juvela, M., Jones, A. P., and Habart, E.

A&A, 639, A144 (2020)

DOI Link
PhD Thesis

Dust Evolution in Photon-Dominated Regions

Schirmer, T.-A.

PhD Thesis, Université Paris-Saclay (2020)

Comprehensive study of dust grain processing in photon-dominated regions using THEMIS interstellar dust model coupled with 1D and 3D radiative transfer codes. Detailed analysis of the Horsehead nebula and preparation of synthetic maps for JWST Early Release Science observations.

PDF

Kinematic structures of the solar neighbourhood revealed by Gaia DR1/TGAS and RAVE

Kushniruk, I., Schirmer, T., and Bensby, T.

A&A, 608, A73 (2017)

Analysis of kinematic groups in the Milky Way using wavelet analysis on Gaia DR1/TGAS data combined with RAVE radial velocities. Contributed to methodology section on wavelet analysis techniques.

DOI Link

For citation metrics and additional publication details, please visit my profiles on ORCID, Google Scholar, or ADS.

About

I grew up in Eastern France, near Belfort, where immediate access to nature, vast open spaces, and mountains profoundly shaped the person I am today. This region, rich in culinary and wine-making traditions, nurtured my curiosity and appreciation for the finer things in life.

Having always been drawn to the stars and sciences, I also developed a passion for reading - an accessible means of travel that opened numerous horizons for me. It was natural that I chose to pursue studies in astrophysics, which led me to Paris and the École Normale Supérieure Paris-Saclay.

During this journey, I had the opportunity to complete two internships (bachelor's and first year of master's) at the Besançon Observatory, under the supervision of Julien Montillaud, who instilled in me the scientific rigor essential for research. It was there that I truly discovered astrophysics and developed my passion for this field. Confirmed in my desire to pursue this path, I then completed my second-year master's internship at the Meudon Observatory, benefiting from the enriching guidance of Jacques Le Bourlot and Franck Le Petit.

The next step took me to Sweden, to the Lund Observatory, as part of my fourth year of studies. This experience served a dual purpose: deepening my knowledge in astrophysics, particularly regarding the GAIA mission, while discovering a country that had long attracted me through its harmonious relationship with nature and the quality of life of its inhabitants. This year proved to be a tremendous success that far exceeded all my expectations!

Returning to France, I began my PhD at the Institut d'Astrophysique Spatiale in Orsay, where I spent three fascinating years studying dust in photon-dominated regions, under the benevolent and stimulating supervision of Laurent Verstraete and Alain Abergel. Determined to continue in research, I was fortunate to secure a postdoctoral position at Chalmers in Göteborg - an ideal opportunity that allowed me to continue my research on dust grains while returning to Sweden, a country that had captivated me so much.

After nearly four enriching years of postdoctoral research in Göteborg, I decided to settle permanently in this city and begin a professional transition toward data science, opening an exciting new chapter in my career.

Beyond research, I cultivate numerous interests. Once again enjoying privileged access to nature and living near a lake, I discovered the world of triathlon in Sweden and reconnected with running after an eight-year hiatus following a knee injury sustained while playing rugby. I am also passionate about culture in all its forms: literature, museums, intellectual exchanges... In our era, immediate access to knowledge offers us the opportunity to constantly explore new subjects - a truly inexhaustible source of wonder! Finally, I have a genuine passion for gastronomy: I love cooking, baking, and exploring new restaurants. This is why I particularly appreciate the Swedish tradition of "fika", that special moment when one savors excellent pastries over good coffee in pleasant company.

Curriculum Vitae

Download Industry CV (PDF) Download Academic CV (PDF)

Last updated: August 2026

Work Experience

Data Scientist

Volvo Group — Digital Technology & Operations
August 2026 - Present
Gothenburg, Sweden
  • Data scientist in the Data Science Sweden chapter

Data Scientist & Post-doctoral Researcher in Astrophysics

Chalmers University of Technology
August 2021 - August 2025
Gothenburg, Sweden
  • Led a research project using an open-source radiative transfer code parallelized on the university cluster to explore grids of parameters constraining physical properties of astrophysical objects — resulting in a conference talk, a publication in Astronomy & Astrophysics, and a press release
  • Optimized the computational pipeline using Machine Learning (Random Forest) to significantly reduce computation time
  • Co-supervised a PhD student with Prof. Susanne Aalto, mentoring on data analysis and scientific communication
  • Chaired the Local and Scientific Organising Committees of an international conference (110+ participants, 12-person team) — cosmic-dust-sweden.sciencesconf.org
  • Organized a technical workshop on ALMA/JWST synergies (20+ participants)
  • Collaborated within a 50+ member international team on a NASA/ESA project (PDRs4All)
  • Co-founded SENECA — the Swedish Network for Early Career Astronomers

Data Scientist & Post-doctoral Researcher in Astrophysics

Institut d'Astrophysique Spatiale
October 2020 - July 2021
Orsay, France
  • Continued PhD research work running radiative transfer simulations to explore grids of physical parameters, optimizing hyperparameters of the open-source radiative transfer code "SOC" and comparing results with Spitzer satellite observations to study the Orion Bar and IC63 nebulae
  • Served as PhD/Post-doc representative on the laboratory council, helping shape the life of the institute

Data Scientist — PhD Researcher in Astrophysics

Institut d'Astrophysique Spatiale
October 2017 - October 2020
Orsay, France
  • Contributed to the development of the radiative transfer code "SOC" (Python-based) through regular collaboration with Mika Juvela (University of Helsinki), including work trips to Helsinki
  • Designed and implemented a pipeline using SOC to efficiently explore N-dimensional parameter spaces, parallelized on the university computing cluster
  • Optimized computations through hyperparameter tuning and feature engineering
  • Developed visualization techniques to interpret results from large-scale simulations
  • Actively involved in outreach at the Palais de la Découverte (astrophysics department)
  • Served as PhD/Post-doc representative on the laboratory council

Data Scientist — Research Assistant

Lund University
August 2016 - June 2017
Lund, Sweden
  • Applied wavelet analysis to 3D galactocentric velocity data from the GAIA telescope to detect overdensities in Milky Way stellar populations
  • Used the "à trous" algorithm combined with MCMC simulations to assess statistical significance of detected patterns
  • Co-authored a publication in Astronomy & Astrophysics, fully responsible for the data analysis component

Communication & Mentoring

Technical Mentor (PhD Co-Supervision)

Chalmers University of Technology
2023 - 2025
Gothenburg, Sweden
  • Co-supervised Gustav Olander's PhD with Prof. Susanne Aalto on interstellar dust in compact obscure nuclei using the James Webb Space Telescope
  • Conducted weekly meetings and provided ongoing mentoring support as needed

Public Speaker & Science Communicator

Palais de la Découverte (Science Museum)
2017 - 2020
Paris, France
  • Delivered 45-minute presentations + 15-minute Q&A sessions on the lifecycle of matter in the Universe, 2-4 times every weekend
  • Engaged audiences ranging from ages 5 to 99 with very different backgrounds — adapting content to be understood by everyone
  • Guided visitors through interactive astronomy demonstrations and exhibits, explaining concepts like stellar evolution and cosmic dust formation

Teaching Assistant — Lycée Raspail

Lycée Raspail
2015 - 2016
Paris, France
  • Taught preparatory classes for engineering schools entrance exams (60 hours in Physics and Technology* (PT*) and 30 hours in Technology and Industrial Sciences (TSI))
  • Provided individualized support and exam preparation for students in physics and mathematics

Private Tutor — PECES

PECES
2012 - 2015
Paris, France
  • Provided one-on-one tutoring for students in preparatory classes for elite engineering schools in Biology-Chemistry-Physics-Earth Sciences (BCPST), Physics-Chemistry (PC), and Mathematics-Physics (MP) tracks
  • Covered advanced topics in physics, chemistry, and mathematics
  • Developed personalized teaching strategies to help students succeed in competitive entrance exams

Event & Project Leadership

Wallenberg Project — The Origin and Fate of Dust in the Universe

August 2021 - August 2025
Gothenburg, Sweden
  • Core member of collaborative research project funded by the Knut and Alice Wallenberg Foundation, bringing together astronomers and theoretical chemists from Chalmers University of Technology and Gothenburg University
  • Led independent research projects on dust evolution in stellar environments and the interstellar medium, while actively contributing to collaborative projects led by other team members
  • Organized and facilitated weekly collaboration meetings for 3 years, ensuring effective communication and coordination across interdisciplinary team
  • Project scope: Understanding cosmic dust particles from their formation in stellar environments, through destruction and growth in the Galactic and high-redshift ISM, to their interaction with radiation from Active Galactic Nuclei
  • Within this collaboration: organized major international conference (110+ researchers, September 2023), coordinated JWST/ALMA workshop (December 2024), and co-supervised PhD research on JWST observations of compact obscured nuclei
  • Project website: cosmic-dust.se

Workshop Chair — JWST/ALMA Synergies

December 2024
Gothenburg, Sweden
  • Chaired local workshop (20+ participants) exploring complementary capabilities of James Webb Space Telescope and Atacama Large Millimeter Array
  • Co-organized with Matthias Maercker and the Nordic ALMA Regional Center (ARC)
  • Coordinated hands-on training sessions developed by Karl Gordon (STScI) and Nordic ALMA Node specialists, covering JWST and ALMA proposal writing, data processing, and joint proposal development
  • Managed complete event logistics including registration, venue coordination, and comprehensive workshop materials (150+ page guide)

International Conference Chair — Origin and Fate of Dust in Our Universe

September 2023
Gothenburg, Sweden
  • Organized 5-day international conference within the Knut and Alice Wallenberg Foundation-funded Cosmic Dust collaboration, bringing together 110+ researchers from diverse backgrounds
  • Chaired the Scientific Organising Committee (SOC), coordinating abstract reviews, session planning, and invited speaker selection
  • Chaired the Local Organising Committee (LOC), overseeing venue arrangements, registration, scientific program, social activities, and website management
  • Led organizing team of 12 members and oversaw budget planning and execution
  • Created and maintained the conference website: cosmic-dust-sweden.sciencesconf.org

SENECA — The Swedish Network for Early Career Astronomers

2022 - Present
Sweden
  • Founding member with Bibiana Prinoth and Linn Boldt-Christmas
  • Co-organized online workshop presenting Swedish astrophysical institutions and inviting successful postdocs to share grant-winning experiences
  • Helped maintain the network's Slack workspace for community communication
  • Organized satellite events for PhD students and postdocs during Astronomdagarna in Gothenburg (2022) and Lund (2024)
  • Contributed to establishing a supportive community for early career astronomers in Sweden — seneca-astro.github.io

National Conference — Astronomdagarna 2022

6-8 October 2022
Gothenburg, Sweden
  • Member of the Local Organising Committee (LOC) for Astronomdagarna, a biennial national conference bringing together 100+ Swedish astronomers
  • Contributed to the participant guide with local information and conference details (download booklet)
  • Organized the conference dinner including venue selection and menu planning
  • Coordinated networking activities for early career researchers, including a pub event and "1-minute presentation" session under SENECA initiative
  • Assisted with general logistics including registration desk, technical support, and on-site participant assistance

PDRs4All — JWST Early Release Science Program

2017 - 2025
International
  • Extended Core Team Member of a major JWST Early Release Science program studying radiative feedback from massive stars
  • Collaborated with an international team of 50+ researchers from institutions across Europe, North America, and Asia
  • Provided expertise on dust evolution in photon-dominated regions (PDRs)
  • Supported analysis of JWST observations of the Orion Bar and other PDRs — pdrs4all.org

Education

PhD in Astrophysics & Data Science

Institut d'Astrophysique Spatiale, Université Paris-Saclay
2017 - 2020
Orsay, France

Observatoire de Paris

Master degree in astrophysics — Astronomy, Astrophysics and Space Engineering (AAIS)

2015 - 2016
Paris, France
  • Advanced coursework in stellar physics: Asteroseismology and stellar interiors, stellar physics and evolution, magnetohydrodynamics
  • Specialized courses in interstellar medium physics, radiative transfer, atoms/molecules/solids, and galaxy formation
  • Hands-on observational training: one-week observing run at Observatoire de Haute-Provence (120cm IR telescope, 152cm spectroscopy) and infrared observations at Meudon Observatory focusing on the BN/KL complex
  • Computational astrophysics projects: developed numerical simulations in Fortran for dissipative systems, used Meudon PDR code and Paris-Durham shock code in Python
  • Completed 4-month research internship at LERMA/Observatoire de Paris-Meudon on dust models in photon-dominated regions

École Normale Supérieure Paris-Saclay

Master degree in fundamental physics

2014 - 2016
Paris, France
  • Advanced coursework in quantum physics and statistical physics, solid state physics, soft matter physics, and quantum optics
  • Specialized courses in nuclear and particle physics, environmental physics, and astrophysics and cosmology
  • Experimental physics training: photoluminescence of quantum objects, surface wave hydrodynamics, and advanced optics laboratory work
  • Scientific English and professional communication training
  • Completed 4-month laboratory internship at Observatoire de Besançon on 3D self-consistent modeling of dust and gas

École Normale Supérieure Paris-Saclay

Bachelor degree in fundamental physics

2013 - 2014
Paris, France
  • Core physics curriculum: quantum mechanics fundamentals, electromagnetism, statistical physics, and states of matter
  • Specialized courses in matter cohesion, optics and lasers, instrumentation and electronics, and information processing
  • Mathematical and numerical methods for physicists, including computational techniques
  • Experimental physics laboratory work and chemistry coursework
  • Research initiation through internship at Observatoire de Besançon on gravitational collapse modeling
  • Scientific and practical English training

Lycée Albert Schweitzer

Preparatory classes (CPGE PCSI/PC) — Intensive program for elite engineering schools entrance exams

2010 - 2013
Mulhouse, France
  • PCSI (First Year): Mathematics, Physics, Chemistry, Engineering Sciences, French/Philosophy, English, plus laboratory work and tutorials
  • PC (Second Year): Advanced Mathematics, Physics, Chemistry, French/Philosophy, English, TIPE (supervised personal research project)
  • Curriculum Focus: Differential and integral calculus, linear algebra, complex analysis, classical mechanics, thermodynamics, electromagnetism, organic and inorganic chemistry, materials science
  • Program Overview: Rigorous preparation for prestigious engineering schools and universities through intensive schedule (35+ hours), competitive national entrance exam preparation for leading institutions (ENS, École Polytechnique, Centrale, Mines), with university-level STEM curriculum emphasizing problem-solving and mathematical modeling

Intensive Swedish Language Course

Folkuniversitetet
September 2025 - October 2025
  • Followed Swedish classes every morning for 2 months
  • Progressed from A1 and A2 levels to reach B1 proficiency

Side Projects & Portfolio

Sports Club Dashboard (Full-Stack Data App)

2025 - Present
  • Built and deployed Python-based interactive dashboard using Dash/Plotly
  • Serves 100+ users with data visualization and performance tracking
  • Deployed on Railway with ongoing Docker containerization
  • Experimenting with LLM-powered conversational interface for data queries

Kaggle Competitions (ML Practice)

2025 - Present
  • Active participation to sharpen practical ML skills
  • Focus: PyTorch, scikit-learn, hyperparameter tuning (Optuna)
  • Feature engineering, ensemble methods, model evaluation

Certifications

Machine Learning Specialization

DeepLearning.AI & Coursera
July - October 2025

Completed 5 specialized courses: Advanced Learning Algorithms, Unsupervised Learning, Recommenders, Reinforcement Learning, and Supervised Machine Learning: Regression and Classification. Gained proficiency in Machine Learning, Scikit-Learn, TensorFlow, Random Forest, XGBoost, and Neural Networks.

Databricks Fundamentals

Databricks Academy Accreditation
October 2025

Academy Accreditation demonstrating understanding of fundamental concepts related to the Databricks Data Intelligence Platform.

Microsoft Azure Data Scientist Path

Microsoft Azure & Coursera
October 2025 - January 2026

Completed 2 courses: Create Machine Learning Models in Microsoft Azure, and Microsoft Azure Machine Learning for Data Scientists. Learned to create working environments for data science workloads on Azure, train and deploy predictive models using Azure Machine Learning.

Languages & Additional Information

Languages

French (Native), English (Fluent/C1), Swedish (B1)

Interests

Trail Running, Triathlon, Cooking, Baking, Nature, Literature

References

Available upon request

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