SelectedWorks - Tony T. Luo

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Selected Works of Tony T. Luo

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Associate Professor of Computer Science; Associate Chair for Academic Affairs

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This page is not regularly maintained. Move over to my Homepage for more up-to-date information.

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About Tony T. Luo

This page is not regularly maintained. Move over to my Homepage for more up-to-date information.

Positions

December 2023 - Present	Associate Chair for Academic Affairs, Missouri University of Science and Technology ‐ Computer Science
Institution Organization Position Type Position Title Time Period to Options Current Position Affiliate my profile with this Institution
December 2019 - Present	Associate Professor, Missouri University of Science and Technology ‐ Computer Science
Institution Organization Position Type Position Title Time Period to Options Current Position Affiliate my profile with this Institution
April 2012 - October 2019	Scientist and Program Lead, *ASTAR**
Institution Organization Position Type Position Title Time Period to Options Current Position Affiliate my profile with this Institution

Disciplines

Electrical and Computer Engineering and Computer Sciences

Research Interests

Internet of Things, Machine Learning, Trustworthy AI and IoT, and Cybersecurity

Grants

2023 - Present	AIoT Testbed Development (REU)
	National Science Foundation
	Role: PI
	$16,000
2022 - Present	CyberTraining: Deep Learning Systems on Advanced GPU Cyberinfrastructure
	National Science Foundation
	Role: PI
	$61,030
2020 - Present	Robust Federated Learning for Internet of Things
	National Science Foundation
	Role: PI
	$500,000

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Professional Service and Affiliations

2020 - Present	Member, AAAI
2020 - Present	Member, ACM
2019 - Present	Senior Member, Institute of Electrical and Electronics Engineers (IEEE)

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Honors and Awards

Honors and Awards

Best Paper Awards: 2012, 2015, 2018

Courses

Comp Sci 5001: Introduction to Deep Learning
Comp Sci 5420: Introduction to Machine Learning
Comp Sci 3402: Introduction to Data Science
Comp Sci 6407: Internet of Things with Data Science

Education

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2009	Ph.D., National University of Singapore
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Links

Google Scholar Profile
Scopus Author Profile
Dr. Luo's website

Contact Information

334 Computer Science Building

500 W. 15th Street

Missouri University of Science and Technology

Rolla, MO 65409

Email:

ORCID

http://orcid.org/0000-0003-2947-3111

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Featured Works
Recent Works
Research Works
White paper

Featured Works (2)

YOGA: Deep Object Detection in the Wild with Lightweight Feature Learning and Multiscale Attention (Raja Sunkara and Tie (Tony) (Tie) Luo) Pattern Recognition (2023)

We Introduce YOGA, a Deep Learning based Yet Lightweight Object Detection Model that Can Operate on Low-End Edge Devices While Still Achieving Competitive Accuracy. the YOGA Architecture Consists of a Two-Phase Feature Learning Pipeline with ...

TSI-GAN: Unsupervised Time Series Anomaly Detection using Convolutional Cycle-Consistent Generative Adversarial Networks (Tie Luo) 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) (2023)

Recent Works (11)

LightESD: Fully-Automated and Lightweight Anomaly Detection Framework for Edge Computing (Tie Luo) IEEE International Conference on Edge Computing (EDGE) (2023)

One-Shot Federated Learning for LEO Constellations that Reduces Convergence Time from Days to 90 Minutes (Tie Luo) 24th IEEE International Conference on Mobile Data Management (MDM) (2023)

Optimizing Federated Learning in LEO Satellite Constellations via Intra-Plane Model Propagation and Sink Satellite Scheduling (Tie Luo) IEEE International Conference on Communications (ICC) (2023)

TSI-GAN: Unsupervised Time Series Anomaly Detection using Convolutional Cycle-Consistent Generative Adversarial Networks (Tie Luo) 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) (2023)

YOGA: Deep Object Detection in the Wild with Lightweight Feature Learning and Multiscale Attention (Tie Luo) Pattern Recognition (2023)

Black-Box Attack using Adversarial Examples: A New Method of Improving Transferability (Tie Luo) World Scientific Annual Review of Artificial Intelligence (2023)

AsyncFLEO: Asynchronous Federated Learning for LEO Satellite Constellations with High-Altitude Platforms (Tie Luo) IEEE International Conference on Big Data (2022)

Learning Deep Representations via Contrastive Learning for Instance Retrieval (Tie Luo) IEEE Symposium Series On Computational Intelligence (SSCI) (2022)

Long-Short History of Gradients Is All You Need: Detecting Malicious and Unreliable Clients in Federated Learning (Tie Luo) European Symposium on Research in Computer Security (ESORICS) (2022)

No More Strided Convolutions or Pooling: A New CNN Building Block for Low-Resolution Images and Small Objects (Tie Luo) European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) (2022)

Adaptive Anomaly Detection for Internet of Things in Hierarchical Edge Computing: A Contextual-Bandit Approach (Tie Luo) ACM Transactions on Internet of Things (TIOT) (2021)

Research Works (74)

CR-SAM: Curvature Regularized Sharpness-Aware Minimization (Tao Wu, Tony Tie Luo and Donald C. Wunsch) Proceedings of the AAAI Conference on Artificial Intelligence (2024)

The Capacity to Generalize to Future Unseen Data Stands as One of the Utmost Crucial Attributes of Deep Neural Networks. Sharpness-Aware Minimization (SAM) Aims to Enhance the Generalizability by Minimizing Worst-Case Loss using One-Step Gradient ...

LRS: Enhancing Adversarial Transferability through Lipschitz Regularized Surrogate (Tao Wu, Tony Tie Luo and Donald C. Wunsch) Proceedings of the AAAI Conference on Artificial Intelligence (2024)

The Transferability of Adversarial Examples is of Central Importance to Transfer-Based Black-Box Adversarial Attacks. Previous Works for Generating Transferable Adversarial Examples Focus on Attacking Given Pretrained Surrogate Models While the Connections between Surrogate Models and ...

Communication-Efficient Federated Learning For LEO Constellations Integrated With HAPs Using Hybrid NOMA-OFDM (Mohamed Elmahallawy, Tony T. Luo and Khaled Ramadan) IEEE Journal on Selected Areas in Communications (2024)

Space AI has become increasingly important and sometimes even necessary for government, businesses, and society. An active research topic under this mission is integrating federated learning (FL) with satellite communications (SatCom) so that numerous low ...

Catching Elusive Depression Via Facial Micro-Expression Recognition (Xiaohui Chen and Tony Tie (T.) Luo) IEEE Communications Magazine (2023)

Depression is a common mental health disorder that can cause consequential symptoms with continuously depressed mood that leads to emotional distress. One category of depression is Concealed Depression, where patients intentionally or unintentionally hide their ...

YOGA: Deep Object Detection in the Wild with Lightweight Feature Learning and Multiscale Attention (Raja Sunkara and Tie (Tony) (Tie) Luo) Pattern Recognition (2023)

We Introduce YOGA, a Deep Learning based Yet Lightweight Object Detection Model that Can Operate on Low-End Edge Devices While Still Achieving Competitive Accuracy. the YOGA Architecture Consists of a Two-Phase Feature Learning Pipeline with ...

TSI-GAN: Unsupervised Time Series Anomaly Detection using Convolutional Cycle-Consistent Generative Adversarial Networks (Tie Luo) 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) (2023)

LightESD: Fully-Automated and Lightweight Anomaly Detection Framework for Edge Computing (Ronit Das and Tie (Tony) T. Luo) Proceedings - IEEE International Conference on Edge Computing (2023)

Anomaly Detection is Widely Used in a Broad Range of Domains from Cybersecurity to Manufacturing, Finance, and So On. Deep Learning based Anomaly Detection Has Recently Drawn Much Attention Because of its Superior Capability of ...

No More Strided Convolutions or Pooling: A New CNN Building Block for Low-Resolution Images and Small Objects (Raja Sunkara and Tony Tie Luo) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2023)

Convolutional Neural Networks (CNNs) Have Made Resounding Success in Many Computer Vision Tasks Such as Image Classification and Object Detection. However, their Performance Degrades Rapidly on Tougher Tasks Where Images Are of Low Resolution or ...

One-Shot Federated Learning For LEO Constellations That Reduces Convergence Time From Days To 90 Minutes (Mohamed Elmahallawy and Tie (Tony) Tie Luo) Proceedings - IEEE International Conference on Mobile Data Management (2023)

A Low Earth orbit (LEO) satellite constellation consists of a large number of small satellites traveling in space with high mobility and collecting vast amounts of mobility data such as cloud movement for weather forecast, ...

Optimizing Federated Learning In LEO Satellite Constellations Via Intra-Plane Model Propagation And Sink Satellite Scheduling (Mohamed Elmahallawy and Tie (Tony) T. Luo) IEEE International Conference on Communications (2023)

The advances in satellite technology developments have recently seen a large number of small satellites being launched into space on Low Earth orbit (LEO) to collect massive data such as Earth observational imagery. The traditional ...

TSI-GAN: Unsupervised Time Series Anomaly Detection using Convolutional Cycle-Consistent Generative Adversarial Networks (Shyam Sundar Saravanan, Tie (Tony) T. Luo and Mao Van Ngo) Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2023)

Anomaly Detection is Widely Used in Network Intrusion Detection, Autonomous Driving, Medical Diagnosis, Credit Card Frauds, Etc. However, Several Key Challenges Remain Open, Such as Lack of Ground Truth Labels, Presence of Complex Temporal Patterns, ...

Learning Deep Representations via Contrastive Learning for Instance Retrieval (Tie Luo) IEEE Symposium Series On Computational Intelligence (SSCI) (2022)

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