NUFACTS: A tool for the analysis of nuclear development policies. - Mark B. Triplett; Theodore L. Willke; John D. Waddell (WSC, 1977)

Reliable Collaborative Decision Making in Mobile Ad Hoc Networks. - Theodore L. Willke; Nicholas F. Maxemchuk (MMNS, 2004)

Coordinated interaction using reliable broadcast in mobile wireless networks. - Theodore L. Willke; Nicholas F. Maxemchuk (Comput. Networks, 2007)

Reliable Neighborcast. - Nicholas F. Maxemchuk; Patcharinee Tientrakool; Theodore L. Willke (IEEE Trans. Veh. Technol., 2007)

A survey of inter-vehicle communication protocols and their applications. - Theodore L. Willke; Patcharinee Tientrakool; Nicholas F. Maxemchuk (IEEE Commun. Surv. Tutorials, 2009)

Gunther: Search-Based Auto-Tuning of MapReduce. - Guangdeng Liao; Kushal Datta; Theodore L. Willke (Euro-Par, 2013)

Towards Machine Learning-Based Auto-tuning of MapReduce. - Nezih Yigitbasi; Theodore L. Willke; Guangdeng Liao; Dick H. J. Epema (MASCOTS, 2013)

GraphBuilder: scalable graph ETL framework. - Nilesh Jain; Guangdeng Liao; Theodore L. Willke (GRADES, 2013)

How Well Do Graph-Processing Platforms Perform? An Empirical Performance Evaluation and Analysis. - Yong Guo; Marcin Biczak; Ana Lucia Varbanescu; Alexandru Iosup; Claudio Martella; Theodore L. Willke (IPDPS, 2014)

Benchmarking graph-processing platforms: a vision. - Yong Guo; Ana Lucia Varbanescu; Alexandru Iosup; Claudio Martella; Theodore L. Willke (ICPE, 2014)

Full correlation matrix analysis of fMRI data on Intel® Xeon Phi™ coprocessors. - Yida Wang 003; Michael J. Anderson; Jonathan D. Cohen 003; Alexander Heinecke; Kai Li 001; Nadathur Satish; Narayanan Sundaram; Nicholas B. Turk-Browne; Theodore L. Willke (SC, 2015)

Estimation of local subgraph counts. - Nesreen K. Ahmed; Theodore L. Willke; Ryan A. Rossi (IEEE BigData, 2016)

Enabling factor analysis on thousand-subject neuroimaging datasets. - Michael J. Anderson; Mihai Capota; Javier S. Turek; Xia Zhu; Theodore L. Willke; Yida Wang 003; Po-Hsuan Chen; Jeremy R. Manning; Peter J. Ramadge; Kenneth A. Norman (IEEE BigData, 2016)

Real-time full correlation matrix analysis of fMRI data. - Yida Wang 003; Bryn Keller; Mihai Capota; Michael J. Anderson; Narayanan Sundaram; Jonathan D. Cohen 003; Kai Li 001; Nicholas B. Turk-Browne; Theodore L. Willke (IEEE BigData, 2016)

Controlled vs. Automatic Processing: A Graph-Theoretic Approach to the Analysis of Serial vs. Parallel Processing in Neural Network Architectures. - Sebastian Musslick; Biswadip Dey; Kayhan Özcimder; Md. Mostofa Ali Patwary; Theodore L. Willke; Jonathan D. Cohen 003 (CogSci, 2016)

GraphIn: An Online High Performance Incremental Graph Processing Framework. - Dipanjan Sengupta; Narayanan Sundaram; Xia Zhu; Theodore L. Willke; Jeffrey S. Young 001; Matthew Wolf; Karsten Schwan (Euro-Par, 2016)

GraphPad: Optimized Graph Primitives for Parallel and Distributed Platforms. - Michael J. Anderson; Narayanan Sundaram; Nadathur Satish; Md. Mostofa Ali Patwary; Theodore L. Willke; Pradeep Dubey (IPDPS, 2016)

Exact and Estimation of Local Edge-centric Graphlet Counts. - Nesreen K. Ahmed; Theodore L. Willke; Ryan A. Rossi (BigMine, 2016)

Revisiting Role Discovery in Networks: From Node to Edge Roles. - Nesreen K. Ahmed; Ryan A. Rossi; Theodore L. Willke; Rong Zhou 001 (CoRR, 2016)

A Convolutional Autoencoder for Multi-Subject fMRI Data Aggregation. - Po-Hsuan Chen; Xia Zhu; Hejia Zhang; Javier S. Turek; Janice Chen; Theodore L. Willke; Uri Hasson; Peter J. Ramadge (CoRR, 2016)

A Searchlight Factor Model Approach for Locating Shared Information in Multi-Subject fMRI Analysis. - Hejia Zhang; Po-Hsuan Chen; Janice Chen; Xia Zhu; Javier S. Turek; Theodore L. Willke; Uri Hasson; Peter J. Ramadge (CoRR, 2016)

A Higher-Order Latent Space Network Model. - Nesreen K. Ahmed; Ryan A. Rossi; Theodore L. Willke; Rong Zhou 001 (AAAI Workshops, 2017)

A Formal Approach to Modeling the Cost of Cognitive Control. - Kayhan Özcimder; Biswadip Dey; Sebastian Musslick; Giovanni Petri; Nesreen K. Ahmed; Theodore L. Willke; Jonathan D. Cohen 003 (CogSci, 2017)

A semi-supervised method for multi-subject FMRI functional alignment. - Javier S. Turek; Theodore L. Willke; Po-Hsuan Chen; Peter J. Ramadge (ICASSP, 2017)

Edge Role Discovery via Higher-Order Structures. - Nesreen K. Ahmed; Ryan A. Rossi; Theodore L. Willke; Rong Zhou 001 (PAKDD (1), 2017)

High-Performance Incremental SVM Learning on Intel® Xeon Phi™ Processors. - Dipanjan Sengupta; Yida Wang 003; Narayanan Sundaram; Theodore L. Willke (ISC, 2017)

A Framework for Generalizing Graph-based Representation Learning Methods. - Nesreen K. Ahmed; Ryan A. Rossi; Rong Zhou 001; John Boaz Lee; Xiangnan Kong; Theodore L. Willke; Hoda Eldardiry (CoRR, 2017)

Representation Learning in Large Attributed Graphs. - Nesreen K. Ahmed; Ryan A. Rossi; Rong Zhou 001; John Boaz Lee; Xiangnan Kong; Theodore L. Willke; Hoda Eldardiry (CoRR, 2017)

Segmenting Brain Tumors with Symmetry. - Hejia Zhang; Xia Zhu; Theodore L. Willke (CoRR, 2017)

Graphlet decomposition: framework, algorithms, and applications. - Nesreen K. Ahmed; Jennifer Neville; Ryan A. Rossi; Nick G. Duffield; Theodore L. Willke (Knowl. Inf. Syst., 2017)

On Sampling from Massive Graph Streams. - Nesreen K. Ahmed; Nick G. Duffield; Theodore L. Willke; Ryan A. Rossi (Proc. VLDB Endow., 2017)

Bridging the Gap between HPC and Big Data frameworks. - Michael J. Anderson; Shaden Smith; Narayanan Sundaram; Mihai Capota; Zheguang Zhao; Subramanya Dulloor; Nadathur Satish; Theodore L. Willke (Proc. VLDB Endow., 2017)

Matrix-normal models for fMRI analysis. - Michael Shvartsman; Narayanan Sundaram; Mikio Aoi; Adam Charles; Theodore L. Willke; Jonathan D. Cohen 003 (AISTATS, 2018)

Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-Out Classifiers. - Apoorv Vyas; Nataraj Jammalamadaka; Xia Zhu; Dipankar Das 002; Bharat Kaul; Theodore L. Willke (ECCV (8), 2018)

Capturing Shared and Individual Information in fMRI Data. - Javier S. Turek; Cameron T. Ellis; Lena J. Skalaban; Nicholas B. Turk-Browne; Theodore L. Willke (ICASSP, 2018)

Learning Role-based Graph Embeddings. - Nesreen K. Ahmed; Ryan A. Rossi; John Boaz Lee; Xiangnan Kong; Theodore L. Willke; Rong Zhou 001; Hoda Eldardiry (CoRR, 2018)

Scheduling Computation Graphs of Deep Learning Models on Manycore CPUs. - Linpeng Tang; Yida Wang 003; Theodore L. Willke; Kai Li 001 (CoRR, 2018)

Clinically Deployed Distributed Magnetic Resonance Imaging Reconstruction: Application to Pediatric Knee Imaging. - Michael J. Anderson; Jonathan I. Tamir; Javier S. Turek; Marcus T. Alley; Theodore L. Willke; Shreyas S. Vasanawala; Michael Lustig (CoRR, 2018)

Similarity Learning with Higher-Order Proximity for Brain Network Analysis. - Guixiang Ma; Nesreen K. Ahmed; Theodore L. Willke; Dipanjan Sengupta; Michael W. Cole; Nicholas B. Turk-Browne; Philip S. Yu (CoRR, 2018)

A probabilistic approach to discovering dynamic full-brain functional connectivity patterns. - Jeremy R. Manning; Xia Zhu; Theodore L. Willke; Rajesh Ranganath; Kimberly L. Stachenfeld; Uri Hasson; David M. Blei; Kenneth A. Norman (NeuroImage, 2018)

Deep Graph Similarity Learning for Brain Data Analysis. - Guixiang Ma; Nesreen K. Ahmed; Theodore L. Willke; Dipanjan Sengupta; Michael W. Cole; Nicholas B. Turk-Browne; Philip S. Yu (CIKM, 2019)

Deep Reinforcement Learning in System Optimization. - Ameer Haj-Ali; Nesreen K. Ahmed; Theodore L. Willke; Joseph Gonzalez 001; Krste Asanovic; Ion Stoica (CoRR, 2019)

A single-layer RNN can approximate stacked and bidirectional RNNs, and topologies in between. - Javier S. Turek; Shailee Jain; Mihai Capota; Alexander G. Huth; Theodore L. Willke (CoRR, 2019)

NeuroVectorizer: end-to-end vectorization with deep reinforcement learning. - Ameer Haj-Ali; Nesreen K. Ahmed; Theodore L. Willke; Yakun Sophia Shao; Krste Asanovic; Ion Stoica (CGO, 2020)

Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network. - Javier Turek; Shailee Jain; Vy A. Vo; Mihai Capota; Alexander Huth; Theodore L. Willke (ICML, 2020)

Procrustean Orthogonal Sparse Hashing. - Mariano Tepper; Dipanjan Sengupta; Theodore L. Willke (CoRR, 2020)

Navigating the Trade-Off between Multi-Task Learning and Learning to Multitask in Deep Neural Networks. - Sachin Ravi; Sebastian Musslick; Maia Hamin; Theodore L. Willke; Jonathan D. Cohen 003 (CoRR, 2020)

A Vertex Cut based Framework for Load Balancing and Parallelism Optimization in Multi-core Systems. - Guixiang Ma; Yao Xiao; Theodore L. Willke; Nesreen K. Ahmed; Shahin Nazarian; Paul Bogdan (CoRR, 2020)

BrainIAK tutorials: User-friendly learning materials for advanced fMRI analysis. - Manoj Kumar; Cameron T. Ellis; Qihong Lu; Hejia Zhang; Mihai Capota; Theodore L. Willke; Peter J. Ramadge; Nicholas B. Turk-Browne; Kenneth A. Norman (PLoS Comput. Biol., 2020)

Learning Code Representations Using Multifractal-based Graph Networks. - Guixiang Ma; Yao Xiao; Mihai Capota; Theodore L. Willke; Shahin Nazarian; Paul Bogdan; Nesreen K. Ahmed (IEEE BigData, 2021)

A Distributed Graph-Theoretic Framework for Automatic Parallelization in Multi-core Systems. - Guixiang Ma; Yao Xiao; Theodore L. Willke; Nesreen K. Ahmed; Shahin Nazarian; Paul Bogdan (MLSys, 2021)

Slower is Better: Revisiting the Forgetting Mechanism in LSTM for Slower Information Decay. - Hsiang-Yun Sherry Chien; Javier S. Turek; Nicole Beckage; Vy A. Vo; Christopher J. Honey; Theodore L. Willke (CoRR, 2021)

Deep graph similarity learning: a survey. - Guixiang Ma; Nesreen K. Ahmed; Theodore L. Willke; Philip S. Yu (Data Min. Knowl. Discov., 2021)

End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning. - Yao Xiao; Guixiang Ma; Nesreen K. Ahmed; Mihai Capota; Theodore L. Willke; Shahin Nazarian; Paul Bogdan (CoRR, 2022)

Toward a Geometrical Understanding of Self-supervised Contrastive Learning. - Romain Cosentino; Anirvan M. Sengupta; Salman Avestimehr; Mahdi Soltanolkotabi; Antonio Ortega; Theodore L. Willke; Mariano Tepper (CoRR, 2022)

Memory-Augmented Graph Neural Networks: A Neuroscience Perspective. - Guixiang Ma; Vy A. Vo; Theodore L. Willke; Nesreen K. Ahmed (CoRR, 2022)

Memory in humans and deep language models: Linking hypotheses for model augmentation. - Omri Raccah; Phoebe Chen; Theodore L. Willke; David Poeppel; Vy A. Vo (CoRR, 2022)

Role-Based Graph Embeddings. - Nesreen K. Ahmed; Ryan A. Rossi; John Boaz Lee; Theodore L. Willke; Rong Zhou 001; Xiangnan Kong; Hoda Eldardiry (IEEE Trans. Knowl. Data Eng., 2022)

Augmenting Recurrent Graph Neural Networks with a Cache. - Guixiang Ma; Vy A. Vo; Theodore L. Willke; Nesreen K. Ahmed (KDD, 2023)

Scope is all you need: Transforming LLMs for HPC Code. - Tal Kadosh; Niranjan Hasabnis; Vy A. Vo; Nadav Schneider; Neva Krien; Abdul Wasay; Nesreen K. Ahmed; Ted Willke; Guy Tamir; Yuval Pinter; Timothy G. Mattson; Gal Oren 001 (CoRR, 2023)

Leveraging Reinforcement Learning and Large Language Models for Code Optimization. - Shukai Duan 002; Nikos Kanakaris; Xiongye Xiao; Heng Ping; Chenyu Zhou; Nesreen K. Ahmed; Guixiang Ma; Mihai Capota; Theodore L. Willke; Shahin Nazarian; Paul Bogdan (CoRR, 2023)

Domain-Specific Code Language Models: Unraveling the Potential for HPC Codes and Tasks. - Tal Kadosh; Niranjan Hasabnis; Vy A. Vo; Nadav Schneider; Neva Krien; Mihai Capota; Abdul Wasay; Nesreen K. Ahmed; Ted Willke; Guy Tamir; Yuval Pinter; Timothy G. Mattson; et al. (CoRR, 2023)

LeanVec: Search your vectors faster by making them fit. - Mariano Tepper; Ishwar Singh Bhati; Cecilia Aguerrebere; Mark Hildebrand; Ted Willke (CoRR, 2023)

Similarity search in the blink of an eye with compressed indices. - Cecilia Aguerrebere; Ishwar Singh Bhati; Mark Hildebrand; Mariano Tepper; Theodore L. Willke (Proc. VLDB Endow., 2023)

Structure Guided Prompt: Instructing Large Language Model in Multi-Step Reasoning by Exploring Graph Structure of the Text. - Kewei Cheng; Nesreen K. Ahmed; Theodore L. Willke; Yizhou Sun (EMNLP, 2024)

MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks. - Tal Kadosh; Niranjan Hasabnis; Vy A. Vo; Nadav Schneider; Neva Krien; Mihai Capota; Abdul Wasay; Guy Tamir; Ted Willke; Nesreen K. Ahmed; Yuval Pinter; Timothy G. Mattson; et al. (HPEC, 2024)

A Structure-Aware Framework for Learning Device Placements on Computation Graphs. - Shukai Duan 002; Heng Ping; Nikos Kanakaris; Xiongye Xiao; Panagiotis Kyriakis; Nesreen K. Ahmed; Peiyu Zhang 002; Guixiang Ma; Mihai Capota; Shahin Nazarian; Theodore L. Willke; Paul Bogdan (NeurIPS, 2024)

The Landscape and Challenges of HPC Research and LLMs. - Le Chen; Nesreen K. Ahmed; Akash Dutta; Arijit Bhattacharjee; Sixing Yu; Quazi Ishtiaque Mahmud; Waqwoya Abebe; Hung Phan; Aishwarya Sarkar; Branden Butler; Niranjan Hasabnis; Gal Oren 001; et al. (CoRR, 2024)

Locally-Adaptive Quantization for Streaming Vector Search. - Cecilia Aguerrebere; Mark Hildebrand; Ishwar Singh Bhati; Theodore L. Willke; Mariano Tepper (CoRR, 2024)

MPIrigen: MPI Code Generation through Domain-Specific Language Models. - Nadav Schneider; Niranjan Hasabnis; Vy A. Vo; Tal Kadosh; Neva Krien; Mihai Capota; Abdul Wasay; Guy Tamir; Ted Willke; Nesreen K. Ahmed; Yuval Pinter; Timothy G. Mattson; et al. (CoRR, 2024)

GleanVec: Accelerating vector search with minimalist nonlinear dimensionality reduction. - Mariano Tepper; Ishwar Singh Bhati; Cecilia Aguerrebere; Ted Willke (CoRR, 2024)

Toward Optimal Search and Retrieval for RAG. - Alexandria Leto; Cecilia Aguerrebere; Ishwar Singh Bhati; Ted Willke; Mariano Tepper; Vy Ai Vo (CoRR, 2024)

GraSS: Graph-based Similarity Search on Encrypted Query. - Duhyeong Kim; Yujin Nam; Wen Wang 007; Huijing Gong; Ishwar Singh Bhati; Rosario Cammarota; Tajana Simunic Rosing; Mariano Tepper; Theodore L. Willke (IACR Cryptol. ePrint Arch., 2024)

LeanVec: Searching vectors faster by making them fit. - Mariano Tepper; Ishwar Singh Bhati; Cecilia Aguerrebere; Mark Hildebrand; Theodore L. Willke (Trans. Mach. Learn. Res., 2024)

Memory-Augmented Graph Neural Networks: A Brain-Inspired Review. - Guixiang Ma; Vy A. Vo; Theodore L. Willke; Nesreen K. Ahmed (IEEE Trans. Artif. Intell., 2024)

Neural-Symbolic Methods for Knowledge Graph Reasoning: A Survey. - Kewei Cheng; Nesreen K. Ahmed; Ryan A. Rossi; Theodore L. Willke; Yizhou Sun (ACM Trans. Knowl. Discov. Data, 2024)

PCEBench: A Multi-Dimensional Benchmark for Evaluating Large Language Models in Parallel Code Generation. - Le Chen; Nesreen K. Ahmed; Mihai Capota; Ted Willke; Niranjan Hasabnis; Ali Jannesari (IPDPS, 2025)

AutoParLLM: GNN-guided Context Generation for Zero-Shot Code Parallelization using LLMs. - Quazi Ishtiaque Mahmud; Ali TehraniJamsaz; Hung D. Phan; Le Chen; Mihai Capota; Theodore L. Willke; Nesreen K. Ahmed; Ali Jannesari (NAACL (Long Papers), 2025)

The kernel of graph indices for vector search. - Mariano Tepper; Ted Willke (CoRR, 2025)