A5066712825- Pulsars and Gravitational Waves Research
- Gamma-ray bursts and supernovae
- High-pressure geophysics and materials
- Geophysics and Gravity Measurements
- Cosmology and Gravitation Theories
- Astrophysical Phenomena and Observations
- Generative Adversarial Networks and Image Synthesis
- Robotics and Sensor-Based Localization
- Gaussian Processes and Bayesian Inference
- Advanced Vision and Imaging
- Geophysics and Sensor Technology
- Astrophysics and Cosmic Phenomena
- Indoor and Outdoor Localization Technologies
- Seismic Imaging and Inversion Techniques
- Seismic Waves and Analysis
- Vehicle Noise and Vibration Control
- Autonomous Vehicle Technology and Safety
- Video Surveillance and Tracking Methods
- Optical measurement and interference techniques
- Seismology and Earthquake Studies
- Anomaly Detection Techniques and Applications
- Vehicle License Plate Recognition
- Magnetic confinement fusion research
- Domain Adaptation and Few-Shot Learning
- Superconducting Materials and Applications
University of Utah
2019-2025
National Tsing Hua University
2021-2024
High Energy Accelerator Research Organization
2023
National Astronomical Observatory of Japan
2023
Indian Institute of Engineering Science and Technology, Shibpur
2022
Variable Energy Cyclotron Centre
2015
KAGRA is a gravitational-wave (GW) detector constructed in Japan with two unique key features: It was underground, and the test-mass mirrors are cooled to cryogenic temperatures. These features not included other kilometer-scale detectors but will be adopted future such as Einstein Telescope. performed its first joint observation run GEO600 2020. In this observation, sensitivity of GWs inferior that LIGO Virgo. However, further upgrades ongoing reach for detecting next run, which scheduled...
Microchannel heat sink (MCHS) is a promising solution for removing the excess from an electronic component such as microprocessor, chip, etc. In order to increase removal rate, design of MCHS plays vital role, and can avoid damaging heat-sensitive components. Therefore, passage has been designed with periodic right triangular groove in flow passage. The motivation this form shape taken transfer enhancement techniques used solar air heaters. paper, numerical study new microchannel presented....
Deep latent variable models (DLVMs) are designed to learn meaningful representations in an unsupervised manner, such that the hidden explanatory factors interpretable by independent variables (aka disentanglement). The variational autoencoder (VAE) is a popular DLVM widely studied disentanglement analysis due modeling of posterior distribution using factorized Gaussian encourages alignment with axes. Several metrics have been proposed recently, assuming explaining variation data aligned axes...
Automated interpretation of seismic images using deep learning methods is challenging because the limited availability training data. Few-shot a suitable paradigm in such scenarios due to its ability adapt new task with supervision (small budget). Existing few-shot semantic segmentation (FSSS) fix number target classes. Therefore, they do not support joint on multiple datasets varying In context facies, fixing classes inhibits generalization capability model trained one facies dataset...
Abstract The discovery of the optical counterpart, along with gravitational waves (GWs) from GW170817, first binary neutron star merger has opened up a new era for multimessenger astrophysics. Combining GW data also known as AT 2017gfo and classified kilonova, revealed nature compact merging systems by extracting enriched information about total mass, mass ratio, system geometry, equation state. Even though detection kilonovae brought revolution in domain astronomy, there been only one...
For gravitational wave (GW) detected neutron star mergers, one of the leading candidates for electromagnetic (EM) counterparts is afterglow from an ultra-relativistic jet. Where this observed, it will likely be viewed off-axis, such as following GW170817/GRB 170817A. The temporal behaviour off-axis observed GRB can used to reveal lateral jet structure, and statistical model fits put constraints on various free-parameters. Amongst these parameters inclination system line sight. Along with GW...
3D scan registration is a classical, yet highly useful problem in the context of sensors such as Kinect and Velodyne. While there are several existing methods, techniques usually incremental where adjacent scans registered first to obtain initial poses, followed by motion averaging bundle-adjustment refinement. In this paper, we take different approach develop minimal solvers for jointly computing poses cameras small loops 3-, 4-, 5-cycles. Note that classical 2 can be done using minimum 3...
Idling vehicle detection (IVD) can be helpful in monitoring and reducing unnecessary idling integrated into real-time systems to address the resulting pollution harmful products. The previous approach [13], a non-end-to-end model, requires extra user clicks specify part of input, making system deployment more error-prone or even not feasible. In contrast, we introduce an end-to-end joint audio-visual IVD task designed detect vehicles visually under three states: moving, engine off. Unlike...
In the field of multi-messenger astronomy, Bayesian inference is commonly adopted to compare compatibility models given observed data. However, describe a physical system like neutron star mergers and their associated gamma-ray burst (GRB) events, usually more than ten parameters are incorporated in model. With such complex model, likelihood evaluation for each Monte Carlo sampling point becomes massive task requires significant amount computational power. this work, we perform quick...
For gravitational wave (GW) detected neutron star mergers, one of the leading candidates for electromagnetic (EM) counterparts is afterglow from an ultra-relativistic jet. Where this observed, it will likely be viewed off-axis, such as following GW170817/GRB 170817A. The temporal behaviour off-axis observed GRB can used to reveal lateral jet structure, and statistical model fits put constraints on various free-parameters. Amongst these parameters inclination system line sight. Along with GW...
Combustion vehicle emissions contribute to poor air quality and release greenhouse gases into the atmosphere, pollution has been associated with numerous adverse health effects. Roadways extensive waiting and/or passenger drop off, such as schools hospital drop-off zones, can result in high incidence density of idling vehicles. This produce micro-climates increased pollution. Thus, detection vehicles be helpful monitoring responding unnecessary integrated real-time or off-line systems...
The discovery of the optical counterpart, along with gravitational waves from GW170817, first binary neutron star merger, opened up a new era for multi-messenger astrophysics. Combining GW data also known as AT2017gfo, classified kilonova, has revealed nature compact merging systems by extracting enriched information about total mass, mass ratio, system geometry, and equation state. Even though detection kilonova brought revolution in domain astronomy, since there been only one wave detected...
The variational autoencoder (VAE) is a well-studied, deep, latent-variable model (DLVM) that efficiently optimizes the lower bound of log marginal data likelihood and has strong theoretical foundation. However, VAE's known failure to match aggregate posterior often results in \emph{pockets/holes} latent distribution (i.e., prior) and/or \emph{posterior collapse}, which associated with loss information space. This paper addresses these shortcomings VAEs by reformulating objective function...
3D scan registration is a classical, yet highly useful problem in the context of sensors such as Kinect and Velodyne. While there are several existing methods, techniques usually incremental where adjacent scans registered first to obtain initial poses, followed by motion averaging bundle-adjustment refinement. In this paper, we take different approach develop minimal solvers for jointly computing poses cameras small loops 3-, 4-, 5-cycles. Note that classical 2 can be done using minimum 3...
Mapping data from and/or onto a known family of distributions has become an important topic in machine learning and analysis. Deep generative models (e.g., adversarial networks ) have been used effectively to match unknown distributions. Nonetheless, when the form target distribution is known, analytical methods are advantageous providing robust results with provable properties. In this paper, we propose analyze use nonparametric density estimate Jensen-Shannon divergence for matching...