Publications
Recent Publications
Faculty and students share their expertise and results of their research through publications. Citations for and links to recent publications by our faculty are listed below.
- Within the groupings by year, publications are organized alphabetically by faculty author.
- Publications preceded by a (*) include current or former student co-authors.
- Faculty names are bolded.
- The citations are in Chicago format as provided by Google Scholar.
Cui, Kangning, Rongkun Zhu, Manqi Wang, Wei Tang, Gregory D. Larsen, Victor P. Pauca, Sarra Alqahtani, Fan Yang et al. “Detection and Geographic Localization of Natural Objects in the Wild: A Case Study on Palms.” arXiv preprint arXiv:2502.13023 (2025).
Le, Tuan, Risal Shefin, Debashis Gupta, Thai Le, and Sarra Alqahtani. “Verification-Guided Falsification for Safe RL via Explainable Abstraction and Risk-Aware Exploration.” arXiv preprint arXiv:2506.03469 (2025). – Publication Link
Hayashi, Koby, Sinan G. Aksoy, Grey Ballard, and Haesun Park. “Randomized algorithms for symmetric nonnegative matrix factorization.” SIAM Journal on Matrix Analysis and Applications 46, no. 1 (2025): 584-625. – Publication Link
Chen, Chen, Enze Xu, Defu Yang, Chenggang Yan, Tao Wei, Hanning Chen, Yong Wei, and Minghan Chen. “Chemical environment adaptive learning for optical band gap prediction of doped graphitic carbon nitride nanosheets.” Neural Computing and Applications 37, no. 5 (2025): 3287-3301. – Publication Link
Rao, Heng, Yu Gu, Jason Zipeng Zhang, Ge Yu, Yang Cao, and Minghan Chen. “Hierarchical Gradient-Based Genetic Sampling for Accurate Prediction of Biological Oscillations.” In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 39, no. 25, pp. 27126-27134. 2025. – Publication Link
Xu, Chunrui, Enze Xu, Yang Xiao, Defu Yang, Guorong Wu, and Minghan Chen. “A multiscale model to explain the spatiotemporal progression of amyloid beta and tau pathology in Alzheimer’s disease.” International Journal of Biological Macromolecules 310 (2025): 142887. – Publication Link
Devarakonda, Aditya, and Ramakrishnan Kannan. “Communication-Efficient, 2D Parallel Stochastic Gradient Descent for Distributed-Memory Optimization.” arXiv preprint arXiv:2501.07526 (2025). – Publication Link
Shao, Zishan, and Aditya Devarakonda. “Scalable dual coordinate descent for kernel methods.” In Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, pp. 52-63. 2025. – Publication Link
Li, Zihao, Yucheng Shi, Zirui Liu, Fan Yang, Ali Payani, Ninghao Liu, and Mengnan Du. “Language ranker: A metric for quantifying llm performance across high and low-resource languages.” In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 39, no. 27, pp. 28186-28194. 2025. – Publication Link
He, Zirui, Haiyan Zhao, Yiran Qiao, Fan Yang, Ali Payani, Jing Ma, and Mengnan Du. “Saif: A sparse autoencoder framework for interpreting and steering instruction following of language models.” arXiv preprint arXiv:2502.11356 (2025). – Publication Link
Zhao, Haiyan, Xuansheng Wu, Fan Yang, Bo Shen, Ninghao Liu, and Mengnan Du. “Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering.” arXiv preprint arXiv:2505.15038 (2025). – Publication Link
Shefin, Risal Shahriar, Md Asifur Rahman, Thai Le, and Sarra Alqahtani. “xSRL: Safety-Aware Explainable Reinforcement Learning–Safety as a Product of Explainability.” arXiv preprint arXiv:2412.19311 (2024). – Publication Link
(*) Cui, Kangning, Zishan Shao, Gregory Larsen, Victor Pauca, Sarra Alqahtani, David Segurado, João Pinheiro et al. “PalmProbNet: A Probabilistic Approach to Understanding Palm Distributions in Ecuadorian Tropical Forest via Transfer Learning.” In Proceedings of the 2024 ACM Southeast Conference, pp. 272-277. 2024. — Publication Link
Gupta, Debashis, Aditi Golder, Luis Fernendez, Miles Silman, Greg Lersen, Fan Yang, Bob Plemmons, Sarra Alqahtani, and Paul Victor Pauca. “ASGM-KG: Unveiling Alluvial Gold Mining Through Knowledge Graphs.” arXiv preprint arXiv:2408.08972 (2024). — Publication Link
Cui, Kangning, Wei Tang, Rongkun Zhu, Manqi Wang, Gregory D. Larsen, Victor P. Pauca, Sarra Alqahtani, Fan Yang et al. “Real-time localization and bimodal point pattern analysis of palms using uav imagery.” arXiv preprint arXiv:2410.11124 (2024). – Publication Link
Daas, Hussam Al, Grey Ballard, Laura Grigori, Suraj Kumar, Kathryn Rouse, and Mathieu Verite. “Communication Lower Bounds and Optimal Algorithms for Symmetric Matrix Computations.” arXiv preprint arXiv:2409.11304 (2024). — Publication Link
(*) Al Daas, Hussam, Grey Ballard, Laura Grigori, Suraj Kumar, and Kathryn Rouse. “Communication Lower Bounds and Optimal Algorithms for Multiple Tensor-Times-Matrix Computation.” SIAM Journal on Matrix Analysis and Applications 45, no. 1 (2024): 450-477. — Publication Link
(*) Minster, Rachel, Zitong Li, and Grey Ballard. “Parallel randomized Tucker decomposition algorithms.” SIAM Journal on Scientific Computing 46, no. 2 (2024): A1186-A1213. — Publication Link
(*) Wiley, Cade, and Grey Ballard. “Visualizing PRAM Algorithm for Mergesort.” In Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, 2024. — Publication Link Not Yet Available
Devarakonda, Aditya, and Grey Ballard. “Sequential and Shared-Memory Parallel Algorithms for Partitioned Local Depths.” In Proceedings of the 2024 SIAM Conference on Parallel Processing for Scientific Computing (PP), pp. 53-64. Society for Industrial and Applied Mathematics, 2024. – Publication Link
Eswar, Srinivas, Koby Hayashi, Benjamin Cobb, Ramakrishnan Kannan, Grey Ballard, Richard Vuduc, and Haesun Park. “On Rank Selection for Nonnegative Matrix Factorization.” In 2024 IEEE International Conference on Big Data (BigData), pp. 1294-1301. IEEE, 2024. – Publication Link
Zhu, Wentao, Zhiqiang Du, Ziang Xu, Defu Yang, Minghan Chen, and Qianqian Song. “SCRN: Single-cell Gene Regulatory Network Identification in Alzheimer’s Disease.” IEEE/ACM Transactions on Computational Biology and Bioinformatics (2024). — Publication Link
Rao, Heng, Yu Gu, Jason Zipeng Zhang, Ge Yu, Yang Cao, and Minghan Chen. “Hierarchical Gradient-Based Genetic Sampling for Accurate Prediction of Biological Oscillations.” arXiv preprint arXiv:2409.12816 (2024). — Publication Link
Liu, Haoran, Bahjat Fadi Marayati, David de la Cerda, Brendan Matthew Lemezis, Jieyu Gao, Qianqian Song, Minghan Chen, and Ke Zhang Reid. “The Cross-Regulation Between Set1, Clr4, and Lsd1/2 in Schizosaccharomyces pombe.” Plos Genetics 20, no. 1 (2024): e1011107. — Publication Link
(*) Xu, Enze, Jingwen Zhang, Jiadi Li, Qianqian Song, Defu Yang, Guorong Wu, and Minghan Chen. “Pathology steered stratification network for subtype identification in Alzheimer’s disease.” Medical Physics (2024). — Publication Link
Yang, Defu, Jiaqi Zhao, Minghan Chen, Yitian Xue, Jingwen Zhou, Shuai Wang, Guorong Wu, and Wentao Zhu, “Learning Functional Dynamics From A Multilayer Brain Network,” In Proceedings of 21st IEEE International Symposium on Biomedical Imaging (ISBI), Athens, Greece, 2024, pp. 1–4. — Publication Link Not Yet Available
(*) Su, Jiayang, Junbo Ma, Songyang Tong, Enze Xu, and Minghan Chen. “Multiscale Attention Wavelet Neural Operator for Capturing Steep Trajectories in Biochemical Systems.” In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, no. 13, pp. 15100-15107. 2024. — Publication Link
Yang, Defu, Hui Shen, Minghan Chen, Shuai Wang, Jiazhou Chen, Hongmin Cai, Xueli Chen, Guorong Wu, and Wentao Zhu. “A Novel Spatio-temporal Hub Identification in Brain Networks by Learning Dynamic Graph Embedding on Grassmannian Manifolds.” IEEE Transactions on Medical Imaging (2024). – Publication Link
Kuczynski, Caroline E., Christopher D. Porada, Anthony Atala, Samuel S. Cho, and Graça Almeida-Porada. “Evaluating sheep hemoglobins with MD simulations as an animal model for sickle cell disease.” Scientific Reports 14, no. 1 (2024): 276. — Publication Link
Hayman, Daniel, Errin W. Fulp, Daniel Rogers, and David K. Ahn. “Intelligence Driven Threat Actor Analysis: BlackBasta and Affiliates.” In 2024 Cyber Research Conference-Ireland (Cyber-RCI), pp. 1-4. IEEE, 2024. – Publication Link
Cheng, Zijun, Qiujian Lv, Jinyuan Liang, Yan Wang, Degang Sun, Thomas Pasquier, and Xueyuan Han. “Kairos:: Practical Intrusion Detection and Investigation using Whole-system Provenance.” In Proceedings of 2024 IEEE Symposium on Security and Privacy (SP), 2024. — Publication Link
Cao, Xuechun, Shaurya Patel, Soo Yee Lim, Xueyuan Han, and Thomas Pasquier. “FetchBPF: Customizable Prefetching Policies in Linux with eBPF.” In Proceedings of Usenix Annual Technical Conference (ATC’24). — Publication Link (personal author site)
Lim, Soo Yee, Sidhartha Agrawal, Xueyuan Han, David Eyers, Dan O’Keeffe, and Thomas Pasquier. “Securing Monolithic Kernels using Compartmentalization.” arXiv preprint arXiv:2404.08716 (2024). — Publication Link (Preprint)
Short, Samantha M., Mildred D. Perez, Alexis E. Morse, Rebecca Damron Jennings, Dianna S. Howard, David Foureau, Aleksander Chojecki, Natalia Khuri et al. “High-dimensional Immune Profiles and Machine Learning May Predict Acute Myeloid Leukemia Relapse Early following Transplant.” The Journal of Immunology 213, no. 10 (2024): 1441-1451. – Publication Link
Zhao, Haiyan, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, and Mengnan Du. “Explainability for large language models: A survey.” ACM Transactions on Intelligent Systems and Technology 15, no. 2 (2024): 1-38. — Publication Link
Wang, Guanchu, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu et al. “TVE: Learning Meta-attribution for Transferable Vision Explainer.” Accepted for publication at ICML 2024. — Publication Link Not Yet Available
Chuang, Yu-Neng, Guanchu Wang, Chia-Yuan Chang, Ruixiang Tang, Fan Yang, Mengnan Du, Xuanting Cai, and Xia Hu. “Large Language Models As Faithful Explainers.” arXiv preprint arXiv:2402.04678 (2024). — Publication Link (Preprint)
Zhao, Haiyan, Fan Yang, Himabindu Lakkaraju, and Mengnan Du. “Opening the Black Box of Large Language Models: Two Views on Holistic Interpretability.” arXiv preprint arXiv:2402.10688 (2024). — Publication Link (Preprint)
Wu, Xuansheng, Haiyan Zhao, Yaochen Zhu, Yucheng Shi, Fan Yang, Tianming Liu, Xiaoming Zhai et al. “Usable XAI: 10 strategies towards exploiting explainability in the LLM era.” arXiv preprint arXiv:2403.08946 (2024). — Publication Link (Preprint)
Jin, Mingyu, Qinkai Yu, Jingyuan Huang, Qingcheng Zeng, Zhenting Wang, Wenyue Hua, Haiyan Zhao et al (including Fan Yang). “Exploring Concept Depth: How Large Language Models Acquire Knowledge at Different Layers?.” arXiv preprint arXiv:2404.07066 (2024). — Publication Link (Preprint)
Li, Zihao, Yucheng Shi, Zirui Liu, Fan Yang, Ninghao Liu, and Mengnan Du. “Quantifying Multilingual Performance of Large Language Models Across Languages.” arXiv preprint arXiv:2404.11553 (2024). — Publication Link (Preprint)
Chuang, Yu-Neng, Guanchu Wang, Chia-Yuan Chang, Ruixiang Tang, Shaochen Zhong, Fan Yang, Mengnan Du, Xuanting Cai, and Xia Hu. “FaithLM: Towards faithful explanations for large language models.” arXiv preprint arXiv:2402.04678 (2024). – Publication Link
Zhao, Haiyan, Fan Yang, Bo Shen, Himabindu Lakkaraju, and Mengnan Du. “Towards uncovering how large language model works: An explainability perspective.” arXiv preprint arXiv:2402.10688 (2024). – Publication Link
Zeng, Qingcheng, Mingyu Jin, Qinkai Yu, Zhenting Wang, Wenyue Hua, Zihao Zhou, Guangyan Sun, Fan Yang et al. “Uncertainty is fragile: Manipulating uncertainty in large language models.” arXiv preprint arXiv:2407.11282 (2024). – Publication Link
Zhou, Huachi, Shuang Zhou, Hao Chen, Ninghao Liu, Fan Yang, and Xiao Huang. “Enhancing explainable rating prediction through annotated macro concepts.” In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp. 11736-11748. 2024.
Chen, Yan, Zepang Sun, Junmei Yin, M. Usman Ahmad, Zixia Zhou, Wanying Feng, Fan Yang et al. “Digital assessment of tertiary lymphoid structures and therapeutic responses in gastric cancer: a multicentric retrospective study.” International Journal of Surgery 110, no. 10 (2024): 6732-6747. – Publication Link
Shi, Zeru, Zhenting Wang, Yongye Su, Weidi Luo, Hang Gao, Fan Yang, Ruixiang Tang, and Yongfeng Zhang. “Robustness-aware Automatic Prompt Optimization.” arXiv preprint arXiv:2412.18196 (2024). – Publication Link
Zhao, Haiyan, Heng Zhao, Bo Shen, Ali Payani, Fan Yang, and Mengnan Du. “Beyond single concept vector: Modeling concept subspace in llms with gaussian distribution.” arXiv preprint arXiv:2410.00153 (2024). – Publication Link
Jin, Mingyu, Qinkai Yu, Jingyuan Huang, Qingcheng Zeng, Zhenting Wang, Wenyue Hua, Haiyan Zhao, Fan Yang et al. “Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?.” arXiv preprint arXiv:2404.07066 (2024). – Publication Link
Liu, Tongtong, Joe McCalmon, Thai Le, Dongwon Lee, and Sarra Alqahtani. “A Policy-Graph Approach to Explain Reinforcement Learning Agents: A Novel Policy-Graph Approach with Natural Language and Counterfactual Abstractions for Explaining Reinforcement Learning Agents.” (2023). — Publication Link
(*) McCalmon, Joe, Tongtong Liu, Reid Goldsmith, Andrew Cyhaniuk, Talal Halabi, and Sarra Alqahtani. “Safe Reinforcement Learning via Observation Shielding.” Proceedings of the Hawaii International Conference on System Sciences: HICSS2023 (2023). — Publication Link (Prepress)
(*) Liu, Tongtong, Joe McCalmon, Thai Le, Md Asifur Rahman, Dongwon Lee, and Sarra Alqahtani. “A Novel Policy-Graph Approach with Natural Language and Counterfactual Abstractions for Explaining Reinforcement Learning Agents.” Autonomous Agents and Multi-Agent Systems Volume 37, 34 (2023). — Publication Link
(*) Rahman, Md Asifur, Tongtong Liu, and Sarra Alqahtani. “Adversarial behavior exclusion for safe reinforcement learning.” In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, pp. 483-491. 2023. — Publication Link
Jahan, Sharmin, Sarra Alqahtani, Rose F. Gamble, and Masrufa Bayesh. “Automated Extraction of Security Profile Information from XAI Outcomes.” In 2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), pp. 110-115. IEEE, 2023. — Publication Link
Sarra Alqahtani and Talal Halabi. “Stealthy Attacks on Multi-Agent Reinforcement Learning in Mobile Cyber-Physical Systems.” In 2023 7th Cyber Security in Networking Conference (CSNet), pp. 171-177. IEEE, 2023. — Publication Link
(*) Rahman, Md Asifur, and Sarra Alqahtani. “Task-Agnostic Safety for Reinforcement Learning.” In Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, pp. 139-148. 2023. — Publication Link
Dethier, Evan, Miles Silman, Luis E. Fernandez, Jimena Díaz Leiva, Sarra Alqahtani, Paúl Pauca, Seda Camalan et al. “A global 21st century mining boom in tropical river systems: the driver of changes to forest health, riparian geomorphology, and suspended sediment transport.” AGU23 (2023).
Dethier, Evan, Miles Silman, Luis Fernandez, Jorge Caballero Espejo, Sarra Alqahtani, Paúl Pauca, and David Lutz. “Operation mercury: Impacts of national‐level armed forces intervention and anticorruption strategy on artisanal gold mining and water quality in the Peruvian Amazon.” Conservation Letters 16, no. 5 (2023): e12978. — Publication Link
Dethier, Evan N., Miles Silman, Jimena Díaz Leiva, Sarra Alqahtani, Luis E. Fernandez, Paúl Pauca, Seda Çamalan et al. “A global rise in alluvial mining increases sediment load in tropical rivers.” Nature 620, no. 7975 (2023): 787-793. — Publication Link
Al Daas, Hussam, Grey Ballard, Paul Cazeaux, Eric Hallman, Agnieszka Międlar, Mirjeta Pasha, Tim Reid, and Arvind Saibaba. “Randomized algorithms for rounding in the tensor-train format.” SIAM Journal on Scientific Computing 45, no. 1 (2023): A74-A95. — Publication Link
(*) Al Daas, Hussam, Grey Ballard, Laura Grigori, Suraj Kumar, and Kathryn Rouse. “Parallel Memory-Independent Communication Bounds for SYRK.” ACM Symposium on Parallelism in Algorithms and Architectures. 2023. — Publication Link (Prepress)
(*) Eswar, Srinivas, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Richard Vuduc, and Haesun Park. “Distributed-Memory Parallel JointNMF.” In Proceedings of the 37th International Conference on Supercomputing, pp. 301-312. 2023. — Publication Link
(*) Minster, Rachel, Irina Viviano, Xiaotian Liu, and Grey Ballard. “CP decomposition for tensors via alternating least squares with QR decomposition.” Numerical Linear Algebra with Applications 30, no. 6 (2023): e2511. — Publication Link
Devarakonda, Aditya, and Grey Ballard. “Sequential and Shared-Memory Parallel Algorithms for Partitioned Local Depths.” arXiv preprint arXiv:2307.16652 (2023). — Publication Link (Preprint)
(*) Aizpurua, Ariel, Errin Fulp, and Daniel Canas. “Using diversity to evolve more secure and efficient virtual local area networks”. Proceedings of the 2023 International Conference on Computing, Networking, and Communications (ICNC 2023). — Publication Link
Kodituwakku, Angel, Clark Xu, Daniel Rogers, David Ahn, and Errin Fulp. “Temporal Aspects of Cyber Threat Intelligence.” In 2023 IEEE International Conference on Big Data (BigData), pp. 6207-6211. IEEE, 2023. — Publication Link
Zhang, Jingwen, Qing Liu, Haorui Zhang, Michelle Dai, Qianqian Song, Defu Yang, Guorong Wu, and Minghan Chen. “Uncovering the System Vulnerability and Criticality of Human Brain Under Dynamical Neuropathological Events in Alzheimer’s Disease.” Journal of Alzheimer’s Disease 95, no. 3 (2023): 1201-1219. — Publication Link
Yang, Defu, Hui Shen, Minghan Chen, Yitian Xue, Shuai Wang, Guorong Wu, and Wentao Zhu. “Spatiotemporal Hub Identification in Brain Network by Learning Dynamic Graph Embedding on Grassmannian Manifold.” In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 394-402. Cham: Springer Nature Switzerland, 2023. — Publication Link
(*) Jadhav, Sneha, Jianxiang Zhao, Yepeng Fan, Jingjing Li, Hao Lin, Chenggang Yan, and Minghan Chen. “Time-Varying Sequence Model.” Mathematics 11, no. 2 (2023): 336. — Publication Link
(*) Rao, Fan, Minghan Chen, Defu Yang, Bess Morrell, Qianqian Song, and Wentao Zhu. “scENT for revealing gene clusters from single-cell RNA-seq data.” IEEE/ACM Transactions on Computational Biology and Bioinformatics (2023) — Publication Link
(*) Chen, Chen, Enze Xu, Defu Yang, Chenggang Yan, Tao Wei, Hanning Chen, Yong Wei, and Minghan Chen. “Chemical Environment Adaptive Learning for Optical Band Gap Prediction of Doped Graphitic Carbon Nitride Nanosheets.” arXiv preprint arXiv:2302.09539 (2023). — Publication Link
(*) Chu, Xieting, Hongjue Zhao, Enze Xu, Hairong Qi, Minghan Chen, and Huajie Shao. “Neural Symbolic Regression using Control Variables.” arXiv preprint arXiv:2306.04718 (2023). — Publication Link
Yang, Defu, Hui Shen, Minghan Chen, Yitian Xue, Shuai Wang, Guorong Wu, and Wentao Zhu. “Spatiotemporal Hub Identification in Brain Network by Learning Dynamic Graph Embedding on Grassmannian Manifold.” In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 394-402. Cham: Springer Nature Switzerland, 2023. — Publication Link
(*) Cho, Samuel, Adam Green, Changbong Hyeon, and Dave Thirumalai. “TMAO Destabilizes RNA Secondary Structure via Direct Hydrogen Bond Interactions.” The Journal of Physical Chemistry B (2023). — Publication Link
Narayan, Gyan, Luis A. Gracia Mazuca, Samuel S. Cho, Jonathon E. Mohl, and Eda Koculi. “RNA Post-transcriptional Modifications of an Early-Stage Large-Subunit Ribosomal Intermediate.” Biochemistry (2023). — Publication Link
Cochran, William B., and Kate Allman. “Cultivating Moral Agency in a Technology Ethics Course in advance.” Teaching Ethics (2023). — Publication Link
Goyal, Akul, Xueyuan Han, Gang Wang, and Adam Bates. “Sometimes, You Aren’t What You Do: Mimicry Attacks Against Provenance Graph Host Intrusion Detection Systems.” Proceedings of the 30th Network and Distributed System Security Symposium. 2023. — Publication Link
Lim, Soo Yee, Xueyuan Han, and Thomas Pasquier. “Unleashing Unprivileged eBFP Potential With Dynamic Sandboxing.” In Proceedings of the 1st Workshop on eBPF and Kernel Extensions, pp. 42-48. 2023. — Publication Link
Han, Xueyuan, James Mickens, and Siddhartha Sen. “Splice: Efficiently Removing A User’s Data From In-memory Application State.” In Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, pp. 2989-3002. 2023. — Publication Link
Cheng, Zijun, Qiujian Lv, Jinyuan Liang, Yan Wang, Degang Sun, Thomas Pasquier, and Xueyuan Han. “Kairos:: Practical Intrusion Detection and Investigation using Whole-system Provenance.” arXiv preprint arXiv:2308.05034 (2023). — Publication Link
(*) Zhao, Konghao, Jason Grayson, and Natalia Khuri. “Multi-Objective Genetic Algorithm for Cluster Analysis of Single-Cell Transcriptomes.” Journal of Personalized Medicine 13, no. 2 (2023): 183. — Publication Link
(*) Zhao, Konghao, Sapan Bhandari, Nathan Whitener Jason Grayson, and Natalia Khuri. “An Ensemble Machine Learning Approach for Benchmarking and Selection of scRNA-seq Integration Methods.” 14th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (2023). — Publication Link
Tat, Hong Hue, Yuan-Jye Wu, Joseph D. Schaefer, Anne Kao, Mary J. Mathews, Matthew G. Pike, Victor P. Pauca, and Rongzhong Li. “Method and apparatus for acoustic emissions testing.” U.S. Patent 10,564,130, issued February 18, 2020.
Camalan, Seda, Kangning Cui, Paúl Pauca, Sarra Alqahtani, Miles Silman, Raymond Chan, Robert Plemmons, Evan Dethier, Luis Fernandez, and David Lutz. “Change Detection of Amazonian Alluvial Gold Mining Using Deep Learning and Sentinel-2 Imagery.” Remote Sensing 14, no. 7 (2022): 1746. — Publication Link
Cui, Kangning, Seda Camalan, Ruoning Li, Paúl Pauca, Sarra Alqahtani, Robert Plemmons, Miles Silman, Evan Nylen Dethier, David Lutz, and Raymond Chan. “Semi-supervised Change Detection of Small Water Bodies Using RGB and Multispectral Images in Peruvian Rainforests.” In 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), pp. 1-5. IEEE, 2022. — Publication Link
Dethier, Evan, Miles Silman, Jimena Díaz Leiva, Sarra Alqahtani, Luis Fernandez, Paúl Pauca, Seda Çamalan, Francis Magilligan, Carl Renshaw, and David Lutz. “The global crisis of mining in tropical rivers.” (2022). — Publication Link (Preprint)
(*) Liu, Tongtong, Joe McCalmon, Md Asifur Rahman, Cameron Lischke, Talal Halabi, and Sarra Alqahtani. “Weaponizing Actions in Multi-Agent Reinforcement Learning: Theoretical and Empirical Study on Security and Robustness.” In PRIMA 2022: Principles and Practice of Multi-Agent Systems: 24th International Conference, Valencia, Spain, November 16–18, 2022, Proceedings, pp. 347-363. Cham: Springer International Publishing, 2022. — Publication Link
(*) Lischke, Cameron, Tongtong Liu, Joe McCalmon, Md Asifur Rahman, Talal Halabi, and Sarra Alqahtani. “LSTM-Based Anomalous Behavior Detection in Multi-Agent Reinforcement Learning.” In 2022 IEEE International Conference on Cyber Security and Resilience (CSR), pp. 16-21. IEEE, 2022. — Publication Link
Halabi, Talal, Aawista Chaudhry, Sarra Alqahtani, and Mohammad Zulkernine. “A Scary Peek into The Future: Advanced Persistent Threats in Emerging Computing Environments.” In 2022 IEEE Conference on Dependable and Secure Computing (DSC), pp. 1-8. IEEE, 2022. — Publication Link
(*) McCalmon, Joe, Thai Le, Sarra Alqahtani, and Dongwon Lee. “CAPS: Comprehensible Abstract Policy Summaries for Explaining Reinforcement Learning Agents.” Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022), pp. 889-897. 2022. — Publication Link
Daas, Hussam Al, Grey Ballard, and Peter Benner. “Parallel algorithms for tensor train arithmetic.” SIAM Journal on Scientific Computing 44, no. 1 (2022): C25-C53. — Publication Link
(*) Daas, Hussam Al, Grey Ballard, and Lawton Manning. “Parallel Tensor Train Rounding using Gram SVD.” 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 930-940. IEEE, 2022. — Publication Link
(*) Daas, Hussam Al, Grey Ballard, Laura Grigori, Suraj Kumar, and Kathryn Rouse. “Tight Memory-Independent Parallel Matrix Multiplication Communication Lower Bounds.” arXiv preprint arXiv:2205.13047 (2022). — Publication Link (Preprint)
(*) Daas, Hussam Al, Grey Ballard, Laura Grigori, Suraj Kumar and Kathryn Rouse. “Tight Memory-Independent Parallel Matrix Multiplication Communication Lower Bounds”. Proceedings of the 34th Annual ACM Symposium on Parallelism in Algorithms and Architectures, SPAA ’22, ACM, New York, NY, USA. 2022. — Publication Link
(*) Daas, Hussam Al, Grey Ballard, Laura Grigori, Suraj Kumar, and Kathryn Rouse. “Communication Lower Bounds and Optimal Algorithms for Multiple Tensor-Times-Matrix Computation.” arXiv preprint arXiv:2207.10437 (2022). — Publication Link (Preprint)
(*) Minster, Rachel, Zitong Li, and Grey Ballard. “Parallel Randomized Tucker Decomposition Algorithms.” arXiv preprint arXiv:2211.13028 (2022). — Publication Link (Preprint)
(*) Xu, Chunrui, Layne Watson, Henry Hollis, Michelle Dai, Xiangyu Yao, Yang Cao, and Minghan Chen. “Modeling the temporal dynamics of master regulators and CtrA proteolysis in Caulobacter crescentus cell cycle.” PLOS Computational Biology 18, no. 1 (2022): e1009847. — Publication Link
(*) Chen, Minghan, Chunrui Xu, Ziang Xu, Wei He, Haorui Zhang, Jing Su, and Qianqian Song. “Uncovering the dynamic effects of DEX treatment on lung cancer by integrating bioinformatic inference and multiscale modeling of scRNA-seq and proteomics data.” Computers in biology and medicine 149 (2022): 105999. — Publication Link
Li, Wenchao, Defu Yang, Chenggang Yan, Minghan Chen, Quefeng Li, Wentao Zhu, Guorong Wu, and Alzheimer’s Disease Neuroimaging Initiative. “Characterizing Network Selectiveness to the Dynamic Spreading of Neuropathological Events in Alzheimer’s Disease.” Journal of Alzheimer’s Disease (2022): 1-12. — Publication Link
(*) Zhang, Jingwen, Qing Liu, Haorui Zhang, Michelle Dai, Qianqian Song, Defu Yang, Guorong Wu, and Minghan Chen. “Uncovering the system vulnerability and criticality of human brain under evolving neuropathological events in Alzheimer’s Disease.” arXiv preprint arXiv:2201.08941 (2022). — Publication Link (Preprint)
(*) Li, Wenchao, Jiaqi Zhao, Chenyu Shen, Jingwen Zhang, Ji Hu, Mang Xiao, Jiyong Zhang, and Minghan Chen. “Regional Brain Fusion: Graph Convolutional Network for Alzheimer’s Disease Prediction and Analysis”. Frontiers In Neuroinformatics 2022. — Publication Link
(*) Yang, Defu, Wenchao Li, Jingwen Zhang, Hui Shen, Minghan Chen, Wentao Zhu, and Guorong Wu. “A neuropathological hub identification for Alzheimer’s disease via joint analysis of topological structure and neuropathological burden”. IEEE International Symposium on Biomedical Imaging, 2022. — Publication Link
Qian, Wei, Chenxu Zhao, Huajie Shao, Minghan Chen, Fei Wang, and Mengdi Huai. “Patient Similarity Learning with Selective Forgetting”. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 529-534, 2022. — Publication Link
(*) Chen, Minghan, Shishen Jia, Mengfan Xue, Hailiang Huang, Ziang Xu, Defu Yang, Wentao Zhu, and Qianqian Song. “Dual-Stream Subspace Clustering Network for revealing gene targets in Alzheimer’s disease.” Computers in Biology and Medicine 151 (2022): 106305. — Publication Link
(*) Xu, Enze, Jingwen Zhang, Jiadi Li, Defu Yang, Guorong Wu, and Minghan Chen. “Pathology Steered Stratification Network for Subtype Identification in Alzheimer’s Disease.” arXiv preprint arXiv:2210.05880 (2022). — Publication Link (Preprint)
Song, Qianqian, Xuewei Zhu, Lingtao Jin, Minghan Chen, Wei Zhang, and Jing Su. “SMGR: a joint statistical method for integrative analysis of single-cell multi-omics data.” NAR genomics and bioinformatics 4, no. 3 (2022): lqac056. — Publication Link
(*) Chen, Jing, Enze Xu, Yong Wei, Minghan Chen, Tao Wei, and Size Zheng. “Graph Clustering Analyses of Discontinuous Molecular Dynamics Simulations: Study of Lysozyme Adsorption on a Graphene Surface.” Langmuir 38, no. 35 (2022): 10817-10825. — Publication Link
(*) Zhang, Jingwen, Enze Xu, and Minghan Chen. “AT [N]-net: multimodal spatiotemporal network for subtype identification in Alzheimer’s disease.” Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, pp. 1-1. 2022. — Publication Link
(*) Green, Adam, Amanda Pickard, Rongzhong Li, Alexander MacKerell Jr, Ulrich Bierbach, and Samuel Cho. “Computational and Experimental Characterization of rDNA and rRNA G-Quadruplexes.” The Journal of Physical Chemistry B (2022). — Publication Link
Koculi, Eda, and Samuel Cho. “RNA Post-Transcriptional Modifications in Two Large Subunit Intermediates Populated in E. coli Cells Expressing Helicase Inactive R331A DbpA.” Biochemistry 61, no. 10 (2022): 833-842. — Publication Link
(*) Hamilton, Nolan, and Errin Fulp. “Budgeted Classification with Rejection: An Evolutionary Method with Multiple Objectives.” 2022 IEEE Congress on Evolutionary Computation (CEC), pp. 1-10. IEEE, 2022. — Publication Link
(*) Bhandari, Sapan, Nathan Whitener, Konghao Zhao, and Natalia Khuri. “Multi-target integration and annotation of single-cell RNA-sequencing data.” Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, pp. 1-4. 2022. — Publication Link
(*) Khuri, Natalia, Sapan Bhandari, Esteban Murillo Burford, Nathan Whitener, and Konghao Zhao. “An evolutionary approach to data valuation.” Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, pp. 1-10. 2022. — Publication Link
(*) Parsons, Sarah, Nathan Whitener, Sapan Bhandari, and Natalia Khuri. “Interpretable Hierarchical Bayesian Modeling of Cell-Type Distributions in COVID-19 Disease.” In 2022 56th Annual Conference on Information Sciences and Systems (CISS), pp. 7-12. IEEE, 2022. — Publication Link
(*) Wang, Xiaochen, and Natalia Khuri. “Generative Adversarial Network for the Segmentation of Ground Glass Opacities and Consolidations from Lung CT Images.” In BIOINFORMATICS, pp. 27-37. 2022. — Publication Link
(*) Bilodeau, Stephanie, Austin Schwartz, Binfeng Xu, Paúl Pauca, and Miles Silman. “A low-cost, long-term underwater camera trap network coupled with deep residual learning image analysis.” Plos one 17, no. 2 (2022): e0263377. — Publication Link
(*) Peake, Ashley, Joe McCalmon, Yixin Zhang, Daniel Myers, Sarra Alqahtani, and Paúl Pauca. “Deep Reinforcement Learning for Adaptive Exploration of Unknown Environments”. In 2021 International Conference on Unmanned Aircraft Systems (ICUAS). — Publication Link
(*) Zhang, Yixin, Joe McCalmon, Ashley Peake, Sarra Alqahtani, and Paúl Pauca. “A Symbolic-AI Approach for UAV Exploration Tasks.” In 2021 7th International Conference on Automation, Robotics and Applications (ICARA), pp. 101-105. IEEE, 2021. — Publication Link
(*) Li, Zitong, Qiming Fang, and Grey Ballard. “Parallel Tucker Decomposition with Numerically Accurate SVD.” In 50th International Conference on Parallel Processing, pp. 1-11. 2021. — Publication Link
(*) Ballard, Grey, Jack Weissenberger, and Luoping Zhang. “Accelerating Neural Network Training using Arbitrary Precision Approximating Matrix Multiplication Algorithms.” In 50th International Conference on Parallel Processing Workshop, pp. 1-8. 2021. — Publication Link
(*) Eswar, Srinivas, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Michael A. Matheson, and Haesun Park. “PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints.” ACM Transactions on Mathematical Software (TOMS) 47, no. 3 (2021): 1-37. — Publication Link
(*) Ballard, Grey and Sarah Parsons. “Visualizing Parallel Dynamic Programming using the Thread Safe Graphics Library.” In EduHPC-21: Workshop on Education for High Performance Computing at the International Conference for High Performance Computing, Networking, Storage, and Analysis, 2021. — Publication Link
(*) Liu, Qing, Defu Yang, Jingwen Zhang, Ziming Wei, Guorong Wu, and Minghan Chen. “Analyzing the Spatiotemporal Interaction and Propagation of ATN Biomarkers in Alzheimer’s Disease using Longitudinal Neuroimaging Data.” IEEE International Symposium on Biomedical Imaging, 2021. — Publication Link (Preprint)
(*) Hamilton, Nolan and Errin Fulp. “Evolutionary Optimization of High-Coverage Budgeted Classifiers.” arXiv preprint arXiv:2110.13067 (2021). — Publication Link (Preprint)
(*) Khuri, Natalia and Anish Prasanna. “Using Game Theory to Guide the Classification of Inhibitors of Human Iodide Transporters.” In Proceedings of the 36th ACM/SIGAPP Symposium On Applied Computing. March 2021. — Publication Link
(*) Liu, Tianen and Natalia Khuri. “Classification of Drug Prescribing Information Using Long Short-Term Memory Networks.” In Proceedings of the 36th ACM/SIGAPP Symposium On Applied Computing. March 2021. — Publication Link
(*) Yun, Tian, Deepti Garg, and Natalia Khuri. “Mining Biomedical Texts for Pediatric Information”. In Proceedings of the 12th International Conference on Bioinformatics Models, Methods and Algorithms. February 2021. — Publication Link
Salcedo, Eugenia, Michael Winter, Natalia Khuri, Giselle Knudsen, Andrej Sali, and Charles Craik. “Global Protease Activity Profiling Identifies HER2-Driven Proteolysis in Breast Cancer.” ACS Chemical Biology 2021. — Publication Link
(*) Khuri, Natalia, Esteban Murillo Burford, Sarah Parsons, and Chenqi Xu. “A Game-Theoretical Approach for Data Acquisition From Fitness Tracking Devices.” In Proceedings of the IEEE Symposium on Networks, Computers and Communications. June 2021. — Publication Link
(*) Khuri, Natalia and Sarah Parsons. “A Value-Based Approach for Training of Classifiers with High-Throughput Small Molecule Screening Data.” In Proceedings of the 2021 ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB). — Publication Link
Alqahtani, Sarra, Xinchi He, Rose Gamble, and Papa Mauricio. “Formal Verification of Functional Requirements for Smart Contract Compositions in Supply Chain Management Systems.” In Proceedings of the 53rd Hawaii International Conference on System Sciences. 2020. — Publication Link
(*) Peake, Ashley, Joe McCalmon, Yixin Zhang, Benjamin Raiford, and Sarra Alqahtani. “Wilderness Search and Rescue Missions using Deep Reinforcement Learning.” In 2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), pp. 102-107. IEEE, 2020. — Publication Link
(*) Peake, Ashley, Joe McCalmon, Benjamin Raiford, Tongtong Liu, and Sarra Alqahtani. “Multi-agent reinforcement learning for cooperative adaptive cruise control.” In 2020 IEEE 32nd International Conference on Tools with Artificial Intelligence (ICTAI), pp. 15-22. IEEE, 2020. — Publication Link
Daas, Hussam Al, Grey Ballard, and Peter Benner. “Parallel Algorithms for Tensor Train Arithmetic.” arXiv preprint arXiv:2011.06532 (2020). — Publication Link
(*) Eswar, Srinivas, Koby Hayashi, Grey Ballard, Ramakrishnan Kannan, Richard Vuduc, and Haesun Park. “Distributed-memory parallel symmetric nonnegative matrix factorization.” In 2020 SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (SC), pp. 1041-1054. IEEE Computer Society, 2020. — Publication Link
Devine, Karen D., and Grey Ballard. “GentenMPI: Distributed Memory Sparse Tensor Decomposition.” No. SAND2020-8515. Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2020. — Publication Link
Al Daas, Hussam, Grey Ballard, and Peter Benner. “Communication-avoiding TT-tensor orthogonalization and rounding procedures.” In XXI Householder Symposium on Numerical Linear Algebra, p. 93. 2020. — Publication Link
Ballard, Grey, Alicia Klinvex, and Tamara G. Kolda. “TuckerMPI: a parallel C++/MPI software package for large-scale data compression via the tucker tensor decomposition.” ACM Transactions on Mathematical Software (TOMS) 46, no. 2 (2020): 1-31. — Publication Link
(*) Ballard, Grey, and Kathryn Rouse. “General Memory-Independent Lower Bound for MTTKRP.” In Proceedings of the 2020 SIAM Conference on Parallel Processing for Scientific Computing, pp. 1-11. Society for Industrial and Applied Mathematics, 2020. — Publication Link
(*) Zhang, Jingwen, Defu Yang, Wei He, Guorong Wu, and Minghan Chen. “A Network-Guided Reaction-Diffusion Model of AT [N] Biomarkers in Alzheimer’s Disease.” In 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE), pp. 222-229. IEEE, 2020. — Publication Link
Chen, Minghan, Mansooreh Ahmadian, L. T. Watson, and Yang Cao. “Finding acceptable parameter regions of stochastic Hill functions for multisite phosphorylation mechanism.” The Journal of chemical physics 152, no. 12 (2020): 124108. — Publication Link
(*) Hamilton, Nolan H., Eddie Allan, and Errin Fulp. “Cluster Analysis of Passive DNS Features for Identifying Domain Shadowing Infrastructure.” In 2020 International Symposium on Networks, Computers and Communications (ISNCC), pp. 1-4. IEEE, 2020. — Publication Link
(*) Bhandari, Arnav, Katherine Juarez, and Errin Fulp. “Using Execution Profiles to Identify Process Behavior Classes.” In 2020 International Symposium on Networks, Computers and Communications (ISNCC), pp. 1-4. IEEE, 2020. — Publication Link
(*) Prosser, Bryan J., and Errin Fulp. “A Distributed Population Management Approach for Mobile Agent Systems.” In 2020 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), pp. 102-108. IEEE, 2020. — Publication Link
(*) Hamilton, Nolan H., and Errin Fulp. “An evolutionary approach for constructing multi-stage classifiers.” In Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, pp. 1730-1738. 2020. — Publication Link
(*) Rodríguez, Alina Pacheco, Errin Fulp, David John, and Jinku Cui. “Using evolutionary algorithms and pareto ranking to identify secure virtual local area networks.” In Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, pp. 1512-1519. 2020. — Publication Link
(*) Hamilton, Nolan H., Steve McKinney, Eddie Allan, and Errin Fulp. “An Efficient Multi-Stage Approach for Identifying Domain Shadowing.” In ICC 2020-2020 IEEE International Conference on Communications (ICC), pp. 1-7. IEEE, 2020. — Publication Link
Zou, Ling, Peter Spanogiannopoulos, Lindsey M. Pieper, Huan-Chieh Chien, Wenlong Cai, Natalia Khuri, Joshua Pottel et al. “Bacterial metabolism rescues the inhibition of intestinal drug absorption by food and drug additives.” Proceedings of the National Academy of Sciences 117, no. 27 (2020): 16009-16018. — Publication Link
Khuri, Natalia. “Mining environmental chemicals with boosted trees.” In Proceedings of the 35th Annual ACM Symposium on Applied Computing, pp. 1082-1089. 2020. — Publication Link
Khuri, Natalia, Wendy Lee, K. Virginia Lehmkuhl-Dakhwe, Miri VanHoven, and Sami Khuri. “Interdisciplinary Minor in Bioinformatics: First Results and Outlook.” In Proceedings of the 51st ACM Technical Symposium on Computer Science Education, pp. 407-412. 2020. — Publication Link
Zou, Ling, Joshua Pottel, Natalia Khuri, Huy X. Ngo, Zhanglin Ni, Eleftheria Tsakalozou, Mark S. Warren, Yong Huang, Brian K. Shoichet, and Kathleen M. Giacomini. “Interactions of oral molecular excipients with breast cancer resistance protein, BCRP.” Molecular pharmaceutics 17, no. 3 (2020): 748-756. — Publication Link
(*) Parsons, Sarah and Natalia Khuri. “Discovery of Research Trends in Computer Science Education on Ethics Using Topic Modeling.” In Proceedings of the 2020 International Conference on Computational Science and Computational Intelligence. 2020. — Publication Link
Gutiérrez, Giancarlos, Eveling Castro, Javier Delgado, Paúl Pauca, Stefan Klein, and Hans Lamecker. “Automatic quantification of hip osteoarthritis from low-quality x-ray images.” In Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, vol. 11317, p. 113172A. International Society for Optics and Photonics, 2020. — Publication Link