What is he best known for?
The fields of study he is best known for:
- Astronomy
- Astrophysics
- Supernova
His main research concerns Astrophysics, Supernova, Astronomy, Light curve and Galaxy.
His work in Astrophysics tackles topics such as Spectral line which are related to areas like Interstellar medium.
His work deals with themes such as Metallicity, Dark energy, Redshift and White dwarf, which intersect with Supernova.
His study in Light curve is interdisciplinary in nature, drawing from both Wavelength and Active galactic nucleus.
His primary area of study in Galaxy is in the field of Luminosity.
His studies examine the connections between Photometry and genetics, as well as such issues in Luminosity distance, with regards to Extragalactic astronomy, Advanced Camera for Surveys and Baryon acoustic oscillations.
His most cited work include:
- The Hubble Space Telescope Cluster Supernova Survey. V. Improving the Dark-energy Constraints above z > 1 and Building an Early-type-hosted Supernova Sample (1441 citations)
- The Hubble Space Telescope Cluster Supernova Survey. V. Improving the Dark-energy Constraints above z > 1 and Building an Early-type-hosted Supernova Sample (1441 citations)
- THE MAN BEHIND THE CURTAIN: X-RAYS DRIVE THE UV THROUGH NIR VARIABILITY IN THE 2013 ACTIVE GALACTIC NUCLEUS OUTBURST IN NGC 2617 (1012 citations)
What are the main themes of his work throughout his whole career to date?
Eric Hsiao spends much of his time researching Astrophysics, Supernova, Light curve, Astronomy and Galaxy.
The concepts of his Astrophysics study are interwoven with issues in Spectral line and Near-infrared spectroscopy.
His Supernova research is multidisciplinary, incorporating elements of Spectroscopy, Luminosity, Redshift and Infrared.
His Light curve research integrates issues from Absolute magnitude, Fornax Cluster, Chandrasekhar limit and Ultraviolet.
His work on Pair-instability supernova and Stars as part of general Astronomy research is frequently linked to Population, bridging the gap between disciplines.
His research in Galaxy intersects with topics in Cosmology and Cepheid variable.
He most often published in these fields:
- Astrophysics (115.25%)
- Supernova (111.33%)
- Light curve (42.92%)
What were the highlights of his more recent work (between 2019-2021)?
- Supernova (111.33%)
- Astrophysics (115.25%)
- Spectral line (27.67%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Supernova, Astrophysics, Spectral line, Light curve and Ejecta.
His work carried out in the field of Supernova brings together such families of science as Absolute magnitude, Chandrasekhar limit and Photometry.
His Astrophysics study combines topics from a wide range of disciplines, such as Infrared and Envelope.
The study incorporates disciplines such as Stellar population and Brightness in addition to Spectral line.
His Light curve study combines topics in areas such as Type II supernova and Observatory.
His Galaxy research incorporates themes from Photometric system and Cepheid variable.
Between 2019 and 2021, his most popular works were:
- Nebular spectra of 111 Type Ia supernovae disfavour single-degenerate progenitors (14 citations)
- The Carnegie Supernova Project II. The shock wave revealed through the fog: The strongly interacting Type IIn SN 2013L (7 citations)
- The Carnegie Supernova Project II. Observations of the intermediate luminosity red transient SNhunt120 (6 citations)
In his most recent research, the most cited papers focused on:
- Astronomy
- Astrophysics
- Galaxy
His scientific interests lie mostly in Supernova, Astrophysics, Spectral line, Light curve and Galaxy.
He integrates Supernova and Shock wave in his research.
Eric Hsiao integrates Astrophysics with Type in his study.
The Photometry study combines topics in areas such as Wavelength, Observatory and Spitzer Space Telescope.
His Ejecta research is multidisciplinary, relying on both Photosphere and Time domain astronomy.
His Conjunction research is multidisciplinary, incorporating perspectives in Near-infrared spectroscopy, Dispersion and Photometry.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
