學生招募

我在中央大學資工系擔任助理教授一職，正在招收有興趣的專題生，碩士生，或博士生加入自動化系統與AI實驗室。 實驗室著重兩個領域: 在自動化系統上的排程問題，在機器學習上的隱私、公平、透明度、可解釋性的問題。可以從google scholar上參考我的最近研究。

1. 舉凡機器人、無人機、甚至無線傳播，只要牽扯到多個行動或多個目標皆屬於自動化系統之範疇，如自動化巡邏、工廠自動化系統等。我們著重在系統的理論與演算法設計上。

2. 實驗室也同時在機器學習的理論面有所研究，多聚焦當"人類"使用此類工具時所會造成的社會影響與信任問題，如隱私性、公平性、可解釋性等。 

        給碩士生: 若你是除了動手做以外，更喜歡問"為什麼"要這樣做? 那本實驗室會非常契合你。另外，實驗室是以"研究"為主，我希望學生能從研究中得到樂趣，對於自己的最後作品感到驕傲，我們的合作也會建立在這之上。至於甚麼是研究? 我認為是一個提出與解決問題的完整過程。這包含:題目，前人相關的研究，解決辦法，驗證與討論。具體如下:

題目: 問出一個讓人有興趣的問題

相關研究: 跟這問題相關的研究是甚麼，為什麼沒辦法完全解決這個題目呢

解決辦法: 我們想出來的解決辦法是甚麼

驗證與討論: 說服 (用實驗或證明)別人我們的解決辦法解決了甚麼，或是沒有解決了甚麼。

        研究本身就很難，所以我不會開出硬性的規定，我重視的是這段期間能否學到一套完整的，解決問題的辦法，讓學生能帶到之後的職涯上。無論是專題或是碩論都是學生自己的作品，所以我希望這段過程中以學生能保持研究熱忱為主要目標，研究方向上我很歡迎學生提出自己的想法來互相討論，以我們是一個團隊的方式來完成這份研究。如果你有興趣，歡迎你寫信來或是約個時間聊聊。

P.S.，若之後有興趣出國發展(無論念書或是工作)，我本身還有跟數個不同的歐美教授合作，包括Rutgers University, Stony Brook University, University of Edinburgh, City University of New York...etc. 也會有一起的meeting可以參加合作。另外在準備出國申請學校上我也有不少經驗，都可以討論。

自介

我的博士學位是在2020年於美國石溪大學取得，由Prof. Jie Gao and Prof. Shan Lin 指導。這之後，我在Sunrise technology 擔任一年的研究科學家並從2021年9月到2022年7月於愛丁堡大學資訊學院擔任博士後研究，由 Prof. Rik Sarkar指導。

       我的研究領域主要是放在自動化系統，資料隱私，物聯網上並擅長從演算法，機器學習，或是資料科學的角度去解決問題。 我關注的問題通常都是當AI進入到人類生活之後所產生的挑戰以及各種排程問題。大方向上，都是如何安排有限的資源去達成目標，當牽扯到人類行為後，這些目標通常會比傳統的複雜或是包含多個不同需整合的目標。以機器人巡邏來維護治安來舉例，光是犯罪的面向就有分成深思熟慮的作案(e.g., 有計畫的銀行搶案)以及臨時起意(e.g., 肇事逃逸)等，對於不同的犯罪就會需要設計出完全不同的巡邏路徑。對於深思熟慮的作案，機器人設計的路線若是太過呆版，簡單，那犯罪者便可以藉由簡單的觀察來準確預測它接下來的位置，甚而避開機器人的巡邏時間。因此，加入一些隨機性在巡邏路徑上就會是必要的，但接踵而來的問題便是: 怎麼知道加入多少隨機性? 會如何影響效率?(加入隨機性勢必使得巡邏時間拉長，導致效率變差)。而把這種大問題切開來並用數學語言重新定義並釐清問題，最後找出適當的解決辦法以及了解不能解決的部分，便是我身為研究者的工作。

Research Interest

• Scheduling Algorithm in Autonomous System

Classic problems such as path finding/ patrolling for robots. The developed solutions include both approximation algorithm and reinforcement learning. I am recently interested in scheduling problems under privacy issues. This includes two directions: (a.) scheduling under information leakage and (b.) scheduling without revealing sensitive information. There are some preliminary works published in AAMAS, WAFR, INFOCOM.. and other works are ongoing.

• Scheduling in Wireless Sensor Network, IoT, and Smart Building

As sensors and robots become ubiquitous in many different applications, efficiently assigning resources to provide reliable and ensure the quality of service is a crucial problem. I have several works discussed the scheduling problems for heterogenous transmissions in wireless sensor network published in TOSN, SECON, and ALGOSENSOR. 

• Data Science and Machine Learning

I also have multidisciplinary works that involve data analysis/ machine learning in multiple fields such as high-speed physical trigger detection, spam calls analysis and political donation analysis, player styles analysis in gaming.

Selected Publications

• Understanding Endogenous Data Drift in Adaptive Models with Recourse-Seeking Users (AIES 2025)

• Obtaining approximately optimal and diverse solutions via dispersion (LATIN 2022)

• Approximation Algorithms for Multi-Robot Patrol-Scheduling with Min-Max Latency. (WAFR 2020)

  • Online presentation 

• Patrol security game: Defending against adversary with freedom in attack timing, location, and duration  (TCPS 2026, AAMAS 2019)

Recent Publications (2022 - 2026)

Journal

1. Yang, Hao-Tsung, Ting-Kai Weng, Ting-Yu Chang, Kin Sum Liu, Shan Lin, Jie Gao, and Shih-Yu Tsai. “Patrol Security Game: Defending against Adversary with Freedom in Attack Timing, Location, and Duration.” ACM Transactions on Cyber-Physical Systems, vol. 10, no. 2, 2026, pp. 26:1–26:26.

2. Nguyen, Thi Anh Nguyet, Fu-Chang Chien, Thi Dieu Khanh Huynh, H. Kim Nhat, Y. C. Chiu, Hao-Tsung Yang, et al. “Hybrid-Free DNA Test by Band Engineering of Nitride Semiconductor and Machine Learning.” ACS Applied Electronic Materials, vol. 7, no. 8, 2025, pp. 3255–3263.

3. Wu, Min-Hao, Fu-Hau Hsu, Jian-Hung Huang, Keyuan Wang, Yan-Ling Hwang, Hao-Jyun Wang, Jian-Xin Chen, Teng-Chuan Hsiao, and Hao-Tsung Yang. “Enhancing Linux System Security: A Kernel-Based Approach to Fileless Malware Detection and Mitigation.” Electronics, vol. 13, no. 17, 2024, article 3569.

4. Wu, Min-Hao, Fu-Hau Hsu, Jian-Hong Huang, Keyuan Wang, Yen-Yu Liu, Jian-Xin Chen, Hao-Jyun Wang, and Hao-Tsung Yang. “MPSD: A Robust Defense Mechanism against Malicious PowerShell Scripts in Windows Systems.” Electronics, vol. 13, no. 18, 2024, article 3717.

Major / Top-tier International Conference (Based on CORE/ICORE、CSRankings)

5. Liu, Bo-Yi, Zhi-Xuan Liu, Kuan Lun Chen, Shih-Yu Tsai, Jie Gao, and Hao-Tsung Yang. “Understanding Endogenous Data Drift in Adaptive Models with Recourse-Seeking Users.” Proceedings of the Eighth AAAI/ACM Conference on AI, Ethics, and Society, 2025, pp. 1598–1610.

6. Rozemberczki, Benedek, Lauren Watson, Péter Bayer, Hao-Tsung Yang, Olivér Kiss, Sebastian Nilsson, and Rik Sarkar. “The Shapley Value in Machine Learning.” Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022, pp. 5572–5579.

7. Afshani, Peyman, Mark de Berg, Kevin Buchin, Jie Gao, Maarten Löffler, Amir Nayyeri, Benjamin Raichel, Rik Sarkar, Haotian Wang, and Hao-Tsung Yang. “On Cyclic Solutions to the Min-Max Latency Multi-Robot Patrolling Problem.” Proceedings of the 38th International Symposium on Computational Geometry, LIPIcs, vol. 224, 2022, article 2, pp. 2:1–2:14.

8. Gao, Jie, Mayank Goswami, C. S. Karthik, Meng-Tsung Tsai, Shih-Yu Tsai, and Hao-Tsung Yang. “Obtaining Approximately Optimal and Diverse Solutions via Dispersion.” LATIN 2022: Theoretical Informatics—15th Latin American Symposium, Lecture Notes in Computer Science, vol. 13568, Springer, 2022, pp. 222–239.

Conference / Workshop / Local & Applied Conference

9. Chen, Wei-Yu, Ta-Wei Wang, Peggy Joy Lu, Hao-Tsung Yang, and Vincent Shin-Mu Tseng. “Temporal Graph Convolutional Networks for Environmental Anomaly Detection.” Proceedings of the IIAI International Congress on Advanced Applied Informatics (IIAI-AAI 2025), 2025.

10. Chen, Li-Hsuan, Wing-Kai Hon, Ling-Ju Hung, Pei-Hsuan Hsu, Ching-Kai Wang, and Hao-Tsung Yang. “Multi-Robot Patrol-Scheduling with Min-Max Latency on Stars.” IET International Conference on Engineering Technologies and Applications (ICETA 2025), 2025, pp. 131–132. https://doi.org/10.1049/icp.2026.1985.

11. Huang, Yen-Lung, Ming-Hsi Weng, and Hao-Tsung Yang. “PXGen: A Post-hoc Explainable Method for Generative Models.” Proceedings of the 29th International Conference on Technologies and Applications of Artificial Intelligence (TAAI 2024), 2024.

12. Chen, Wen-Ling, Hong-Chang Huang, Kai-Hung Lin, Shang-Wei Hwang, and Hao-Tsung Yang. “Pareto Optimal Algorithmic Recourse in Multi-cost Function.” Proceedings of the 29th International Conference on Technologies and Applications of Artificial Intelligence (TAAI 2024), 2024.