Curriculum Vitae

Education

Ph.D. in Computer Science, Arizona State University — 2021 – 2026
- Data Mining and Machine Learning Lab
- Advisors: Dr. Huan Liu and Dr. Mickey Mancenido
- Funded by DHS-CAOE
M.E. in Computer Science & Engineering, Korea University, Seoul — 2017 - 2019
- Advisor: Dr. Jaewoo Kang
B.S. in Computer Science & Engineering, Korea University, Seoul — 2013 - 2017

Experience

Sep 2026 – Present — Applied AI Engineer, Cognizant, Remote
Sep 2025 – Dec 2025 — Applied Scientist Intern, Amazon, Bellevue WA
- Improved production sentiment forecasting models supporting community operations by developing advanced sequence modeling approaches and improving prediction robustness at scale.
- Designed and productionized an end-to-end ML pipeline spanning data collection, model training, experiment tracking, automated deployment, and monitoring using Python, AWS, MLflow, and CI/CD pipelines.
May 2025 – Aug 2025 — AI/ML Intern, AMD, Austin TX
- Architected and deployed Q-RAG, an enterprise question-centric Retrieval-Augmented Generation framework using synthetic QA generation and LLM-as-a-Judge evaluation to improve knowledge retrieval, identify documentation gaps, and reduce hallucinations across engineering support systems.
- Designed scalable AI evaluation infrastructure enabling automated benchmarking of enterprise RAG systems while significantly reducing manual expert review.
- Partnered with engineering stakeholders to identify knowledge management challenges, prototype AI solutions, iterate on user feedback, and deliver production-ready LLM workflows.
Aug 2024 – Dec 2024 — Software Development Intern, AMD, Austin TX
- Designed production AI inference architecture supporting enterprise RAG, multi-agent orchestration, user-feedback integration, and large-scale experimentation.
- Optimized AI inference and data pipelines to improve throughput, reduce evaluation latency, and eliminate performance bottlenecks across scalable production deployments.
May 2022 – Aug 2024 — Graduate Research Assistant, Department of Homeland Security (DHS-CAOE)
- PI: Dr. Erin K. Chiou; Co-PI: Dr. Michelle V. Mancenido
- Designed NLP solutions for topic modeling and text summarization using BERT and Llama-2.
- Architected a trustworthy multi-agent RAG system for AI-assisted intelligence analysis with researchers, domain experts, and software engineers.
- Delivered an interactive analytics dashboard for stakeholders to explore AI-generated insights through web-based visualizations.
Jan 2021 – Aug 2022 — Graduate Research Assistant, Office of Naval Research project, Arizona State University
- PI: Dr. Huan Liu
- Researched the integration and mutual influence of online and offline COVID-19 datasets using topic modeling.
- Analyzed 2M tweets for sentiment and stance detection in pandemic-related discussions.
Jan 2021 – May 2021 — Research Assistant, Arizona State University & Mathpresso
- PI: Dr. Sang Pil Han
Mar 2017 – Feb 2019 — Research Assistant, Korea University DMIS Lab — Seoul, Republic of Korea

Publications

A complete list is also available on my Google Scholar profile.

(* denotes equal contribution; bold denotes author of this page.)

2026

Adaptive Triggering for Bias Correction in LLM Reasoning
Nayoung Kim, Mickey Mancenido, Huan Liu
Under review, 2026.

Preprint Code

Increasing Transparency of LLM Systems Does Not Always Improve People’s Verification Behavior and Performance: Results from an Empirical Study of AI-Assisted Intelligence Analysis Reporting
Felix Gröner, Michelle V. Mancenido, Nayoung Kim, Emily Summers, Erin K. Chiou
Under review at Human Factors, 2026.

2025

PADTHAI-MM: A Principled Approach for the Design of Trustworthy, Human-Centered AI systems using the MAST Methodology
Myke C. Cohen, Nayoung Kim, Yang Ba, Anna Pan, Shawaiz Bhatti, Pouria Salehi, James Sung, Erik Blasch, Michelle V. Mancenido, Erin K. Chiou
AI Magazine, 2025.

PDF Code

2024

Robust Stance Detection: Understanding Public Perceptions in Social Media
Nayoung Kim, David Mosallanezhad, Lu Cheng, Michelle V. Mancenido, Huan Liu
International Conference on Social Networks Analysis and Mining (ASONAM), 2024.

PDF Code Slides

2023

Evaluating Trustworthiness of AI-Enabled Decision Support Systems: Validation of the Multisource AI Scorecard Table (MAST)
Pouria Salehi, Yang Ba, Nayoung Kim, David Mosallanezhad, Anna Pan, Myke C. Cohen, Yixuan Wang, Jieqiong Zhao, Shawaiz Bhatti, Michelle V. Mancenido, Erin K. Chiou
Journal of Artificial Intelligence Research, 2023.

PDF

2022

Debiasing Word Embeddings with Nonlinear Geometry
Lu Cheng, Nayoung Kim, Huan Liu
Proceedings of the 29th International Conference on Computational Linguistics (COLING), 2022.

PDF Code

Bridging the Gap: Commonality and Differences between Online and Offline COVID-19 Data
Nayoung Kim, Ahmadreza Mosallanezhad, Lu Cheng, Baoxin Li, Huan Liu
15th International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS), 2022.

PDF Code

Technical Skills

Large language models & agents — Retrieval-Augmented Generation (RAG), agentic AI, multi-agent systems, LangChain / LangGraph, LlamaIndex, LLM-as-a-judge, prompt engineering, synthetic data generation, inference-time scaling
Model training & alignment — model alignment, post-training, RLHF, RLAIF, LoRA, PEFT, responsible AI, AI safety
Retrieval & search — vector search, knowledge retrieval, embeddings, FAISS / Chroma, Elasticsearch
Machine learning — PyTorch, TensorFlow, Scikit-Learn, Hugging Face, Pandas, NumPy
Cloud & deployment — AWS, GCP, Docker, MLflow, WandB, TensorRT, model serving, GPU optimization, CI/CD
Software engineering — Flask, Node.js, REST APIs, Git, Linux, unit testing
Languages — Python, SQL, Java, JavaScript, Bash

Talks

Machine Learning Day 2024, Arizona State University, West Valley Campus — April 26, 2024
SCAI AI Day, Arizona State University — November 17, 2023

Teaching

Spring 2022 — Teaching Assistant, CSE 205: Object-Oriented Programming and Data Structures, Arizona State University (Instructor: Phillip Miller)
Fall 2021 — Teaching Assistant, CSE 205: Object-Oriented Programming and Data Structures, Arizona State University (Instructor: Faye Tadayon-Navabi)

Mentoring

Andre Ellini, Undergraduate, Barrett, The Honors College, ASU, 2024
Michael Clarkin, Undergraduate, Barrett, The Honors College, ASU, 2024
Robert Bradley, Undergraduate, Barrett, The Honors College, ASU, 2024

Service

Program Committee

ASONAM 2024, SBP-BRiMS 2023, ASONAM 2023

Conference Reviewer

AMLC 2025 (Gen AI Evaluation Workshop), NeurIPS 2025 (Reliable ML Workshop), AAAI 2023, EMNLP 2023, ECML-PKDD 2022, ACM Multimedia 2022, ASONAM 2022, ASONAM 2021, IEEE CogMI 2021

Volunteer

WSDM 2022, KDD 2021

Honors & Awards

SCAI Travel Award, Arizona State University, 2022 & 2024
Conference Scholarship, SBP-BRiMS, 2022
Fulton Scholarship, Ira A. Fulton Schools of Engineering, Arizona State University, 2021
General Scholarships, Korea University, 2017–2018
Work-Study Scholarship, Korea University, 2015
Academic Excellence Scholarship, Korea University, 2013