Code in the air: simplifying sensing on smartphones. - Tim Kaler; John Patrick Lynch; Timothy Peng; Lenin Ravindranath; Arvind Thiagarajan; Hari Balakrishnan; Samuel Madden 001 (SenSys, 2010)

Ordering heuristics for parallel graph coloring. - William Hasenplaugh; Tim Kaler; Tao B. Schardl; Charles E. Leiserson (SPAA, 2014)

Polylogarithmic Fully Retroactive Priority Queues via Hierarchical Checkpointing. - Erik D. Demaine; Tim Kaler; Quanquan C. Liu; Aaron Sidford; Adam Yedidia (WADS, 2015)

Executing Dynamic Data-Graph Computations Deterministically Using Chromatic Scheduling. - Tim Kaler; William Hasenplaugh; Tao B. Schardl; Charles E. Leiserson (ACM Trans. Parallel Comput., 2016)

A Multicore Path to Connectomics-on-Demand. - Alexander Matveev; Yaron Meirovitch; Hayk Saribekyan; Wiktor Jakubiuk; Tim Kaler; Gergely Ódor; David M. Budden; Aleksandar Zlateski; Nir Shavit (PPoPP, 2017)

Optimal Reissue Policies for Reducing Tail Latency. - Tim Kaler; Yuxiong He; Sameh Elnikety (SPAA, 2017)

Scalable Graph Learning for Anti-Money Laundering: A First Look. - Mark Weber; Jie Chen 007; Toyotaro Suzumura; Aldo Pareja; Tengfei Ma 001; Hiroki Kanezashi; Tim Kaler; Charles E. Leiserson; Tao B. Schardl (CoRR, 2018)

High-throughput image alignment for connectomics using frugal snap judgments: poster. - Tim Kaler; Brian Wheatman; Sarah Wooders (PPoPP, 2019)

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. - Aldo Pareja; Giacomo Domeniconi; Jie Chen 007; Tengfei Ma 001; Toyotaro Suzumura; Hiroki Kanezashi; Tim Kaler; Charles E. Leiserson (CoRR, 2019)

EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. - Aldo Pareja; Giacomo Domeniconi; Jie Chen 007; Tengfei Ma 001; Toyotaro Suzumura; Hiroki Kanezashi; Tim Kaler; Tao B. Schardl; Charles E. Leiserson (AAAI, 2020)

Cilkmem: Algorithms for Analyzing the Memory High-Water Mark of Fork-Join Parallel Programs. - Tim Kaler; William Kuszmaul; Tao B. Schardl; Daniele Vettorel (APOCS, 2020)

High-Throughput Image Alignment for Connectomics using Frugal Snap Judgments. - Tim Kaler; Brian Wheatman; Sarah Wooders (HPEC, 2020)

PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation. - Tim Kaler; Tao B. Schardl; Brian Xie; Charles E. Leiserson; Jie Chen 007; Aldo Pareja; Georgios Kollias (APOCS, 2021)

Ordering Heuristics for Parallel Graph Coloring. - William Hasenplaugh; Tim Kaler; Tao B. Schardl; Charles E. Leiserson (Massive Graph Analytics, 2022)

Executing Dynamic Data-Graph Computations Deterministically Using Chromatic Scheduling. - Tim Kaler; William Hasenplaugh; Tao B. Schardl; Charles E. Leiserson (Massive Graph Analytics, 2022)

Accelerating Training and Inference of Graph Neural Networks with Fast Sampling and Pipelining. - Tim Kaler; Nickolas Stathas; Anne Ouyang; Alexandros-Stavros Iliopoulos; Tao B. Schardl; Charles E. Leiserson; Jie Chen 007 (MLSys, 2022)

Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching. - Tim Kaler; Alexandros-Stavros Iliopoulos; Philip Murzynowski; Tao B. Schardl; Charles E. Leiserson; Jie Chen 007 (MLSys, 2023)

Speedcode: Software Performance Engineering Education via the Coding of Didactic Exercises. - Tim Kaler; Xuhao Chen 001; Brian Wheatman; Dorothy Curtis; Bruce Hoppe; Tao B. Schardl; Charles E. Leiserson (IPDPS (Workshops), 2024)

The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset. - Claudio Bellei; Muhua Xu; Ross Phillips; Tom Robinson; Mark Weber; Tim Kaler; Charles E. Leiserson; Arvind 001; Jie Chen 007 (CoRR, 2024)

Lessons Learned: A Multi-Agent Framework for Code LLMs to Learn and Improve. - Yuanzhe Liu 001; Ryan Deng; Tim Kaler; Xuhao Chen 001; Charles E. Leiserson; Yao Ma; Jie Chen 007 (CoRR, 2025)