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Hongyu Xiao

Seismology, Progamming, Food

Contact MeCurriculum Vitae
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About Me

Hello! I’m Hongyu Xiao, a Ph.D. in Seismology and Tectonics from the University of Illinois at Urbana-Champaign.

My research focuses on uncovering the hidden crustal variations of the Midcontinent (Midwest) region in the United States. These studies contribute to understanding tectonic activity and assessing seismic hazards. I specialize in leveraging advanced seismological techniques to analyze the North American Craton and its implications for cratonic evolution in the Midwest.

Currently, I’m a Research Associate at the University of Oklahoma, where I focus my research on induced seismicity and carbon storage management, and developing strategies for geological carbon sequestration. My research interest includes subsurface analysis and applying seismological methods to ensure the safety and efficiency of carbon capture and storage (CCS) projects.

Beyond academia, I enjoy gardening, exploring outdoor adventures, and enjoying food. From savoring seafood delicacies to embarking on city hikes, I believe in balancing work and life by embracing nature and new flavors. Curious? Learn more about my journey!

Information
School:
The University of Oklahoma
Email:
hongyu.xiao-1 [at] ou.edu
Phone:
+1 872-203-0968
Address:
Sarkeys Energy Center, Norman, OK U.S.A
Language:
English, Chinese, German
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Latest Updates

  • AGU Meeting 2024: AL/ML in Induced Seismicity Monitoring

    In December 2024, I presented our research on transfer learning techniques for induced seismicity monitoring at the AGU Annual Meeting. Representing the University of Oklahoma, the presentation highlighted the potential of applying machine learning in seismology to detect and analyze seismic events with greater efficiency. The work was well-received by scientists worldwide, sparking insightful discussions and fostering new collaborations.

  • New Research Associate Position at University of Oklahoma

    In April 2024, I joined the University of Oklahoma as a Research Associate. My work focuses on induced seismicity monitoring and carbon sequestration, addressing critical challenges in anthropogenic earthquake research and sustainable environmental solutions.

  • Ph.D. Dissertation Submitted

    In December 2023, I submitted my Ph.D. dissertation, which explores seismic activity and crustal morphology in the Midcontinent of North America. The research provides valuable insights into earthquake studies and tectonic processes.

Research

Illinois Basin / Michigan Basin / Midcontinent / The United States

Receiver function analysis

Receiver functions (RF) are time series computed from three-component seismic timeseries, and they indicate the Earth structure near the station (receiver) [Langston et al 1978].

The H-κ-c method is a generalized receiver function method with harmony corrections on P to S converted phases and the corresponding crustal multiples, essentially improving the estimates of crustal thickness (H) and the ratio of P to S velocity (Vp/Vs ratio, κ) [Li et al JGR 2018].

Illinois Basin / Central Midcontinent / The United States

Ambient Noise tomography

Ambient noise tomography (ANT for short) is a seismic imaging method using coherent signals extracted from seismic ambient noise records to construct tomography of the earth interior. By calculating cross-correlation of noise signals, we could recover the coherent surface wave signals hidden in the noise records which is called Empirical Green’s Function.

Illinois Basin / Central Midcontinent / The United States

Joint inversion tomography

Ambient nnoise imaging is sensitive to velocity structures however lack of the power to detect sharp discontinuity/large impedance contrast. Receiver function is sensitive to large impedance contrast however unable to track velocity structure.

The joint inversion could overcome the potential tradeoffs during inversion processes. The tomography model provides very detailed shear velocity structures in central midcontinent.

Oklahoma / Induced Seismicity / Machine Learning

Machine Learning in Induced Seismology Research

This research leverages advanced machine learning techniques to enhance the monitoring and analysis of induced seismicity. Using transfer learning, we refine seismic detection models to identify low-magnitude events with minimal false negatives, a critical need for induced seismicity monitoring in Oklahoma. This approach enables rapid deployments while maintaining high performance, providing a practical tool for understanding anthropogenic earthquake processes.

Machine Learning in Induced Seismology Research
Education
Doctor of Philosophy (Ph.D.) ,UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
2017 - 2023

Working with Dr.Xiaodong Song at University of Illinois Urbana-Champaign (UIUC). Dr.Xiaodong Song is currently at Peking University as Chair Professor of School of earth and space sciences now

My research projects were about the lithosphere morphology and the seismic velocity structure of the midcontinent in the United States

Master of Science ,UNIVERSITY OF CHICAGO
2014 - 2016

Worked with Dr.Douglas R. MacAyeal at University of Chicago in Hyde Park.

My research project was a multiple-layer neural network (a.k.a machine learning) model for Early Earthquake Warning Systems based on historical seismicity records.

I managed large datasets of seismic records using supervised training and did many data cleaning, manipulation, preprocessing, and feature design.

Bachelor of Engineering ,CHINA UNIVERSITY OF PETROLEUM, BEIJING
2010 - 2014

Worked with Dr.Ji Hancheng at China University of Petroleum,Beijing.

My undergraudate thesis was "Genetic analysis of chert in Wumishan formation." I conducted Total Organic Carbon (TOC) Analysis for the hydrocarbon source rock samples from Wumishan formation.

G.P.A. 3.88/4, Top Graduates from competitive Honor Program

Professional Skills
Python / C
[Proficiency]
Perl
[Proficiency]
ArcGIS
[Experience]
CSH / awk
[Proficiency]
MATLAB
[Experience]
HTML/CSS
[Can do]
Teaching
2021 Spring Semester
Planet Earth

Introduces non-science majors to physical aspects (earthquakes, volcanoes, floods, tsunamis, mountains, plate tectonics) and historical aspects (formation of earth and life, dinosaurs, ice age, evolution of climate) in earth science. Presents information on earth resources, natural hazards, and development of natural landscapes. Focuses on humanistic issues; provides context for understanding environmental change.

2020 Spring Semester
Geology of the National Parks

Develops geologic background, concepts, and principles through study of selected national parks and monuments. Examines the geologic framework and history, modern geologic processes, and factors influencing the present day landscape for each park area.

2019 Fall Semester
Mineralogy and Mineral Optics

Introduction to: crystallography; crystal optics; structure, composition, properties, stability and geological occurrences of minerals; and mineral identification.

2019 Spring Semester
Physical Geology

Introduces Earth phenomena and processes. Includes minerals and rocks, continental drift, plate tectonics, rock deformation, igneous and sedimentary processes, geologic time, landscape evolution, internal structure and composition of the earth, groundwater, seismology and earthquakes, and formation of natural resources. Emphasizes the chemical and physical aspects of the Earth, and the basis for geological inference.

2018 Fall Semester
The Oceans

Integrated introduction to oceanography and marine geology and geophysics. Topics include ocean-basin formation and evolution (in the context of plate tectonics), ocean ecology, the hydrologic cycle, water chemistry, currents and waves, the interaction of oceans with climate, coastal hazards, resources, pollution, and the Law of the Sea. Course is oriented toward students not majoring in science.

2018 Fall Semester
Structural Geology and Tectonics

Introduction to principles of rock deformation, stress, and strain; description and interpretation of geologic structures; study of methods for structural analysis; outline of geotectonic processes.

Figures I Made
Figure 1: Seismic Event Detection
Seismic Event Detection

Demonstrates the application of machine learning for detecting seismic events.

Figure 2: Loss Curve for Model Training
Loss Curve for Model

A typical loss curve during machine learning training, showing convergence.

Figure 3: Time-Series Plot
Time-Series Plot

Highlights the temporal distribution of seismic events in Oklahoma.

Figure 4: Model Accuracy Over Epochs
Data Availability Map

Shows data Availability of spefciic seismic station in the study area.

Figure: Rose plot of azimuth distribution
Back azimuth distribution

Illustrates the back azimuth distribution of seismic events in the study area.

Figure 6: Seismic Event Distribution Map
Event and Station Distribution

A spatial map showing the distribution of seismic events and station in the study area.

A bit more about me ...

Plants / Flower / Begonia

Growing Begonia as a hobby

Growing flowers is my newly developed skills over the Pandemic. It is super fun to watch them grow

I have varies flower plants like Begonia,Roses, Lilies etc Most of them actually survived the winter under my care!

Now my plan for flower planting is to have flowers at all seasons!

Hiking / Mississippi River / Fall

Hiking in the fall showing the Mississippi River

Hiking is one of my preferred way of vacation. I love to see the fall foliage in Michigan state. It is such an amazing beauty

Sometimes, the unpredictable weather could add more fun to it.

Food / Streetfood / Qingdao

Always available for food tryout !

Holding the belief that food is the simplest happiness within reach. I am always happy trying new food

Spicy food? Street food? Smelly but local food? Bring them on.

However, I am only loyal to Qingdao food taste and establish my rating based on it. :)

Contact Me
Feel free to contact me

Address

1301 W, Green St., Urbana, U.S.A

Phone

+1779-232-3992

Email

hongyux2@illinois.edu