# Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

## Markdown

This is a page not in th emain menu

## Future Blog Post

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This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

## Blog Post number 4

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

## Blog Post number 3

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

## Blog Post number 2

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

## Blog Post number 1

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

## Mathematical Epidemiology and Theretical Evolutionary Biology (UT Austin)

Over the past several years, we have been developing new network-based mathematical approaches for predicting the spread of infectious diseases. In collaboration with public health officials in the United States and Canada, we apply these methods to the design of optimal control measures for respiratory diseases including influenza and SARS. We are also collaborating with field ecologists to better understand the contact network structures of wildlife populations and their epidemiological consequences. Using mathematical modeling, we have addressed several fundamental questions about (a) the impact of environmental heterogeneity on evolutionary dynamics and (b) the structure of complex fitness landscapes. Our work in these areas have yielded important insights into the diversity of certain classes of biological molecules and the ability of some viruses to rapidly evolve as they spread through human populations.

## Real-time prediction of emerging drug use epidemics in the United States (UCSD)

Mathematical modeling has been used extensively to forecast emerging and re- emerging infectious disease epidemics because it allows to mechanistically represent the different factors determining disease transmission and their dynamics over time. We will develop a mathematical model of drug use in the United States which represents current patterns of drug use across the country and associated HIV, HCV and overdose incidence. It will explicitly represent heterogeneity in susceptibility to drug use disorders in the population, social networks and the influence of drug markets, law enforcement and healthcare services on drug use and associated health outcomes. This project will 1) systematically investigate the potential for emerging drug use epidemics; 2) identify the optimal allocation of resources towards combination of interventions to control them and limit associated harms; 3) pilot a targeted mass-media based intervention to increase access to appropriate prevention methods among a specific population at risk of an emerging drug use in real time as identified by the model.

## Model and develop optimal control algorithm for the vector-brone disease system (KSU)

Vector-borne diseases have more complex transmission routes than the most of infcectious diseases. This research utilizes the dynamic modeling and agent-based modeling to describe the disease transmission for ZIKA Virus and Zoonotic Visceral Leishmaniasis. Theortical analysis are used to figure out the most important part from the model. Based on the analysis result, this research uses optimal control theory to design the control strategies which can reduce the cost during the epidmeic. The simulation is used to verify the control strategies and predict the future disease transmission Since the traditional Pontryagin maximum principle-based optimal control algorithm can only solve the optimal control problem for with convex objective functions. The major contribution of this research is developing the new methodology of numerical epidemic control.An innovative heuristic algorithm based method is proposed to solve the optimal control problem with the highly nonlinear objective function. This project also introduces evidence data based optimal control method, which trained the neural network with epidemic data to control the current prevalence.

## Zoonotic visceral leishmaniasis transmission: modeling, backward bifurcation, and optimal control

Published in Journal of mathematical biology, 2016

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Recommended citation: Zhao, Songnian, Yan Kuang, Chih-Hang Wu, David Ben-Arieh, Marcelo Ramalho-Ortigao, and Kaiming Bi. "Zoonotic visceral leishmaniasis transmission: modeling, backward bifurcation, and optimal control." Journal of mathematical biology 73, no. 6-7 (2016): 1525-1560.

## Modeling individual fear factor with optimal control in a disease-dynamic system

Published in Chaos, Solitons & Fractals, 2017

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Recommended citation: Chen, Yuyang, Kaiming Bi, Songnian Zhao, David Ben-Arieh, and Chih-Hang John Wu. "Modeling individual fear factor with optimal control in a disease-dynamic system." Chaos, Solitons & Fractals 104 (2017): 531-545.

## Risk perception and human behaviors in epidemics

Published in IISE Transactions on Healthcare Systems Engineering, 2018

[Website]

Recommended citation: Zhao, Songnian, Yan Kuang, Chih-Hang Wu, Kaiming Bi, and David Ben-Arieh. "Risk perception and human behaviors in epidemics." IISE Transactions on Healthcare Systems Engineering 8, no. 4 (2018): 315-328.

## Current visceral leishmaniasis research: a research review to inspire future study

Published in BioMed research international, 2018

[PDF]

Recommended citation: Bi, Kaiming, Yuyang Chen, Songnian Zhao, Yan Kuang, and Chih-Hang John Wu. "Current visceral leishmaniasis research: a research review to inspire future study." BioMed research international 2018 (2018).

## Modeling learning and forgetting processes with the corresponding impacts on human behaviors in infectious disease epidemics

Published in Computers & Industrial Engineering, 2019

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Recommended citation: Bi, Kaiming, Yuyang Chen, Songnian Zhao, David Ben-Arieh, and Chih-Hang John Wu. "Modeling learning and forgetting processes with the corresponding impacts on human behaviors in infectious disease epidemics." Computers & Industrial Engineering 129 (2019): 563-577.

## A new evidence-based optimal control in healthcare delivery: A better clinical treatment management for septic patients

Published in Computers & Industrial Engineering, 2019

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Recommended citation: Chen, Yuyang, Kaiming Bi, Chih-Hang John Wu, and David Ben-Arieh. "A new evidence-based optimal control in healthcare delivery: A better clinical treatment management for septic patients." Computers & Industrial Engineering 137 (2019): 106010.

## A Memetic Algorithm for Solving Optimal Control Problems of Zika Virus Epidemic with Equilibriums and Backward Bifurcation Analysis

Published in Communications in Nonlinear Science and Numerical Simulation, 2020

[PDF]

Recommended citation: Bi, Kaiming, Yuyang Chen, Chih-Hang John Wu, and David Ben-Arieh. "A Memetic Algorithm for Solving Optimal Control Problems of Zika Virus Epidemic with Equilibriums and Backward Bifurcation Analysis." Communications in Nonlinear Science and Numerical Simulation (2020): 105176.

## A new zoonotic visceral leishmaniasis dynamic transmission model with age-structure

Published in Chaos, Solitons & Fractals, 2020

[PDF]

Recommended citation: Bi, Kaiming, Yuyang Chen, Songnian Zhao, David Ben-Arieh, and Chih-Hang John Wu. "A new zoonotic visceral leishmaniasis dynamic transmission model with age-structure." Chaos, Solitons & Fractals 133 (2020): 109622.

## Additive manufacturing embraces big data

Published in Progress in Additive Manufacturing, 2021

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Recommended citation: Bi, Kaiming, Dong Lin, Yiliang Liao, Chih-Hang Wu, and Pedram Parandoush. "Additive manufacturing embraces big data." Progress in Additive Manufacturing (2021): 1-17.

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## IMSE 881, Integer Programming (Fall 2015)

Graduate Course, Kansas State University, IMSE Department, 2015

Working as a graduate teaching assistant, Grade Homework and Hold help sessions

## IMSE 685, Information System (Spring 2016)

Undergraduate Course, Kansas State University, IMSE Department, 2016

Working as a graduate teaching assistant, Grade Homework and Hold help sessions

## IMSE 643, Industrial Simulation (Fall 2018 & Spring 2019)

Undergraduate Course, Kansas State University, IMSE Department, 2018

Working as an instructor, teach simulation software, meet 50 students once a week