Students

Ph. D. students

Hongjun Chang (Biology)

hjchang23@kaist.ac.kr

Research Interests
I'm interested in the computational modeling of biological neural networks to explain experimental results such as neural oscillation, and applying the control theory of networks to biological interaction networks and neural networks.

Keyword
Neural network modeling, Network theory

Uiryong Kang (Life Sciences & Electrical Engineering)

urkang@kaist.ac.kr

Research Interests
Without doubt, brain is one of the most vital organ in maintaining normal body function. Besides, it is probably the most efficient computing machinery mankind has ever found. Because this marvelous organ has hierarchical structures and properties of complex network at all scales, it should be studied by tools of network science in a systematic manner. In this context, I have a great interest in figuring out hidden scientific principles of brain function retained in various brain networks.

Keyword
Network neuroscience, Comparative connectomics, Network control theory

Seong-hoon Jang (Bio and brain Engineering)

jangdeath@kaist.ac.kr

Research Interests
I am interested in complex network of cancer micro-enviroment which is comprised with various cell types. I believe that understanding and controlling of this dynamic network give a new insight for cancer therapy.

Keyword
Immunology, Cancer System biology, Bio-informatics,

Hoon-min Kim (Physics & Bio and Brain Engineering)

hunmin007@kaist.ac.kr

Research Interests
As biological systems of cells contain numerous components with complex regulating relations and their dynamics unknown, it is difficult to predict biological behaviors of complex diseases for certain conditions. Reconstructing the regulatory network for computational modelling from high-throughput experimental data would provide optimal treatment strategy for complex diseases with network control theory combined. My research interest lies on network model reconstruction strategy and network control theory.

Keyword
Systems biology, Network inference, Control theory

Juhee Kim (Life Sciences)

juheekim@kaist.ac.kr

Research Interests
I want to learn about convergence studies linked to life science and to use various methods to help understand biological phenomena. As biology has characteristics of 'complexity' and 'connectivity', it is effective to analyze biological phenomena from different perspectives that utilize high-throughput data and construct network models. I am particularly interested in what triggers cancer and what makes cancer subtypes different from each other.

Keyword
Cancer, Complex network, Network modeling, Control theory

Hyunjin Kim (Nursing & Biomedical Science and Engineering)

hyunjin0430@kaist.ac.kr

Research Interests
My interest is cancer. I would like to analyze a lot of information about cancer in order to understand it from a system biological perspective. Through this, I want to understand the mechanism of cancer and suggest effective treatment.

Keyword
Cancer, Systems biology, bioinformatics

Kyeong Hwan Han (Biotechnology)

gksrudghks77@kaist.ac.kr

Research Interests
I'm interested in treatment of cancer. Cancer is one of the most complex phenomenons and it has emergent properties, so i belive that systemistic approachs are needed for conquest of cancer. I want to make a contribution to treatment of cancer using methodology of systems biology, immunology, and synthetic biology. I'm interested particulary in two thing. First, repressing cancer cell's expresion of inhibitory molecules like PD-L1. Second, immune cell control to kill cancer cells specifically.

Keyword
Systems biology, Immunology, Synthetic biology

Corbin Hopper (Bio & Brain Engineering)

chopper@kaist.ac.kr

Research Interests
I am exploring how computers give insight into biology and how biology can inspire computation. As an example of the first direction, simulating genetic networks can evaluate strategies to redirect cancer cells towards a healthy state. The other direction includes evolutionary algorithms. I am especially interested in information theory, which has been linked to energetic efficiency. Imitating how living organisms adapt may offer tractable ways to untangle complex networks.

Keyword
Network control, Information theory, Cancer systems biology, Boolean networks

Woojeong Lee (Biological Sciences)

frship35@kaist.ac.kr

Research Interests
There have been many studies on cancer so far, and the complexity of cancer pathways and the heterogeneity between cancer subtypes have become more prominent. However, in order to do research beyond one step further than now, cancer should be viewed from a different perspective. My interest is to find a common property, which is not about individual genes but about complex interactions of various genes, that can penetrate all specific networks of various cancer subtypes. And by applying this concept in practice, my ultimate goal is to treat malignant cancer cells to become more controllable.


Keywords
Systems biology, Cancer biology, Stem cell, Network control

Jae Hyuk Choi (Chemical and Biomolecular Engineering)

jhchoii@kaist.ac.kr


Research Interests
As biotechnology improves, massive amounts of biological data is accumulated. Such data therefore, needs to be processed in order to understand the interactions between the components and understand the biological system. In order to understand such regulatory networks, biotechnology along with the use of computers is required and will eventually help solve problems regarding human health.


Keyword
Network control theory, Systems biology, Machine/Deep learning

Seoyoon Jeong (Physics & Life Science)

syjeong@kaist.ac.kr


Research Interests
I have been interested in the systematic analysis of living things, from molecular dynamics to ecosystems. These days I focus on tumor and inflammation diseases. Due to the intrinsic heterogeneity of the tumor itself and tumor microenvironment (TME), they become one of the most complex phenomena. My goal is to build a universal cancer model working across various species in the view of translational research to compensate for the difference between animal models and human patients.


Keyword
Systems biology, Complex network, Immunology, Cancer biology

Jeonghwan Min (Life Science and Biotechnology)

m_jeonghwan@kaist.ac.kr


Research Interests
Although we have progressed tremendously in elucidating individual signaling pathways, much of what happens when these pathways interact with each other is still unknown. This is a serious problem because real cellular dynamics happen at a multiple-pathway level.

Systems biology seeks to simulate real cellular dynamics by focusing on these pathway interactions. With the systems biology approach, I seek to create a platform for discovering novel drug targets and drug combinations for a disease. My ultimate goal is to use this platform to cure long-unresolved diseases such as cancer and aging.


Keywords
Systems biology, Systems pharmacology, Cancer biology, Aging

Yujin Nam (Computer Science)

yujin.nam@kaist.ac.kr




Research Interests

We have long believed aging is inevitable, but it may not. All living organisms are constructed based on what is written on the genome, and grow old as a ball rolling along a slope. I believe controlling this slope, which is genomic landscape, can cure aging. I'm exploring it with computing, network control theory, and cell experiments.


Keywords
Aging, Bioinformatics

Hyunsoo Yeo (Bio and Brain Engineering)

nky0309@kaist.ac.kr

Research Interests
By analyzing large-scale datasets and using network control theory, we can identify key nodes and signaling pathways as targets that are crucial for reversion cancer cell to normal cell. Ultimate goal is to develop novel therapeutic strategies that targets, thereby restoring normal cellular behavior and inhibiting cancer progression. I believe we can make significant strides towards developing more effective cancer treatments and improving patient outcomes.

Keywords
Cancer biology, Network control, Systems biology

Hyelim Park (Life Sciences)

park1210@kaist.ac.kr


Research Interests
Cancer’s heterogeneity, shaped by genetic, epigenetic, and phenotypic variations, drives tumor progression and treatment resistance. To uncover key vulnerabilities, my research takes a systems-level approach, integrating network perturbation, bifurcation analysis, and phenotypic reprogramming. By identifying critical transitions where small perturbations influence cancer cell fate, I explore strategies to disrupt malignant signaling and induce stable reversion to non-cancerous states. With a focus on epigenetic regulation, I investigate phenotypic plasticity and potential intervention points. Through computational modeling, high-throughput data analysis, and experimental validation, my work aims to advance precision medicine by targeting cancer’s systemic vulnerabilities.

Keywords
Cancer Systems Biology, Network Control, Phenotypic Reversion

 

M. S. students

Myoungbo Kang (Biotechnology & Statistic)

mbkang@kaist.ac.kr

Research Interests
I aim to conduct integrated research, spanning biology to computer modeling and simulations. While traditional cancer treatments mainly involve chemotherapy or surgery, there's a growing expectation that addressing the complexity of gene regulatory networks could lead to a more foundational and reversible approach to cancer treatment. My goal is to extract insights from extensive datasets, understand biological networks, and experimentally validate these findings, contributing to innovative and effective cancer therapeutic strategies.

Keywords
Cancer biology, Reverse control, Systems biology

Yoonsu Na (Biology & Convergence Software)

ysna99@kaist.ac.kr

Research Interests
As human health and cancer treatment is becoming one of the most important issue among the world, I think Systems Biology is a key breakthrough to deal with these issues. By modeling and analyzing various biological networks, we might be able to find novel target which is engaged in reversion of tumor to normal state. With concepts of Boolean network and control theory, I think it is not impossible to make a therapeutic strategies for unconquered cancer types.

Keywords
Network modeling, Network control, Cancer Biology

Ferio Brahmana (Engineering Physics)

feriobrahmana@kaist.ac.kr

Research Interests
My research interest lies in comprehending biological systems, particularly human cells, as complex dynamical entities. By conceptualizing these systems as dynamical systems, I aim to establish computable mathematical models that deepen our understanding of the intricate dynamics governing human cells. The overarching goal is to leverage this understanding to exercise control over human cell systems through computer simulation and a systems biology approach. With precise control mechanisms, there is significant potential to navigate the complex interplay of multi-interactions within human cells. I believe this approach holds promise for addressing and combating complex diseases, such as cancer, aging, and immune-related disorders, offering an intriguing perspective like the reverse control theory in the context of fighting diseases like cancer or aging.

Keywords
System Biology, Network Control, Reverse Control Theory

Junseo Seo (Systems Biomedical Science)

juneseo99@kaist.ac.kr

Research Interests
I focus on the interdisciplinary field of bioinformatics, single-cell genomics, spatial transcriptomics, and systems biology. My research primed on constructing reliable gene regulatory networks and uncovering key factors that regulate these networks, driving changes in biological phenotypes. By analyzing such gene regulatory networks from single-cell or spatial data, my goal is to reveal and control cell fate decisions. I also explore processes such as differential gene expression and cellular trajectory construction to gain deeper insights into cellular behavior. Ultimately, I aim to simulate these complex processes computationally, with the long-term vision of developing strategies to manipulate cell fate, potentially leading to breakthroughs in the treatment and reversion of cancer and other severe diseases.

Keywords
Bioinformatics, Single cell genomics, Spatial transcriptomics, Systems biology

Minkyung Kim (Life Science & Biological Information SW)

minkyung32@kaist.ac.kr

Research Interests
I want to research to advance healthcare infrastructure and broaden patient treatment options through personalized medicine. Personalized medicine provides treatment strategies based on an individual's genome, but it targets only specific genetic markers. It can overlook the complex interactions among these markers. Therefore, I think it is crucial to understand the intricate interactions within gene regulatory networks using a systems biology approach. Through computer simulations, I aim to discover therapeutic targets that can lead to more effective cancer treatments. This work will contribute to the advancement of precision medicine, ultimately aiming to enhance treatment options for patients.

Keywords
Cancer Biology, System biology, Bioinformatics