Publications
Sheo yon Jhin, Seojin Kim, and Noseong Park, "Addressing Prediction Delays in Time Series Forecasting: A Continuous GRU Approach with Derivative Regularization," ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024
Jayoung Kim, Yehjin Shin, Jeongwhan Choi, Hyowon Wi, and Noseong Park, "Polynomial-based Self-Attention for Table Representation Learning," International Conference on Machine Learning (ICML), 2024
Jeongwhan Choi, Sumin Park, Hyowon Wi, Sung-Bae Cho, and Noseong Park, "PANDA: Expanded Width-Aware Message Passing Beyond Rewiring," International Conference on Machine Learning (ICML), 2024
Woojin Cho, Minju Jo, Haksoo Lim, Kookjin Lee, Dongeun Lee, Sanghyun Hong, and Noseong Park, "Parameterized Physics-informed Neural Networks for Parameterized PDEs," International Conference on Machine Learning (ICML), 2024
Hyeyoon Lee, Kanghyun Choi, Dain Kwon, SunJong Park, Mayoore Selvarasa Jaiswal, Noseong Park, Jonghyun Choi, and Jinho Lee, "DataFreeShield: Defending Adversarial Attacks without Training Data," International Conference on Machine Learning (ICML), 2024
Seoyoung Hong, Jeongwhan Choi, Yeon-Chang Lee, Srijan Kumar, and Noseong Park, "SVD-AE: Simple Autoencoders for Collaborative Filtering," International Joint Conference on Artificial Intelligence (IJCAI), 2024
Jinsung Jeon and Noseong Park, "SPI-GAN: Denoising Diffusion GANs with Straight-Path Interpolations," ICLR Workshop on Practical ML for Limited/Low-resource Settings (PML4LRS), 2024
Woojin Cho, Minju Jo, Haksoo Lim, Kookjin Lee, Dongeun Lee, Sanghyun Hong, and Noseong Park, "Extension of Physics-informed Neural Networks to Solving Parameterized PDEs," ICLR Workshop on AI4DifferentialEquations in Science (AI4DiffEqtnsInSci), 2024
Jinsung Jeon, Hyundong Jin, Jonghyun Choi, Sanghyun Hong, Dongeun Lee, Kookjin Lee, and Noseong Park, "PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images," International Conference on Learning Representations (ICLR), 2024
Youn-Yeol Yu, Jeongwhan Choi, Woojin Cho, Kookjin Lee, Nayong Kim, Kiseok Chang, Changseung Woo, Ilho Kim, Seokwoo Lee, Joon Young Yang, Sooyoung Yoon, and Noseong Park, "Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer," International Conference on Learning Representations (ICLR), 2024
Yehjin Shin, Jeongwhan Choi, Hyowon Wi, and Noseong Park, "An Attentive Inductive Bias for Sequential Recommendation beyond the Self-Attention," AAAI Conference on Artificial Intelligence (AAAI), 2024
Woojin Cho, Seunghyeon Cho, Hyundong Jin, Jinsung Jeon, Kookjin Lee, Sanghyun Hong, Dongeun Lee, Jonghyun Choi, and Noseong Park, "Operator-learning-inspired Modeling of Neural Ordinary Differential Equations," AAAI Conference on Artificial Intelligence (AAAI), 2024
Hyowon Wi, Yehjin Shin, and Noseong Park, "Continuous-time Autoencoders for Regular and Irregular Time Series Imputation," ACM International Web Search and Data Mining Conference (WSDM), 2024
Seonkyu Lim, Jaehyeon Park, Seojin Kim, Hyowon Wi, Haksoo Lim, Jinsung Jeon, Jeongwhan Choi, and Noseong Park, "Long-term Time Series Forecasting based on Decomposition and Neural Ordinary Differential Equations," IEEE International Conference on Big Data (IEEE BigData), 2023
Woojin Cho, Kookjin Lee, Donsub Rim, and Noseong Park, "Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks," Conference on Neural Information Processing Systems (NeurIPS), 2023
Jaehoon Lee, Chan Kim, Gyumin Lee, Haksoo Lim, Jeongwhan Choi, Kookjin Lee, Dongeun Lee, Sanghyun Hong, and Noseong Park, "HyperNetwork Approximating Future Parameters for Time Series Forecasting under Temporal Drifts," NeurIPS Workshop on Distribution Shifts (DistShift), 2023
Haksoo Lim, Sewon Park, Minjung Kim, Jaehoon Lee, Seonkyu Lim, and Noseong Park, "MadSGM: Multivariate Anomaly Detection with Score-based Generative Models," ACM International Conference on Information and Knowledge Management (CIKM), 2023
Sheo Yon Jhin, Jaehoon Lee, and Noseong Park, "Precursor-of-Anomaly Detection for Irregular Time Series," ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
JaeYeon Park, Kichang Lee, Noseong Park, Seng Chan You, and JeongGil Ko, "Self-Attention LSTM-FCN Model for Arrhythmia Classification and Uncertainty Assessment," to appear in Artificial Intelligence In Medicine (IF=7.011), 2023
Jeongwhan Choi, Seoyoung Hong, Noseong Park, and Sung-Bae Cho, "GREAD: Graph Neural Reaction-Diffusion Networks," International Conference on Machine Learning (ICML), 2023
Chaejeong Lee, Jayoung Kim, and Noseong Park, "CoDi: Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis," International Conference on Machine Learning (ICML), 2023
Minju Jo, Seungji Kook, and Noseong Park, "Hawkes Process based on Controlled Differential Equations," International Joint Conference on Artificial Intelligence (IJCAI), 2023
Jeongwhan Choi, Seoyoung Hong, Noseong Park, and Sung-Bae Cho, "Blurring-Sharpening Process Models for Collaborative Filtering," International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023
Jeongwhan Choi, and Noseong Park, "Graph Neural Rough Differential Equations for Traffic Forecasting," ACM Transactions on Intelligent Systems and Technology (IF=10.489), Vol. 14, No. 4, 2023
Jaewon Jung, Jaeyong Song, Hongsun Jang, Hyeyoon Lee, Kanghyun Choi, Noseong Park, and Jinho Lee, "Fast Adversarial Training with Dynamic Batch-level Attack Control," Design Automation Conference (DAC), 2023
Jayoung Kim, Chaejeong Lee, and Noseong Park, "STaSy: Score-based Tabular Data Synthesis," International Conference on Learning Representations (ICLR), 2023
Sheo Yon Jhin, Minju Jo, Seungji Kook, and Noseong Park, "Learnable Path in Neural Controlled Differential Equations," AAAI Conference on Artificial Intelligence (AAAI), 2023
Seoyoung Hong, Minju Jo, Seungji Kook, Jaeeun Jung, Hyowon Wi, and Noseong Park, "TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering," IEEE International Conference on Big Data (IEEE BigData), 2022 [Best Student Paper Award]
Jinsung Jeon, Jeonghak Kim, Haryong Song, Seunghyeon Cho, and Noseong Park, "GT-GAN: General Purpose Time Series Synthesis with Generative Adversarial Networks," Conference on Neural Information Processing Systems (NeurIPS), 2022
Hwangyong Choi, Jeehyun Hwang, Jeongwhan Choi, Kookjin Lee, Dongeun Lee, and Noseong Park, "Climate Modeling with Neural Diffusion Equations," to appear in Knowledge and Information Systems (IF=3.205)
Sheo Yon Jhin, Heejoo Shin, Sujie Kim, Seoyoung Hong, Solhee Park, Noseong Park, Seungbeom Lee, Hwiyoung Maeng, and Seungmin Jeon, "Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting," to appear in Knowledge and Information Systems (IF=3.205)
Taeri Kim, Noseong Park, Jiwon Hong, and Sang-Wook Kim, "Phishing URL Detection: A Network-based Approach Robust to Evasion," ACM Conference on Computer and Communications Security (CCS), 2022
Seoyoung Hong, Heejoo Shin, Jeongwhan Choi, and Noseong Park, "Prediction-based One-shot Dynamic Parking Pricing," ACM International Conference on Information and Knowledge Management (CIKM), 2022, Full Research Paper
Jihyeon Hyeong, Jayoung Kim, Noseong Park, and Sushil Jajodia, "An Empirical Study on the Membership Inference Attack against Tabular Data Synthesis Models," ACM International Conference on Information and Knowledge Management (CIKM), 2022, Short Research Paper
Manh Tuan Do, Noseong Park, and Kijung Shin, "Two-Stage Training of Graph Neural Networks for Graph Classification," to appear in Neural Processing Letters (IF=2.565)
Seunghyeon Cho, Sanghyun Hong, Kookjin Lee, and Noseong Park, "AdamNODEs: When Neural ODE Meets Adaptive Moment Estimation," ICML Workshop on Continuous Time Methods for Machine Learning, 2022
Jayoung Kim, ChaeJeong Lee, Yehjin Shin, Sewon Park, Minjung Kim, Noseong Park, and Jihoon Cho, "SOS: Score-based Oversampling Minor Classes for Tabular Data," ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022
Kanghyun Choi, Hye Yoon Lee, Deokki Hong, Joonsang Yu, Noseong Park, Youngsok Kim, and Jinho Lee, "It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
Thai Le, Noseong Park, and Dongwon Lee, "SHIELD: Defending Textual Neural Networks against Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher," Annual Meeting of the Association for Computational Linguistics (ACL), 2022
Deokki Hong, Kanghyun Choi, Hey Yoon Lee, Joonsang Yu, Youngsok Kim, Noseong Park, and Jinho Lee, "Enabling Hard Constraints in Differentiable Neural Network and Accelerator Co-Exploration," Design Automation Conference (DAC), 2022
Jaehoon Lee, Jinsung Jeon, Sheo yon Jhin, Jihyeon Hyeong, Jayoung Kim, Minju Jo, Seungji Kook, and Noseong Park, "LORD: Lower-Dimensional Embedding of Log-Signature in Neural Rough Differential Equations," International Conference on Learning Representations (ICLR), 2022
Sheo Yon Jhin, Jaehoon Lee, Minju Jo, Seungji Kook, Jinsung Jeon, Jihyeon Hyeong, Jayoung Kim and Noseong Park, "EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting," The Web Conference (WWW), 2022
Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang, Noseong Park, "Graph Neural Controlled Differential Equations for Traffic Forecasting," AAAI Conference on Artificial Intelligence (AAAI), 2022
Taeyong Kong, Taeri Kim, Jinsung Jeon, Jeongwhan Choi, Yeon-Chang Lee, Noseong Park, and Sang-Wook Kim, "Linear, or Non-Linear, That is the Question!," ACM International WSDM Conference (WSDM), 2022
Jaehoon Lee, Jihyeon Hyung, Jinsung Jeon, Noseong Park, and Jihoon Cho, "Invertible Tabular GANs: Killing Two Birds with One Stone for Tabular Data Synthesis," Conference on Neural Information Processing Systems (NeurIPS), 2021
Kanghyun Choi, Deokki Hong, Noseong Park, Youngsok Kim, and Jinho Lee, "Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples," Conference on Neural Information Processing Systems (NeurIPS), 2021
Jeehyun Hwang, Jeongwhan Choi, Hwangyong Choi, and Noseong Park, "Climate Modeling with Neural Diffusion Equations," IEEE International Conference on Data Mining (ICDM), 2021
Sheo Yon Jhin, Heejoo Shin, Seoyoung Hong, Solhee Park, and Noseong Park, "Attentive Neural Controlled Differential Equations for Time-series Classification and Forecasting," IEEE International Conference on Data Mining (ICDM), 2021
Jinsung Jeon, Soyoung Kang, Minju Jo, Seunghyeon Cho, Noseong Park, Seonghoon Kim, and Chiyoung Song, "LightMove: A Lightweight Next-POI Recommendation for Taxicab Rooftop Advertising," ACM International Conference on Information and Knowledge Management (CIKM), 2021
Jeongwhan Choi, Jinsung Jeon, and Noseong Park, "LT-OCF: Learnable-Time ODE-based Collaborative Filtering," ACM International Conference on Information and Knowledge Management (CIKM), 2021
Sheo Yon Jhin, Minju Jo, Taeyong Kong, Jinsung Jeon, and Noseong Park, "ACE-NODE: Attentive Co-Evolving Neural Ordinary Differential Equations," ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
Duanshun Li, Jing Liu, Jinsung Jeon, Seoyoung Hong, Thai Le, Dongwon Lee, and Noseong Park, "Large-Scale Data-Driven Airline Market Influence Maximization," ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021
Duanshun Li, Jing Liu, Dongeun Lee, Ali Seyedmazloom, Giridhar Kaushik, Kookjin Lee, and Noseong Park, "A Novel Method to Solve Neural Knapsack Problems," International Conference on Machine Learning (ICML), 2021
Thai Le, Noseong Park, and Dongwon Lee, "A Sweet Rabbit Hole by DARCY: Using Honeypots to Detect Universal Trigger's Adversarial Attacks," Annual Meeting of the Association for Computational Linguistics (ACL), 2021
Jayoung Kim, Jinsung Jeon, Jaehoon Lee, Jihyeon Hyung, and Noseong Park, "OCT-GAN: Neural ODE-based Conditional Tabular GANs," The Web Conference (WWW), 2021
Jinsung Jeon, Jing Liu, Jayoung Kim, Jaehoon Lee, Jamie Jooyeon Lee, Ozlem Uzuner, Sushil Jajodia, and Noseong Park, "Scalable Graph Synthesis with Adj and 1 – Adj," SIAM International Conference on Data Mining (SDM), 2021
Jinsung Jeon,Dongeun Lee, Seunghyun Hwang,Soyoung Kang, Duanshun Li, Kookjin Lee, Jing Liu, and Noseong Park, "Large-Scale Flight Frequency Optimization with Global Convergence in the US Domestic Air Passenger Markets," SIAM International Conference on Data Mining (SDM), 2021
Jungeun Kim, Kookjin Lee, Dongeun Lee, Sheo Yon Jhin, and Noseong Park, "DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation," AAAI Conference on Artificial Intelligence (AAAI), 2021
Jonghoon Shin, Junhyung Moon, Beomsik Kim, Jihwan Eom, Noseong Park, and Kyoungwoo Lee, "Attention-based Stress Detection exploiting Non-contact Monitoring of Movement Patterns with IR-UWB radar," ACM/SIGAPP Symposium On Applied Computing (SAC), Poster, 2021
Jihoon Ko, Kyuhan Lee, Kijung Shin, and Noseong Park, "MONSTOR: An Inductive Approach for Estimating and Maximizing Influence over Unseen Networks," IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2020
Tanmoy Chakraborty, Noseong Park, Ayush Agarwal, and V. S. Subrahmanian, "Ensemble Detection and Analysis of Communities in Complex Networks," ACM Transactions on Data Science, 2020
Noseong Park, Andrea Pugliese, Edoardo Serra, and V. S. Subrahmanian, "Top-k User-Specified Preferred Answers in Massive Graph Databases," Data & Knowledge Engineering (IF=1.784), 2020.
Jing Liu, Yudi Chen, Duanshun Li, Noseong Park, Kisung Lee, and Dongwon Lee, "Predicting Influence Probabilities using Graph Convolutional Networks," the 2019 IEEE International Conference on Big Data (IEEE Big Data), 2019 [Code&Data]
Noseong Park, Nasheen Nur, Kookjin Lee, Hyunjoong Kang, and Soonhyeon Kwon, "Two Problems in Knowledge Graph Embedding: Non-Exclusive Relation Categories and Zero Gradients," the 2019 IEEE International Conference on Big Data (IEEE Big Data), Short Paper, 2019
Haipeng Chen, Jing Liu, Rui Liu, Noseong Park, and V. S. Subrahmanian, "VASE: A Twitter-based Vulnerability Analysis and Score Engine," the 19th IEEE International Conference on Data Mining (ICDM), Short Paper, 2019 [Code&Data]
Haipeng Chen, Jing Liu, Rui Liu, Noseong Park, and V. S. Subrahmanian, "VEST: A System for Vulnerability Exploit Scoring & Timing," the 28th International Joint Conference on Artificial Intelligence (IJCAI), Demo Paper, 2019 [Runner-up (2nd place) for the Innovation Award]
Haipeng Chen, Sushil Jajodia, Jing Liu, Noseong Park, Vadim Sokolov, and V. S. Subrahmanian, "FakeTables: Using GANs to Generate Functional Dependency Preserving Tables with Bounded Real Data," the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019
Haipeng Chen, Rui Liu, Noseong Park and V. S. Subrahmanian, "Using Twitter to Predict When Vulnerabilities will be Exploited," the 25th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2019
Nasheen Nur, Noseong Park, Mohsen Dorodchi, Wenwen Dou, Mohammad Javad Mahzoon, Xi Niu and Mary Lou Maher, "Student Network Analysis: A Novel Way to Predict Delayed Graduation in Higher Education," the 20th International Conference on Artificial Intelligence in Education (AIED; a top-tier education conference), 2019
Zhe Cui, Noseong Park, and Tanmoy Chakraborty, "Incremental Community Discovery Using Latent Network Representation and Probabilistic Inference," Knowledge and Information Systems (IF=2.247), 2019
Tanmoy Chakraborty, Saptarshi Ghosh, Noseong Park, "Ensemble-based Overlapping Community Detection using Disjoint Community Structures ," Knowledge-Based Systems (IF=4.396) , vol. 163, 2019
Ankesh Anand, Kshitij Gorde, Joel Moniz, Noseong Park, Tanmoy Chakraborty, and Bei-Tseng Chu, "Phishing URL Detection with Oversampling based on Text Generative Adversarial Networks," the 2018 IEEE International Conference on Big Data (IEEE Big Data), 2018
Chuqin Li, Xi Niu, Ahmad Al-Doulat and Noseong Park, "A Computational Approach to Finding Contradictions in User Opinionated Text," IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018
Noseong Park, Mahmoud Mohammadi, Kshitij Gorde, Sushil Jajodia, "Data Synthesis based on Generative Adversarial Networks," the 44th International Conference on Very Large Data Bases (VLDB), 2018 [Code&Data]
Tanmoy Chakraborty, Sushil Jajodia, Noseong Park, Andrea Pugliese, Edoardo Serra, and V. S. Subrahmanian, "Hybrid Adversarial Defense: Merging Honeypots and Traditional Security Methods," Journal of Computer Security, vol. 26, no. 5, 2018 [Authors in Alphabetical Order]
Hyunjoong Kang, Sanghyun Hong, Kookjin Lee, Noseong Park and Soonhyun Kwon, "On Integrating Knowledge Graph Embedding into SPARQL Query Processing," IEEE International Conference on Web Services (ICWS), Short Paper, 2018
David K. Park, Seungjoo Yoo, Hyojin Bahng, Jaegul Choo, Noseong Park, "MEGAN: Mixture of Experts of Generative Adversarial Networks for Image Generation for Multimodal Image Generation," International Joint Conference on Artificial Intelligence (IJCAI), 2018 [Code&Data]
Noseong Park, Ankesh Anand, Joel Ruben Antony Moniz, Kookjin Lee, Jaegul Choo, David K. Park, Tanmoy Chakraborty, Hongkyu Park, and Youngmin Kim, "MMGAN: Manifold Matching Generative Adversarial Network for Generating Images," the 24th International Conference on Pattern Recognition (ICPR), 2018 [Code&Data]
Tanmoy Chakraborty, Zhe Cui, and Noseong Park, "Metadata vs. Ground-truth: A Myth behind the Evolution of Community Detection Methods," the 27th International World Wide Web Conference (WWW; Poster), 2018
Francesco Parisi, Noseong Park, Andrea Pugliese, V. S. Subrahmanian, "Top-k User-Defined Vertex Scoring Queries in Edge-Labeled Graph Databases," ACM Transactions on the WEB, vol.12, no. 4 , 2018 [Authors in Alphabetical Order]
Sushil Jajodia, Noseong Park, Edoardo Serra, and V. S. Subrahmanian, "SHARE: A Stackelberg Honey-Based Adversarial Reasoning Engine," ACM Transactions on Internet Technology, vol. 18, no 3, March 2018 [Authors in Alphabetical Order]
Sanghyun Hong, Tanmoy Chakraborty, Sungjin Ahn, Ghaith Husari and Noseong Park, "SENA: Preserving Social Structure for Network Embedding," ACM Conference on Hypertext and Social Media (HT), Prague, Czech Republic, July 2017
Ankesh Anand, Tanmoy Chakraborty, Noseong Park, "We used Neural Networks to Detect Clickbaits: You won't believe what happened Next!," the 39th European Conference on Information Retrieval (ECIR), Aberdeen, Scotland UK, April 2017 [Code&Data]
Sushil Jajodia, Noseong Park, Fabio Pierazzi, Andrea Pugliese, Edoardo Serra, Gerardo I. Simari, V. S. Subrahmanian, "A Probabilistic Logic of Cyber Deception," IEEE Transactions on Information Forensics & Security, vol. 12, no. 11, 2017 [Authors in Alphabetical Order]
Bo An, Haipeng Chen, Noseong Park, and V. S. Subrahmanian, "Data-Driven Frequency-Based Airline Profit Maximization," ACM Transactions on Intelligent Systems and Technology, vol. 8, no. 4, 2017 [Code&Data] [Authors in Alphabetical Order]
Tanmoy Chakraborty, Noseong Park, and V. S. Subrahmanian, "Ensemble-Based Algorithms to Detect Disjoint and Overlapping Communities in Networks," IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2016 (acceptance rate 13%) [Best Paper Runner-up][Authors in Alphabetical Order]
Bo An, Haipeng Chen, Noseong Park, and V. S. Subrahmanian, "MAP: Maximizing Airline Profits using an Ensemble Game-Theoretic Forecasting Approach," ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016 [Code&Data] [Authors in Alphabetical Order]
Chanhyun Kang, Noseong Park, B. Aditya Prakash, Edoardo Serra, and V. S. Subrahmanian, "Ensemble Models for Data-driven Prediction of Malware Infections," ACM International Conference on Web Search and Data Mining (WSDM), 2016 (acceptance rate 18.2%)
Sushil Jajodia, Noseong Park, Edoardo Serra, and V. S. Subrahmanian, "Using Temporal Probabilistic Logic for Optimal Monitoring of Security Events with Limited Resources," Journal of Computer Security, vol. 24, no. 6, pp. 735-791, 2016 [Authors in Alphabetical Order]
Noseong Park, Edoardo Serra, Tom Snitch, and V. S. Subrahmanian, "APE: A Data-Driven, Behavioral Model Based Anti-Poaching Engine," IEEE Transactions on Computational Social Systems, vol. 2, no. 2, pp. 1-23, 2015 [NBC Nightly News], [Representative Research of UMD] [Authors in Alphabetical Order]
Noseong Park, Edoardo Serra, and V. S. Subrahmanian, "Saving Rhinos with Predictive Analytics," IEEE Intelligent Systems, vol. 30, no. 4, pp. 86-88, July-Aug. 2015 [Authors in Alphabetical Order]
Noseong Park, Michael Ovelgönne, and V. S. Subrahmanian, "Subgraph Matching and Centrality in Huge Social Networks," ASE/IEEE International Conference on Social Computing (SOCIALCOM), 2013 (overall acceptance rate 9.9%) [Best Paper Group 4.5%]
Michael Ovelgönne, Noseong Park, V. S. Subrahmanian, Elizabeth K. Bowman, and Kirk A. Ogaard, "Personalized Best Answer Computation in Graph Databases," the 12th International Semantic Web Conference (ISWC), 2013 (acceptance rate 21.5%) [Authors in Alphabetical Order]
Noseong Park, Bong Wan Kim, Yoonmee Doh, and Jongarm Jun, "A Multi-Access Asynchronous Low-Power MAC based on Preamble Sampling for WSNs, " Proc. of the IEEE Symposium on Computers and Communications (ISCC), 2011
Chan Yong Lee, Hong Il Cho, Gang Uk Hwang, Yoonmee Doh and Noseong Park, "Performance modeling and analysis of IEEE 802.15.4 slotted CSMA/CA protocol with ACK mode," AEU International Journal of Electronics and Communications, vol. 65, no. 2, pp. 123-131, 2011
Taehong Kim, Daeyoung Kim, Noseong Park, Seongeun Yoo and Tomás Sánchez López, "Shortcut tree routing in ZigBee Networks," Proc. of the IEEE International Symposium on Wireless Pervasive Computing (ISWPC), 2007
Taehong Kim, Noseong Park, Poh Kit Chong, Jongwoo Sung and Daeyoung Kim, "Distributed Low Power Scheduling in Wireless Sensor Networks," Proc. of the IEEE International Symposium on Wireless Pervasive Computing (ISWPC), 2007
Noseong Park, Daeyoung Kim, Yoonmee Doh, Sangsoo Lee and Ji-tae Kim, "An Optimal and Lightweight Routing for Minimum Energy Consumption in Wireless Sensor Networks," Proc. of the IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), 2005 (ppt)
Noseong Park, Daeyoung Kim, Jihoon Park and Yoonmee Doh, "Sub-network mobility analysis in wireless sensor networks," Proc. of the International Conference on Computer Communications and Networks (ICCCN), 2005
Sangsoo Lee, Daeyoung Kim, Sungjin Ahn and Noseong Park, "Power-Aware Position Vector Routing for Wireless Sensor Networks," Proc. of the IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC), 2005