Yongsheng Mei, Mahdi Imani, and Tian Lan. "Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data", Accepted at the International Conference on Learning Representations (ICLR), May 2024.

K. gogineni, S. Dayapule, J. Gómez-Luna, K. Gogineni, P. Wei, T. Lan, M. Sadrosadati, O. Mutlu, and G. Venkataramani. "SwiftRL: Towards Efficient Reinforcement Learning on Real Processing-In-Memory Systems", In proceedings of the International Symposium on Performance Analysis of Systems and Software (ISPASS), May 2024.

Yongsheng Mei, Hanhan Zhou, and Tian Lan. "Projection-Optimal Monotonic Value Function Factorization in Multi-Agent Reinforcement Learning", Accepted at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2024.

Jiangong Chen, Tian Lan, and Bin Li. "GPT-VR Nexus: ChatGPT-Powered Immersive Virtual Reality Experience", Accepted at the IEEE Virtual Reality Conference (VR), Demo, May 2024.

Jingdi Chen, Carlee Joe-Wong, and Tian Lan. "RGMComm: Return Gap Minimization via Discrete Communications in Multi-Agent Reinforcement Learning", Accepted at the AAAI conference on Artificial Intelligence (AAAI), February 2024.

Huiqun Li, Hanhan Zhou, Yifei Zou, Dongxiao Yu, and Tian Lan. "ConcaveQ: Non-Monotonic Value Function Factorization via Concave Representations in Deep Multi-Agent Reinforcement Learning", Accepted at the AAAI conference on Artificial Intelligence (AAAI), February 2024.

Jingdi Chen, Hanhan Zhou, Yongsheng Mei, Gina Adam, Nathaniel Bastian, and Tian Lan. "Real-time Network Intrusion Detection via Decision Transformers", Accepted at the AAAI Artificial Intelligence for Cyber Security (AICS) Workshop, February 2024.

Zihao Zhao, Yuzhu Mao, Muhammad Zeeshan, Yang Liu, Tian Lan, Wenbo Ding. "AQUILA: Communication Efficient Federated Learning with Adaptive Quantization in Device Selection Strategy", Accepted at the IEEE Transactions on Mobile Computing (TMC), 2023.

Hanhan Zhou, Tian Lan, Guru Prasadh Venkataramani, and Wenbo Ding. "Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction", In proceedings of the Conference on Neural Information Processing Systems (NeurIPS), December 2023.

Jiayu Chen, Vaneet Aggarwal, and Tian Lan. "ODPP: A Unified Algorithm Framework for Unsupervised Option Discovery based on Determinantal Point Process", In proceedings of the Conference on Neural Information Processing Systems (NeurIPS), December 2023.

Hanhan Zhou, Vaneet Aggarwal, and Tian Lan. "Double Policy Estimation for Importance Sampling in Sequence Modeling-Based Reinforcement Learning", In proceedings of the NeurIPS 2023 Foundation Models for Decision Making Workshop (FMDM), December 2023.

Han Zhang, Xingang Shi, Xia Yin, Jilong Wang, Zhiliang Wang, Yingya Guo, Tian Lan, and Haijun Geng. "Achieving High Availability in Inter-DC WAN Traffic Engineering", IIEEE Transactions on Networking (ToN), vol. 31, no. 6, pp. 2406-2421, December 2023.

Jiayu Chen, Vaneet Aggarwal, Tian Lan. "Hierarchical Adversarial Inverse Reinforcement Learning", Accepted at IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.

Chenyi Liu, Vaneet Aggarwal, Tian Lan, Nan Geng, Yuan Yang, Mingwei Xu, Qing Li. "FERN: Leveraging Graph Attention Networks for Failure Evaluation and Robust Network Design", Accepted at IEEE Transactions on Networking (ToN), 2023.

Jingdi Chen, Lei Zhang, Joseph Riem, Gina Adam, Nathaniel D. Bastian, and Tian Lan. "RIDE: Real-time Intrusion Detection via Explainable Machine Learning Implemented in a Memristor Hardware Architecture", Accepted at IEEE Conference on Dependable and Secure Computing, Workshop on AI/ML for Cybersecurity (AIML), November 2023.

Jingdi Chen, Nakjung Choi, and Tian Lan. "Distributional-Utility Actor-Critic for Network Slice Performance Guarantee", Accepted at ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc), October 2023.

Jing Qiao, Shikun Shen, Shuzhen Chen, Xiao Zhang, Tian Lan, Xiuzhen Cheng, and Dongxiao Yu. "Communication Resources Limited Decentralized Learning with Privacy Guarantee through Over-the-Air Computation", Accepted at ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (ACM MobiHoc) (MobiHoc Best Paper Award Runner-up), October 2023.

Yongsheng Mei, Tian Lan, Mahdi Imani, and Suresh Subramaniam.. "A Bayesian Optimization Framework for Finding Local Optima in Expensive Multimodal Functions", Accepted at European Conference on Artificial Intelligence (ECAI), October 2023.

Jiayu Chen, Jingdi Chen, Tian Lan, and Vaneet Aggarwal, "Learning Multi-Agent Options for Tabular Reinforcement Learning using Factor Graphs", IEEE Transactions on Artificial Intelligence (TAI), vol. 4, no. 5, pp. 1141 - 1153, October 2023.

Chenyi Liu, Vaneet Aggarwal, Tian Lan, Nan Geng, Yuan Yang, and Mingwei Xu. "Machine Learning for Robust Network Design: A New Perspective", IEEE Communications Magazine, vol. 61, no. 10, pp. 86-92, October 2023.

Yuzhu Mao, Zihao Zhao, Meilin Yang, Le Liang, Yang Liu, Wenbo Ding, Tian Lan, Xiao-Ping Zhang. "SAFARI: Sparsity-Enabled Federated Learning with Limited and Unreliable Communications", Accepted at IEEE Transactions on Mobile Computing (TMC), 2023.

Yangyang Wang, Xiao Zhang, Mingyi Li, Tian Lan, Huashan Chen, Hui Xiong, Xiuzhen Cheng, and Dongxiao Yu. "Theoretical Convergence Guaranteed Resource-Adaptive Federated Learning with Mixed Heterogeneity.", In proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), August 2023.

Hanhan Zhou, Vaneet Aggarwal, and Tian Lan. "Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients", IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), vol. 7, no. 5, pp. 1351-1361, July 2023.

Jiayu Chen, Dipesh Tamboli, Tian Lan, Vaneet Aggarwal. "Multi-task Hierarchical Adversarial Inverse Reinforcement Learning", In proceedings of the International Conference on Machine Learning (ICML), July 2023.

Yongsheng Mei, Guru Venkataramani, and Tian Lan. "Exploiting Partial Common Information Microstructure for Multi-Modal Brain Tumor Segmentation", In proceedings of ICML Workshop on Machine Learning for Multimodal Healthcare Data (ICML-ML4MHD), July 2023.

Kailash Gogineni, Yongsheng Mei, Peng Wei, Tian Lan, and Guru Venkataramani. "FP-AccMER: Accelerating Multi-agent Experience Replay with Cache Locality-aware Prioritization", In proceedings of the IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP), July 2023.

Kailash Gogineni, Peng Wei, Tian Lan, and Guru Venkataramani. "Towards Efficient Multi-Agent Learning Systems", In proceedings of the ISCA Workshop on Architecture and System Support for Transformer Models (ASSYST), June 2023.

Jingdi Chen, Lei Zhang, Joseph Riem, Gina Adam, Nathaniel D. Bastian, and Tian Lan. "Explainable Learning-Based Intrusion Detection Supported by Memristors", In proceedings of the IEEE Conference on Artificial Intelligence, Poster, June 2023.

Jiayu Chen, Tian Lan, and Vaneet Aggarwal. "Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Control", In proceedings of the International Conference on Robotics and Automation (ICRA), May 2023.

Yongsheng Mei, Hanhan Zhou, Tian Lan, Guru Venkataramani, and Peng Wei. "MAC-PO: Multi-Agent Experience Replay via Collective Priority Optimization", In proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2023.

Kailash Gogineni, Peng Wei, Tian Lan, and Guru Venkataramani. "Scalability Bottlenecks in Multi-Agent Reinforcement Learning Systems", In proceedings of the International Workshop on Performance Analysis of Machine Learning Systems (FastPath), April 2023.

Chenyi Liu, Nan Geng, Vaneet Aggarwal, Tian Lan, Yuan Yang, and Mingwei Xu. "A Reinforcement Learning Framework for Vehicular Network Routing Under Peak and Average Constraints", IEEE Transactions on Vehicular Technology (TVT), vol. 72, no. 5, pp. 6753-6764, January 2023.

Sultan Alamro, Suresh Subramaniam, and Tian Lan. "Forseti: Dynamic Chunk-level Reshaping for Data Processing on Heterogeneous Clusters", Journal of Parallel and Distributed Computing (JPDC), vol. 171, pp. 14-23, January 2023.

Hanhan Zhou, Tian Lan, and Vaneet Aggarwal. "PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement Learning", In proceedings of the Conference on Neural Information Processing Systems (NeurIPS), December 2022.

Jiayu Chen, Jingdi Chen, Vaneet Aggarwal, and Tian Lan. "Multi-agent Covering Option Discovery based on Kronecker Product of Factor Graphs", In proceedings of the Conference on Neural Information Processing Systems (NeurIPS), December 2022.

Hanhan Zhou, Tian Lan, Guru Prasadh Venkataramani, and Wenbo Ding. "Federated Learning with Online Adaptive Heterogeneous Local Models", FL-NeurIPS 2022 (Oral Presentation), December 2022.

Shijing Li and Tian Lan, "From Network Inference Errors to Utility Suboptimality: How Much Is the Impact?", IEEE Transactions on Network and Service Management (TNSM), vol. 9, no. 6, pp. 4075-4086, November 2022.

Kailash Gogineni, Yongsheng Mei, Guru Venkataramani, and Tian Lan, "Verify-Pro: A Framework for Server Authentication Using Communication Protocol Dialects", In proceedings of the IEEE Military Communications Conference (MILCOM), November 2022.

GuangFeng Yan, Linqi Song, Shaolun Huang, and Tian Lan, "AC-SGD: Adaptively Compressed SGD for Communication-Efficient Distributed Learning", IEEE Journal on Selected Areas in Communications (JSAC), Series on Machine Learning in Communications and Networks, vol. 40, no. 9, pp. 2678-2693, September 2022.

Yuzhu Mao, Zihao Zhao, Guangfeng Yan, Yang Liu, Tian Lan, Linqi Song, and Wenbo Ding, "Communication Efficient Federated Learning with Adaptive Quantization", ACM Transactions on Intelligent Systems and Technology (TIST), vol. 13, no. 4, pp. 1-26, August 2022.

Jian Xu, Shao-Lun Huang, Linqi Song, and Tian Lan, "Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering", In proceedings of the International Conference on Distributed Computing Systems (ICDCS), July 2022.

Shijing Li, Tian Lan, Bharath Balasubramanian, Moo-Ryong Ra, Hee-won Lee, and Rajesh Panta, "Pushing Collaborative Data Deduplication to the Network Edge: An Optimization Framework and System Design", IEEE Transactions on Network Science and Engineering (TNSE), vol. 9, no. 4, pp. 2110-2122, July 2022.

Yimeng Wang, Mridul Agarwal, Tian Lan, and Vaneet Aggarwal, "Learning-based Online QoE Optimization in Multi-Agent Video Streaming", Algorithms, Special Issue on Deep Learning for Internet of Things, vol. 15, no. 7, pp. 227-239, June 2022.

Mridul Agarwal, Vaneet Aggarwal and Tian Lan, "Multi-Objective Reinforcement Learning with Non-Linear Scalarization", In proceedings of the In proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2022.

Jiayu Chen, Jingdi Chen, Tian Lan, and Vaneet Aggarwal, "Multi-agent Covering Option Discovery through Kronecker Product of Factor Graphs", In proceedings of the In proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2022.

Yifei Zou, Zongjing Jin, Dongxiao Yu and Tian Lan, "An Optimized Contention Resolution on Wireless Channel via Reinforcement Learning", In proceedings of the Fifth Annual Conference on Machine Learning and Optimization (MLO), April 2022.

Yurong Chen, Yongsheng Mei, Tian Lan, and Guru Venkataramani, "Exploring Effective Fuzzing Strategies to Analyze Communication Protocols", ACM Digital Threats: Research and Practice (DTRAP), March 2022.

Han Zhang, Xingang Shi, Xia Yin, Jilong Wang, Zhiliang Wang, Yingya Guo, and Tian Lan, "Boosting Bandwidth Availability Over Inter-DCWAN", In proceedings of the 17th International Conference on emerging Networking EXperiments and Technologies (CoNext), December 2021.

Vaneet Aggarwal and Tian Lan, "Preemptive Scheduling on Unrelated Machines with Fractional Precedence Constraints", Journal of Parallel and Distributed Computing (JPDC), vol. 157, pp. 280-286, November 2021.

Abubakr Al-Abbasi, Vaneet Aggarwal, Tian Lan, Yu Xiang, Moo-Ryong Ra, Yih-Farn Chen, "FastTrack: Minimizing Stalls for CDN-based Over-the-top Video Streaming Systems", IEEE Transactions on Cloud Computing (TCC), vol. 9, pp. 1453-1466, October 2021.

Guangfeng Yan, Linqi Song, Shaolun Huang, and Tian Lan, "DQ-SGD: Dynamic Quantization in SGD for Communication-Efficient Distributed Learning", In proceedings of IEEE Mobile Adhoc and Sensor Systems (MASS), October 2021.

Vaneet Aggarwal, Tian Lan, and Parimal Parag, "Modeling and Optimization of Latency in Erasure-coded Storage Systems", Tutorial at the IEEE Information Theory Workshop (ITW), October 2021.

Chenyi Liu, Nan Geng, Vaneet Aggarwal, Tian Lan, Yuan Yang, and Mingwei Xu, "CMIX: Deep Multi-agent Reinforcement Learning with Peak and Average Constraints", In proceedings of the The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), September 2021.

Yongsheng Mei, Tian Lan, and Guru Venkataramani, "MPD: Moving Target Defense through Communication Protocol Dialects", In proceedings of the International Conference on Security and Privacy in Communication Networks (SecureComm), September 2021.

Vaneet Aggarwal, Tian Lan, Suresh Subramaniam, and Maotong Xu, "On the Approximability of Related Machine Scheduling under Arbitrary Precedence", IEEE Transactions on Network and Service Management (TNSM), vol. 18, no. 3, pp. 3706–3718, September 2021.

Jiayu Chen, Marina Wagdy Wadea Haliem, Tian Lan, and Vaneet Aggarwal, "Multi-agent Deep Covering Option Discovery", In proceedings of the Reinforcement Learning for Real Life Workshop at ICML, July 2021.

Jiayu Chen, Vaneet Aggarwal, and Tian Lan, "DeepFreight: A Model-free Deep-reinforcement-learning-based Algorithm for Multi-transfer Freight Delivery", In proceedings of International Conference on Automated Planning and Scheduling (ICAPS), July 2021.

Vaneet Aggarwal and Tian Lan, "Modeling and Optimization of Latency in Erasure-coded Storage Systems", Monograph in Foundations and Trends in Communication and Information Theory, Now Publishers Inc, June 2021.

Jian Xu, Linqi Song, Shaolun Huang, and Tian Lan, "Live Gradient Compensation for Evading Stragglers in Distributed Learning", In Proceedings of INFOCOM, May 2021.

Jingdi Chen, Yimeng Wang, and Tian Lan, "Bringing Fairness to Actor-Critic Reinforcement Learning for Network Utility Optimization ", In Proceedings of INFOCOM, May 2021.

Peng Zou, XianglinWei, Omur Ozel, Tian Lan, and Suresh Subramaniam, "Timely Probabilistic Data Preprocessing in Mobile Edge Computing ", In Proceedings of WCNC, April 2021.

Yurong Chen, Tian Lan, and Guru Venkataramani, "Communication Protocol Customization and Fuzzing", Tutorial at the TPCP Software Security Summer School (SSSS), 2020.

Hanhan Zhou, Tian Lan and Guru Venkataramani, "Hunting Garbage Collection Related Concurrency Bugs Through Critical Condition Restoration", In Proceedings of CCS FEAST Workshop, November 2020.

Yu Xiang, Hang Liu, Tian Lan, Howie Huang, and Suresh Subramania, "Optimizing Job Reliability via Contention-Free, Distributed Scheduling of VM Checkpointing", IEEE Transactions on Network and Service Management (TNSM), vo. 18, no. 2, October 2020.

Nan Geng, Tian Lan, Vaneet Aggarwal, Yuan Yang, and Mingwei Xu, "A Multi-agent Reinforcement Learning Perspective on Distributed Traffic Engineering", IEEE International Conference on Network Protocols (ICNP), October 2020.

Sultan Alamro, Maotong Xu, Tian Lan, and Suresh Subramaniam, "Shed+: Optimal Dynamic Speculation to Meet Application Deadlines in Cloud", IEEE Transactions on Network and Service Management (TNSM), vol. 17, no. 3, September 2020.

Hongfa Xue, Tian Lan and Guru Venkataramani, "Integrated Reasoning Engine for Pointer-related Code Clone Detection", arXiv, July 2020.

Shijing Li and Tian Lan, "HotDedup: Managing Hot Data Storage at Network Edge through Optimal Distributed Deduplication", in Proceedings of IEEE/ACM INFOCOM, April 2020.

Yurong Chen, Hongfa Xue, Tian Lan and Guru Venkataramani, "CHOP: Dynamic Bound Check Elimination Through Convex Hull OPtimization", Computers & Security Journal, vo. 90, March 2020.

Hongfa Xue, Yongsheng Mei, Kailash Gogineni, Guru Venkataramani and Tian Lan, "Twin-Finder: Integrated Reasoning Engine for Pointer-related Code Clone Detection", in Proceedings of International Workshop on Software Clones (IWSC), February 2020.

Yimeng Wang, Tian Lan, and Vaneet Aggarwal, "DeepChunk: Deep Q-Learning for Chunk-based Caching in Data Processing Networks", IEEE Transactions on Cognitive Communications and Networking (TCCN), vo. 5, no. 4, pp. 1034-1045, December 2019.

Abubakr Al-Abbasi, Vaneet Aggarwal, Jiangxian Wu, and Tian Lan, "TTLoC: Taming Tail Latency for Erasure-coded Cloud Storage Systems", IEEE Transactions on Network and Service Management (TNSM), vo. 16, no. 4, pp. 1609-1623, December 2019.

Yurong Chen, Tian Lan and Guru Venkataramani, "Exploring Effective Fuzzing Strategies to Analyze Communication Protocols", in proceedings of CCS FEAST Workshop, November 2019.

Yurong Chen, Tian Lan and Guru Venkataramani, "CustomPro: Network Protocol Customization through Cross-host Feature Analysis", In proceedings of SecureComm (SecureComm Best Paper Award), October 2019.

Hongfa Xue, Yurong Chen, Guru Venkataramani and Tian Lan, "Hecate: Automated Customization of Program and Communication Features to Reduce Attack Surfaces", In proceedings of SecureComm, October 2019.

YimengWang, Nakjung Choi, and Tian Lan, "A Reinforcement Learning Approach for Online Service Tree Placement in Edge Computing", in proceedings of IEEE ICNP, Workshop on Harnessing the Data Revolution in Networking, October 2019.

Yongbo Li, Yimeng Wang, and Tian Lan, "TailAccountant: Tail Energy Accounting for Mobile Ad Prefetching and Energy Optimization", IEEE Transactions on Mobile Computing (TMC), vol. 18, no. 9, pp. 2117-2128, September 2019.

Yimeng Wang, Yongbo Li, Tian Lan, and Vaneet Aggarwal, "DeepChunk: Deep Q-Learning for Chunk-based Caching in Data Processing Networks", in proceedings of Annual Allerton Conference on Communication, Control, and Computing (Allerton), September 2019.

Jianhua Fan, Xiangli Wei, Tongxiang Wang, Tian Lan, and Suresh Subramaniam, "Churn-resilient Task Scheduling in a Tiered IoT Infrastructure", China Communications, vol. 16, no. 8, pp. 162-175, August 2019.

Shijing Li, Tian Lan, Bharath Balasubramanian, Moo-Ryong Ra, Hee-won Lee, and Rajesh Panta, "EF-dedup: Enabling Collaborative Data Deduplication at the Network Edge", In proceedings of IEEE ICDCS, July 2019.

Hongfa Xue, Shaowen Sun, Tian Lan, and Guru Venkataramani, "Machine-Learning-based Analysis of Program Binaries: A Comprehensive Study", IEEE Access, vo. 7, pp. 65889 - 65912, May 2019.

Tian Lan "Encyclopedia of Wireless Networks - Fairness", book chapter, Springer, May 2019.

Hongfa Xue, Yurong Chen, Guru Venkataramani, and Tian Lan, "AMASS: Automated Software Mass Customization via Feature Identification and Tailoring", EAI Transactions on Security and Safety, vo. 6, no. 20, pp. 1-14, April 2019.

Yang Zhang, Arnob Ghosh, Vaneet Aggarwal, and Tian Lan, "Tiered Cloud Storage via Two-Stage, Latency-aware Bidding", IEEE Transactions on Network and Service Management (TNSM), vo. 16, no. 1, pp. 176-191, January 2019.

Shijing Li, Tian Lan, Moo-Ryong Ra, and Rajesh Panta, "Joint Scheduling and Source Selection for Background Traffic in Erasure-Coded Storage", IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 29, no. 12, pp. 2826-2837, December 2018.

Yongbo Li and Tian Lan, "Multichoice Games for Optimizing Task Assignment in Edge Computing", In proceedings of IEEE Globecom, December 2018.

Hongfa Xue, Yurong Chen, Guru Venkataramani, Tian Lan, Guang Jin, and Jason Li, "MORPH: Enhancing System Security through Interactive Customization of Application and Communication Protocol Features", In proceedings of CCS, Poster, October 2018.

Yurong Chen, Shaowen Sun, Tian Lan, and Guru Venkataramani, "TOSS: Tailoring Online Server Systems through Binary Feature Customization", In proceedings of CCS FEAST Workshop, October 2018.

Hongfa Xue, Guru Venkataramani, and Tian Lan, "Clone-Slicer: Detecting Domain Specific Binary Code Clones through Program Slicing", In proceedings of CCS FEAST Workshop, October 2018.

Maotong Xu, Sultan Alamro, Tian Lan, and Suresh Subramaniam, "Chronos: A Unifying Optimization Framework for Speculative Execution of Deadline-critical MapReduce Jobs", In proceedings of IEEE ICDCS, July 2018.

Hongfa Xue, Guru Venkataramani, Tian Lan, "Clone-Hunter: Accelerated Bound Checks Elimination via Binary Code Clone Detection", In proceedings of ACM SIGPLAN Workshop on Machine Learning and Programming Languages (MAPL), June 2018.

Sultan Alamro, Maotong Xu, Tian Lan, and Suresh Subramaniam, "Shed: Optimal Dynamic Cloning to Meet Application Deadlines in Cloud", In proceedings of IEEE ICC, May 2018.

Vaneet Aggarwal, Yu Xiang, Tian Lan, and Yih-Farn Robin Chen, "Sprout: A Functional Caching Approach to Minimize Service Latency in Erasure-coded Storage", IEEE Transactions on Networking (ToN), vol. 25, no. 6, pp. 3683-3694, December 2017.

Maotong Xu, Sultan Alamro, Tian Lan, and Suresh Subramaniam, "CRED: Cloud Right-sizing to Meet Execution Deadlines and Data Locality", IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 28, no. 12, pp. 3389-3400, December 2017.

Jianhua Fan, Xiangli Wei, Tongxiang Wang, Tian Lan, and Suresh Subramaniam, "Deadline-Aware Task Scheduling in a Tiered IoT Infrastructure", In proceedings of IEEE GlobeCom, December 2017.

Yurong Chen, Tian Lan, and Guru Venkataramani, "DAMGate: Dynamic Adaptive Multi-feature Gating in Program Binaries", In proceedings of CCS FEAST Workshop, October 2017.

Yimeng Wang, Yongbo Li, and Tian Lan, "Capitalizing on the Promise of Ad Prefetching in Real-World Mobile Systems", In proceedings of IEEE Mobile Adhoc and Sensor Systems (MASS), October 2017.

Maotong Xu, Sultan Alamro, Tian Lan, and Suresh Subramaniam, "LASER: A Deep Learning Approach for Speculative Execution and Replication of Deadline-Critical Jobs in Cloud", In proceedings of ICCCN (invited paper), July 2017.

Maotong Xu, Sultan Alamro, Tian Lan, and Suresh Subramaniam, "Optimizing Speculative Execution of Deadline-Sensitive Jobs in Cloud", In Proceedings of ACM Sigmetrics, Poster, June 2017.

Fan Yao, Yongbo Li, Hongfa Xue, Yurong Chen, Tian Lan and Guru Venkataramani, "StatSym: Vulnerable Path Discovery through Statistics-guided Symbolic Execution", In Proceedings of IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), June 2017.

Yongbo Li, Yurong Chen, Tian Lan, and Guru Venkataramani, "MobiQoR: Pushing the Envelope of Mobile Edge Computing via Quality-of-Result Optimization", In Proceedings of ICDCS, June 2017.

Shijing Li, Tian Lan, Moo-Ryong Ra, and Rajesh Panta, "S3: Joint Scheduling and Source Selection for Background Traffic in Erasure-Coded Storage", In Proceedings of IEEE ICDCS, June 2017.

Vaneet Aggarwal and Tian Lan, "Tail Index for a Distributed Storage System with Pareto File Size Distribution", Technical report available at https://arxiv.org/abs/1607.06044, May 2017.

Hongfa Xue, Yurong Chen, Fan Yao, Yongbo Li, Tian Lan and Guru Venkataramani, "SIMBER: Eliminating Redundant Memory Bound Checks via Statistical Inference", In Proceedings of IFIP SEC, May 2017.

Vaneet Aggarwal, JiangxianWu, and Tian Lan, "Taming Tail Latency for Erasure-coded, Distributed Storage Systems", In Proceedings of INFOCOM, May 2017.

Yu Xiang, Juzi Zhao, Tian Lan, Howie Huang, and Suresh Subramania, "Elastic Reliability Optimization Through Peer-to-Peer Checkpointing in Cloud Computing", IEEE Transactions on Parallel and Distributed Systems (TPDS), vol 28, no. 2, February 2017.

Yu Xiang, Tian Lan, Vaneet Aggarwal, and Yih-Farn Robin Chen, "Optimizing Differentiated Latency in Multi-Tenant, Erasure-Coded Storage", IEEE Transactions on Network and Service Management (TNSM), Vol. 14, No. 1, pp. 204-216, January 2017.

Yu Xiang, Vaneet Aggarwal, Tian Lan, and Yih-Farn Robin Chen, "Differentiated latency in data center networks with erasure coded files through traffic engineering", IEEE Transactions on Cloud Computing (TCC), vol. 1, no. 99, January 2017.

Yongbo Li, Fan Yao, Tian Lan, and Guru Venkataramani, "SARRE: Semantics-Aware Rule Recommendation and Enforcement for Event Paths on Android", IEEE Transactions on Information Forensics and Security (TIFS), vol. 11, no. 12, pp. 2748-2762, December 2016.

Sultan Alamro, Maotong Xu, Tian Lan, and Suresh Subramaniam, "CRED: Cloud Right-sizing to Meet Execution Deadlines and Data Locality", In Proceedings of IEEE CLOUD, July 2016.

Yu Xiang, Tian Lan, Vaneet Aggarwal, and Yih-Farn Robin Chen, "Joint Latency and Cost Optimization for Erasure-coded Data Center Storage", IEEE Transactions on Networking (ToN), vol. 24, no. 4, pp. 2443-2457, June 2016.

Vaneet Aggarwal, Yu Xiang, Tian Lan, and Yih-Farn Robin Chen, "Sprout: A Functional Caching Approach to Minimize Service Latency in Erasure-coded Storage", In Proceedings of IEEE ICDCS, Poster, May 2016.

Zhe Huang, Bharath Balasubramanian, Michael Wang, Tian Lan, Mung Chiang, and Danny H.K. Tsang, "RUSH: A RobUst ScHeduler to Manage Uncertain Completion-Times in Shared Clouds", In Proceedings of ICDCS, May 2016.

Shijing Li, Tian Lan, Moo-Ryong Ra, and Rajesh Panta, "Background Traffic Optimization for Meeting Deadlines in Data Center Storage", In Proceedings of CISS (Invited paper), March 2016.

Yongbo Li, Fan Yao, Tian Lan, and Guru Venkataramani, "Semantics-Aware Rule Recommendation and Enforcement for Event Paths on Android", In Proceedings of SecureComm, Poster, October 2015.

Yu Xiang, Tian Lan, Vaneet Aggarwal, and Yih-Farn Robin Chen, "Multi-Tenant Latency Optimization in Erasure-Coded Storage with Differentiated Services", In Proceedings of IEEE ICDCS, Poster, June 2015.

Yu Xiang, Tian Lan, Vaneet Aggarwal, and Yih-Farn Robin Chen, "Taming Network Latency in Erasure-Coded Datacenter Storage", In Proceedings of CCGrid, May 2015.

Zhe Huang, Bharath Balasubramanian, Michael Wang, Tian Lan, Mung Chiang, and Danny H.K. Tsang, "Need for Speed: CORA Scheduler for Optimizing Completion-Times in the Cloud", In Proceedings of IEEE INFOCOM, April 2015.

Yu Xiang, Tian Lan, Vaneet Aggarwal, and Yih-Farn Robin Chen, "Joint Latency and Cost Optimization for Erasure-coded Data Center Storage", In Proceedings of IFIP WG 7.3 Performance 2014 (ACM SIGMETRICS Performance Evaluation Review, vol. 42, no. 2, pp. 3-14), Sepetember 2014.

Yu Xiang and Tian Lan. "Datacenter Smart Pricing", Book chapter in "Smart Data Pricing", Wiley, September 2014.

Mian Dong, Tian Lan, and Lin Zhong. "Rethink Energy Accounting with Cooperative Game Theory", In Proceedings of ACM Mobicom, September 2014.

Yu Xiang, Hang Liu, Tian Lan, Howie Huang, Suresh Subramaniam, "Optimizing Job Reliability via Contention-Free, Distributed Checkpoint Scheduling". In Proceedings of ACM SIGCOMM Workshop on Distributed Cloud Computing (DCC), August 2014.

Bharath Balasubramanian, Tian Lan, and Mung Chiang, "SAP: Similarity-Aware Partitioning for Efficient Cloud Storage", In Proceedings of IEEE INFOCOM, April 2014.

Carlee Joe-Wong, Soumya Sen, Tian Lan, and Mung Chiang. "Multi-Resource Allocation: Fairness-Efficiency Tradeoffs in A Unifying Framework", IEEE Transactions on Networking (ToN), vol. 12, no. 6, pp. 1785-1798, December 2013.

Yu Xiang, Bharath Balasubramanian, Michael Wang, Tian Lan, Soumya Sen and Mang Chiang, "Self-adaptive, Deadline-aware Resource Control in Cloud Computing", In Proceedings of IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO), September 2013.

Mian Dong, Tian Lan, and Lin Zhong. "How does energy accounting matter for energy management?", In Proceedings of ACM Sigmetrics, Poster, June 2013.

Mian Dong, Tian Lan, and Lin Zhong. "System Energy Consumption is a Multi-player Game", Extended Abstract at International Conference on Computer-Aided Design, (ICCAD), November 2012.

Stuart Wagner, Eric van den Berg, Jim Giacopelli, Andrei Ghetie, Jim Burns, Miriam Tauil, Soumya Sen, Michael Wang, Mung Chiang, Tian Lan, Robert Laddaga, Paul Robertson, and Prakash Manghwani. "Autonomous, Collaborative Control for Resilient Cyber Defense (ACCORD)", In Proceedings of IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO), August 2012.

Nakharin Limrungsi, Juzi Zhao, Yu Xiang, Tian Lan, Howie Huang, and Suresh Subramania. "Provide Reliability as An Elastic Service in Cloud", In proceedings of ICC 2012, June 2012.

Wei Wang, Peng Zhang, Tian Lan, and Vaneet Aggarwal. "Datacenter Net Profit Optimization with Individual Job Deadlines", In proceedings of CISS 2012 (Invited paper), March 2012.

Carlee Joe-Wong, Soumya Sen, Tian Lan, and Mung Chiang. "Multi-Resource Allocation: Fairness-Efficiency Tradeoffs in A Unifying Framework", In proceedings of INFOCOM 2012 (INFOCOM 2012 Best Paper Award), March 2012.

Wenjie Jiang, Minghua Chen, Tian Lan, Sangtae Ha, and Mung Chiang. "Dynamic VM Placement and Routing in A Data Center Network", In proceedings of INFOCOM 2012, mini-conference, March 2012.

Tian Lan and Mung Chiang. "An Axiomatic Theory of Fairness for Resource Allocation", Preprint available online, December 2011.

Tian Lan and Mung Chiang. "Measuring Fairness: Theory and Applications", In proceedings of Allerton Conference on Communication, Control and Computing (Allerton), September 2011.

Tian Lan, Xiaojun Lin, and Mung Chiang. "Stability and Benefits of Suboptimal Utility Maximization", IEEE/ACM Transactions on Networking (TON), vol. 19, no. 4, pp. 1194-1207, August 2011.

Tian Lan, Ruby Lee, and Mung Chiang. "Key Management in Sensor Networks", Book Chapter in "Theoretical Aspects of Distributed Computing in Sensor Networks", Springer Verlag, January 2011.

Latha Kent, Kenneth kerpez, Kaustubh Sinkar, and Tian Lan. "Resource Allocation and Performance Study for A LTE Network Integrated with Femtocells", In proceedings of IEEE GLOBECOM, December 2010.

Tian Lan, David Kao, Mung Chiang, and Ashutosh Sabharwal. "An Axiomatic Theory of Fairness for Resource Allocation", In proceedings of IEEE INFOCOM, March 2010.

Alexandre Proutiere, Yung Yi, Tian Lan, and Mung Chiang. "Resource Allocation Over Network Dynamics: Stochastic Approximation Without Timescale Separation", In proceedings of IEEE INFOCOM, mini-conference, March 2010.

Tian Lan, Ruby Lee, and Mung Chiang. "Reliable and Secure Distributed Storage Without Cryptography", Preprint available online, January 2010.

Tian Lan, Ruby Lee, and Mung Chiang. "Multi-path Key EstablishmentAgainst REM Attacks inWireless Ad Hoc Networks", In proceedings of IEEE GLOBECOM (GLOBECOM 2009 Best Paper Award), December 2009.

Kenneth kerpez, Tian Lan, Kaustubh Sinkar, and Latha Kent. "System and Method for Resource Allocation of A LTE Network Integrated with Femtocells", Patent US20110183678, December 2009.

Mung Chiang, Prashanth Hande, Tian Lan, and Chee Wei Tan. "Power Control in Cellular Networks", Monograph, Foundations and Trends in Networking, vol. 2, no. 4, Now Publishers Inc, 2008.

Tian Lan, Xiaojun Lin, Mung Chiang, and Ruby Lee. "How Bad Is Suboptimal Rate Allocation?" In proceedings of IEEE INFOCOM, April 2008.

Wei Yu and Tian Lan. "Transmitter Optimization for the Multi-Antenna Downlinkwith Per-Antenna Power Constraints", IEEE Transactions on Signal Processing (TSP), vol. 55, no. 6, part 1, pp. 2646-2660, (IEEE Signal Processing Society 2008 Best Paper Award), June 2007.

Tian Lan, Prashanth Hande and Mung Chiang. "Joint Beamforming and Power Control for Optimal SIR Distribution in Cellular Uplinks", In proceedings of IEEE ISIT, June 2006.

Wei Yu and Tian Lan. "Downlink Beamforming with Per-Antenna Power Constraints", In proceedings of IEEE SPAWC Workshop, June 2005.

Tian Lan and Wei Yu. "Input Optimization for Multi-Antenna Broadcast Channels with Per-Antenna Power Constraints", In proceedings of IEEE GLOBECOM, December 2004.

Wei Yu and Tian Lan. "Minimax Duality of Gaussian Vector Broadcast Channels", In proceedings of IEEE ISIT, June 2004.