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Kornel Howil

Kornel Howil contributes to research discovery and scholarly infrastructure.

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Published work

3 published item(s)

preprint2026arXiv

APEX: Audio Prototype EXplanations for Classification Tasks

Explainable AI (XAI) has achieved remarkable success in image classification, yet the audio domain lacks equally mature solutions. Current methods apply vision-based attribution techniques to spectrograms, overlooking fundamental differences between visual and acoustic signals. While prototype reasoning is promising, acoustic similarity remains multidimensional. We introduce APEX (Audio Prototype EXplanations), a post-hoc framework for interpreting pre-trained audio classifiers. Crucially, APEX requires no fine-tuning of the original backbone and strictly preserves output invariance. APEX disentangles explanations into four perspectives: Square-based prototypes to localize transient events, Time-based for temporal patterns, Frequency-based highlighting spectral bands, and Time-Frequency-based integrating both. This yields intuitive, example-based explanations that respect acoustic properties, providing greater semantic clarity than standard gradient-based methods.

preprint2022arXiv

Dark lenses through the dust: parallax microlensing events in the VVV

We use near-infrared photometry and astrometry from the VISTA Variables in the Via Lactea (VVV) survey to analyse microlensing events containing annual microlensing parallax information. These events are located in highly extincted and low-latitude regions of the Galactic bulge typically off-limits to optical microlensing surveys. We fit a catalog of $1959$ events previously found in the VVV and extract $21$ microlensing parallax candidates. The fitting is done using nested sampling to automatically characterise the multi-modal and degenerate posterior distributions of the annual microlensing parallax signal. We compute the probability density in lens mass-distance using the source proper motion and a Galactic model of disc and bulge deflectors. By comparing the expected flux from a main sequence lens to the baseline magnitude and blending parameter, we identify 4 candidates which have probability $> 50$% that the lens is dark. The strongest candidate corresponds to a nearby ($\approx0.78$ kpc), medium-mass ($1.46^{+1.13}_{-0.71} \ M_{\odot}$) dark remnant as lens. In the next strongest, the lens is located at heliocentric distance $\approx5.3$ kpc. It is a dark remnant with a mass of $1.63^{+1.15}_{-0.70} \ M_{\odot}$. Both of those candidates are most likely neutron stars, though possibly high-mass white dwarfs. The last two events may also be caused by dark remnants, though we are unable to rule out other possibilities because of limitations in the data.

preprint2021arXiv

Using the Carnot cycle to determine changes of the phase transition temperature

The Clausius-Clapeyron relation and its analogs in other first-order phase transitions, such as type-I superconductors, are derived using very elementary methods, without appealing to the more advanced concepts of entropy or Gibbs free energy. The reasoning is based on Kelvin's formulation of the second law of thermodynamics, and should be accessible to high school students. After recalling some basic facts about the Carnot cycle, we present two very different systems that undergo discontinuous phase transitions (ice/water and normal/superconductor), and construct engines that exploit the properties of these systems to produce work. In each case, we show that if the transition temperature $T_tr$ were independent of other parameters, such as pressure or magnetic field, it would be possible to violate Kelvin's principle, i.e., to construct a perpetuum mobile of the second kind. Since the proposed cyclic processes can be realized reversibly in the limit of infinitesimal changes in temperature, their efficiencies must be equal to that of an ordinary Carnot cycle. We immediately obtain an equation of the form $dT /dX = f(T, X)$, which governs how the transition temperature changes with the parameter $X$.