Hai Phan
Education
Ph.D.; CNRS, University Motpellier 2; Computer Science And Engineering; 2013
M.S.; Konkuk University; Computer Science And Engineering; 2010
B.S.; HCM City University of Technology; Computer Science And Engineering; 2008
M.S.; Konkuk University; Computer Science And Engineering; 2010
B.S.; HCM City University of Technology; Computer Science And Engineering; 2008
2024 Fall Courses
DS 790A - DOCT DISSERTATION & RES
IS 488 - INDEPENDENT STUDY IN INFO
IS 489 - INFO UNDERGRAD THESIS RESEARCH
IS 700B - MASTER'S PROJECT
IS 701B - MASTER'S THESIS
IS 776 - IS RESEARCH STUDY
DS 700B - MASTER'S PROJECT
DS 725 - INDEPENDENT STUDY I
IS 792 - PRE-DOCTORAL RESEARCH
IS 726 - INDEPENDENT STUDY II
DS 726 - INDEPENDENT STUDY II
DS 791 - GRADUATE SEMINAR
DS 792B - PRE-DOCTORAL RESEARCH
IS 790A - DOCT DISSERTATION & RES
IS 725 - INDEPENDENT STUDY I
DS 677 - DEEP LEARNING
IS 488 - INDEPENDENT STUDY IN INFO
IS 489 - INFO UNDERGRAD THESIS RESEARCH
IS 700B - MASTER'S PROJECT
IS 701B - MASTER'S THESIS
IS 776 - IS RESEARCH STUDY
DS 700B - MASTER'S PROJECT
DS 725 - INDEPENDENT STUDY I
IS 792 - PRE-DOCTORAL RESEARCH
IS 726 - INDEPENDENT STUDY II
DS 726 - INDEPENDENT STUDY II
DS 791 - GRADUATE SEMINAR
DS 792B - PRE-DOCTORAL RESEARCH
IS 790A - DOCT DISSERTATION & RES
IS 725 - INDEPENDENT STUDY I
DS 677 - DEEP LEARNING
Past Courses
DS 789: TRUSTWORTHY ARTIFICIAL INTELLIGENCE
DS 791: GRADUATE SEMINAR
IS 333: SOCIAL NETWORK ANALYSIS
IS 665: DATA ANALYTICS FOR INFO SYSTEM
IS 688: WEB MINING
IS 698: EMERGING TOPICS IN DEEP LEARNING - ARTIFICIAL INTELLIGENCE
DS 791: GRADUATE SEMINAR
IS 333: SOCIAL NETWORK ANALYSIS
IS 665: DATA ANALYTICS FOR INFO SYSTEM
IS 688: WEB MINING
IS 698: EMERGING TOPICS IN DEEP LEARNING - ARTIFICIAL INTELLIGENCE
Journal Article
Jiang, Xiaopeng, & Hu, Han, & On, Thinh, & Lai, Phung, & Mayyuri, Vijaya , & Chen, An, & Shila, Devu, & Larmuseau, Adriaan, & Jin, Ruoming, & Borcea, Cristian M., & Phan, Hai Nhat (2024). FLSys: Toward an Open Ecosystem for Federated Learning Mobile Apps. IEEE Transactions on Mobile Computing (IEEE TMC),
Zhu, Jianfeng, & Jin, Ruoming, & Yalamanchi, Neha, & Kenne, Deric, & Phan, Hai Nhat (2023). Exploring COVID-19’s Impact on Mental Health: A Longitudinal and Thematic Analysis of Reddit Users’ Discourse. Journal of Medical Internet Research,
Ayranci, Pelin, & Bandera, Cesar, & Phan, Hai Nhat, & Kenne, Derik, & Jin, Ruoming, & Li, Dong (2022). Distinguishing the Effect of Time Spent at Home During COVID-19 Pandemic on the Mental Health of Urban and Suburban College Students Using Cell Phone Geolocation. International Journal of Environmental Research and Public Health, 19(12),
Phan, Hai Nhat, & Bandera, Cesar (2022). Distinguishing the Effect of Time Spent at Home During COVID-19 Pandemic on the Mental Health of Urban and Suburban College Students Using Cell Phone Geolocation.
Phan, Hai Nhat (2022). OnML: An Ontology-based Approach for Interpretable Machine Learning.
Zhu, Jianfeng, & Jin, Ruoming, & Yalamanchi, Neha, & Kenne, Deric, & Phan, Hai Nhat (2023). Exploring COVID-19’s Impact on Mental Health: A Longitudinal and Thematic Analysis of Reddit Users’ Discourse. Journal of Medical Internet Research,
Ayranci, Pelin, & Bandera, Cesar, & Phan, Hai Nhat, & Kenne, Derik, & Jin, Ruoming, & Li, Dong (2022). Distinguishing the Effect of Time Spent at Home During COVID-19 Pandemic on the Mental Health of Urban and Suburban College Students Using Cell Phone Geolocation. International Journal of Environmental Research and Public Health, 19(12),
Phan, Hai Nhat, & Bandera, Cesar (2022). Distinguishing the Effect of Time Spent at Home During COVID-19 Pandemic on the Mental Health of Urban and Suburban College Students Using Cell Phone Geolocation.
Phan, Hai Nhat (2022). OnML: An Ontology-based Approach for Interpretable Machine Learning.
SHOW MORE
Liu, Guanxiong, & Khalil, Issa, & Khreishah, Abdallah, & Phan, Hai Nhat (2020). Trojans and adversarial examples: A lethal combination.
Liu, Guanxiong, & Khalil, Issa, & Khreishah, Abdallah, & Phan, Hai Nhat (2020). Trojans and Adversarial Examples: A Lethal Combination.
Liu, Guanxiong, & Khalil, Issa, & Khreishah, Abdallah, & Phan, Hai Nhat (2020). Trojans and Adversarial Examples: A Lethal Combination.
Liu, S, & Shih, Frank Y., & Russell, Gareth J., & Phan, Hai Nhat (2020). Classification of ecological data by deep learning. Pattern Recognition and Artificial Intelligence, 34(13), 2052010 .
Hu, Han, & Phan, Hai Nhat, & Chun, Soon A, & Geller, James, & Vo, Huy, & Ye, Xinyue, & Jin, Ruoming, & Ding, Kele, & Kenne, Deric, & Dou, Dejing (2019). An insight analysis and detection of drug-abuse risk behavior on Twitter with self-taught deep learning. Computational Social Networks, 6(1), 10.
Phan, Hai Nhat (2017). Preserving Differential Privacy in Convolutional Deep Belief Networks. Machine Learning, 106(9-10), 1681–1704.
Liu, Guanxiong, & Khalil, Issa, & Khreishah, Abdallah, & Phan, Hai Nhat (2020). Trojans and Adversarial Examples: A Lethal Combination.
Liu, Guanxiong, & Khalil, Issa, & Khreishah, Abdallah, & Phan, Hai Nhat (2020). Trojans and Adversarial Examples: A Lethal Combination.
Liu, S, & Shih, Frank Y., & Russell, Gareth J., & Phan, Hai Nhat (2020). Classification of ecological data by deep learning. Pattern Recognition and Artificial Intelligence, 34(13), 2052010 .
Hu, Han, & Phan, Hai Nhat, & Chun, Soon A, & Geller, James, & Vo, Huy, & Ye, Xinyue, & Jin, Ruoming, & Ding, Kele, & Kenne, Deric, & Dou, Dejing (2019). An insight analysis and detection of drug-abuse risk behavior on Twitter with self-taught deep learning. Computational Social Networks, 6(1), 10.
Phan, Hai Nhat (2017). Preserving Differential Privacy in Convolutional Deep Belief Networks. Machine Learning, 106(9-10), 1681–1704.
COLLAPSE
Conference Paper
How to Backdoor HyperNetwork in Personalized Federated Learning?
NeurIPS 2023 - Backdoor in Deep Learning, December 2023
Differential Privacy in HyperNetworks for Personalized Federated Learning
The 32nd ACM International Conference on Information and Knowledge Management (ACM CIKM 2023), July (3rd Quarter/Summer) 2023
Active Membership Inference Attack under Local Differential Privacy in Federated Learning
The 26th International Conference on Artificial Intelligence and Statistics (AISTATS), April (2nd Quarter/Spring) 2023
XRand: Differentially Private Defense against Explanation-Guided Attacks
AAAI Conference on Artificial Intelligence (AAAI 2023), February 2023
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks
IEEE BigData 2022, December 2022
NeurIPS 2023 - Backdoor in Deep Learning, December 2023
Differential Privacy in HyperNetworks for Personalized Federated Learning
The 32nd ACM International Conference on Information and Knowledge Management (ACM CIKM 2023), July (3rd Quarter/Summer) 2023
Active Membership Inference Attack under Local Differential Privacy in Federated Learning
The 26th International Conference on Artificial Intelligence and Statistics (AISTATS), April (2nd Quarter/Spring) 2023
XRand: Differentially Private Defense against Explanation-Guided Attacks
AAAI Conference on Artificial Intelligence (AAAI 2023), February 2023
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks
IEEE BigData 2022, December 2022
SHOW MORE
Un-Fair Trojan: Targeted Backdoor Attacks Against Model Fairness
The 9th IEEE International Conference on Software Defined Systems (IEEE SDS-2022), December 2022
User-Entity Differential Privacy in Learning Natural Language Models
IEEE BigData 2022, December 2022
Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning
August 2022
A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples
December 2021
c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation
December 2021
Continual Learning with Differential Privacy
December 2021
Social and Motivational Factors for the Spread of Physical Activities in a Health Social Network
November 2021
The 9th IEEE International Conference on Software Defined Systems (IEEE SDS-2022), December 2022
User-Entity Differential Privacy in Learning Natural Language Models
IEEE BigData 2022, December 2022
Lifelong DP: Consistently Bounded Differential Privacy in Lifelong Machine Learning
August 2022
A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples
December 2021
c-Eval: A Unified Metric to Evaluate Feature-based Explanations via Perturbation
December 2021
Continual Learning with Differential Privacy
December 2021
Social and Motivational Factors for the Spread of Physical Activities in a Health Social Network
November 2021
COLLAPSE
Conference Proceeding
How to Backdoor HyperNetwork in Personalized Federated Learning?
2023
Zone-based Federated Learning for Mobile Sensing Data
The 21st IEEE International Conference on Pervasive Computing and Communications (PerCom 2023), March 2023
An ensemble deep learning model for drug abuse detection in sparse twitter-sphere
MEDINFO, August 2019
Classification of ecological data using deep learning methods
Global Conference on Biomedical Engineering, November 2018
Deep Learning Model for Classifying Drug Abuse Risk Behavior in Tweets
International Conference on Health Informatics, June 2018
Enabling Real-Time Drug Abuse Detection in Tweets
Proceedings of ICDE/HDMM, April (2nd Quarter/Spring) 2017
2023
Zone-based Federated Learning for Mobile Sensing Data
The 21st IEEE International Conference on Pervasive Computing and Communications (PerCom 2023), March 2023
An ensemble deep learning model for drug abuse detection in sparse twitter-sphere
MEDINFO, August 2019
Classification of ecological data using deep learning methods
Global Conference on Biomedical Engineering, November 2018
Deep Learning Model for Classifying Drug Abuse Risk Behavior in Tweets
International Conference on Health Informatics, June 2018
Enabling Real-Time Drug Abuse Detection in Tweets
Proceedings of ICDE/HDMM, April (2nd Quarter/Spring) 2017