South Korea, Daejeon

KAIST, School of Computing

IBS, Data Science Group

Assem Zhunis


Work experience

July 2020  - Present

IBS Data Science Group, S. Korea

Research Assistant. Chief Investigator - Meeyoung Cha. 

My projects include Sleep studies, Social media analysis, Human-AI interaction.  Research area: Computational Social Science, LLM, Human-AI interaction, and Big Data analysis. Tools: Python, R.

July 2022  - September 2022

CYENS Center of Excellence (fAIre MSG team), Cyprus

Research Intern (Online). Mentors:  Pr. Jahna Otterbacher & Dr. Styliani Kleanthous

This summer I worked on a project titled “Political Personalization on Twitter Upon Russo-Ukrainian War”. In this project, I tried to understand how leaders and countries are associated with each other during international disasters among English-speaking Twitter users. I was responsible for conceptualizing the idea, collecting and preprocessing the data, running the analysis, and writing the first draft of the manuscript for submission. [Website] [Presentation]

 January 2020 - February 2020

Software Security Lab, S. Korea

Web developer. Employer - Pr. Sang Kil Cha.

Created first UI prototypes of the educational website for hackers. Designed website pages and functionalities. Tools: Razor pages, .Net Core, SQLite, and C#.

January 2019  -  April 2019

Nano 2D Materials Lab, S. Korea

Research assistant. Employer - Pr. Kibum Kang. 

Studied 2 Dimensional Organic Nano Materials. Synthesis of MOF nanosheets.


Korea Advanced Institute of Science and Technology (KAIST)

Daejeon, South Korea

2017 fall - 2021 fall

Bachelor's in Computer Science (minor in Materials Science and Engineering)

Coursework: OS, Algorithms, Data Structures, Probabilistic Programming, ML in NLP, Graph ML and Mining, Big Data Analysis using R, Database & Big Data, Human-Computer Interaction, Human-AI Interaction, Social Computing, Computational Social Science, Computer Vision, Computer Graphics.

2022 spring - 2023 fall

Master's in Computer Science

Worked as TA for Data Science Methodology (CS564) and Introduction to Machine Learning (CS376) classes.


Research projects

We study how Sleep Dimensions like quality and quantity are explained by cultural norms and values. Here we analyze 52 million sleeping readings aggregated from wearable logs from 19 cities between 2014 and 2017 and examine how sleep is affected by culture. Accepted to Scientific Reports 2023.


This work examined user-chatbot interactions on a live platform and provides insights into people's informational and emotional needs during a global health crisis. Users sought health-related information and shared emotional messages with the chatbot, indicating the potential of future chatbots to provide accurate health information and emotional support.  Accepted to Journal of Medical Internet Research (JMIR), To Appear (IF=7.08).


In this work, we investigate how differently users express emotions online when interacting with a commercially available chatbot (Simsimi) and posting on a public social media platform (Twitter).  This is an ongoing project in collaboration with Simsimi corporation. The short paper is published at '"KCC 2021 Web Conference".

[PDF] [Paper]

In this work, I tried to understand how leaders and countries are associated with each other during international disasters among English-speaking Twitter users. Under review.


In this project, we use sentiment classifiers to analyze the public discourse on Twitter and compare the average sentiments in posts of individuals before and after the outbreak of the pandemic.  Published at '"KCC 2021 Web Conference". Presented at "BIEN 2021: The International Conference of Women Scientists and Engineers Conference on BT, IT, ET, and NT". Accepted to "TheWebConf22" (WWW'22), Lion, France.

[Paper] [Presentation]

We shed light on how empirical studies can contribute to the AI and robot rights debate by revealing the public perception of this issue and conducting several experiments with GAN-generated images. Published in the "Frontiers in Robotics and AI" journal, section Ethics in Robotics and Artificial Intelligence.

[Paper] [Data]

We present a generative simulation model that accounts for the economic and human capital cost of adopting some strategies against COVID-19, and provide an end-to-end pipeline to simulate the virus spread and the incurred loss of various policy combinations. Front. Public Health, 21 November 2022 Sec. Infectious Diseases: Epidemiology and Prevention

[Code] [Paper] [Poster]

Course Projects

App for crowdsourced music generation.

[Code] [Prototype]

Predicting river flows from satellite images. This project got 1st place at JunctionX Hackathon Seoul 2021


In these experiments, I compare different diffusion kernels for Graph diffusion Convolution. Original paper: Diffusion Improves Graph Learning by Klicpera et al. 

[Code] [Presentation]

In these experiments, we apply the INLP method for mitigating gender, race, and religious biases in the toxicity classification tasks.

[Code] [Presentation]

In this project, we developed an ML model using Qiskit for solving quantum problems. Qiskit Hackathon 2021. 


Summarization of YouTube lectures using BERT for better remote education. Coded the backend of a website for human-AI cooperation. Used tools: Flask, React, Python. 

[Code] [Prototype]

Analysis of Kaggle Soccer data. Conducted preprocessing and statistical analysis of the data. Predicted key features for successful soccer teams using R.

[Code] [Report]

NLP project on sentiment analysis of COVID-19 tweets. Implemented transfer learning for increasing performance of emotion classifier from 82% to 83%. Used tools: Python, NLTK.

[Code] [Report] [Video]

Recognitions & Awards







Reading 📖  : writing book reviews in personal Telegram channel (

Volunteering: Member of the volunteering club in Daejeon (Silver Lining)

Yoga 🧘‍♀️ : still can't stand still

Ukulele 🎶  : learned to play some Beatles songs during quarantine

Writing ✍️ : hoping to publish some crazy and boring novels