MAPS 2022 Contributors

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A Eddie AftandilianAftandilian, Eddie GitHubUnited States Productivity Assessment of Neural Code Completion
Farhana AleenAleen, Farhana NVIDIA Committee Member in Program Committee within the MAPS-track
Amin AlipourAlipour, Amin University of HoustonUnited States Syntax-Guided Program Reduction for Understanding Neural Code Intelligence Models
Uri AlonAlon, Uri Carnegie Mellon UniversityUnited States A Systematic Evaluation of Large Language Models of Code Committee Member in Program Committee within the MAPS-track
Jordi Armengol-EstapéArmengol-Estapé, Jordi University of Edinburgh ExeBench: An ML-scale dataset of executable C functions
B Osbert BastaniBastani, Osbert University of PennsylvaniaUnited States Committee Member in Program Committee within the MAPS-track
Alexander BrauckmannBrauckmann, Alexander University of Edinburgh ExeBench: An ML-scale dataset of executable C functions
C Satish ChandraChandra, Satish FacebookUnited States Session Chair of Morning II (part of MAPS) Predictive Synthesis of API-Centric Code Committee Member in Program Committee within the MAPS-track
Swarat ChaudhuriChaudhuri, Swarat University of Texas at AustinUnited States Session Chair of Evening (part of MAPS) General Chair in Organizing Committee within the MAPS-track
Xinyun ChenChen, Xinyun Committee Member in Program Committee within the MAPS-track
D Julian DolbyDolby, Julian IBM Research, USA Automatically Debugging AutoML Pipelines Using Maro: ML Automated Remediation Oracle
E Kevin EllisEllis, Kevin Cornell UniversityUnited States Unsupervised Program Synthesis: Hierarchy and Perception From Perception to Programs: Regularize, Overparameterize, and Amortize
G Justin GottschlichGottschlich, Justin Merly, Inc. / University of PennsylvaniaUnited States Committee Member in Organizing Committee within the MAPS-track
Vinod GroverGrover, Vinod NVIDIAUnited States Committee Member in Program Committee within the MAPS-track
H James HegartyHegarty, James Facebook A Graph Neural Network-based performance model for Deep Learning Applications
Vincent J. HellendoornHellendoorn, Vincent J. Carnegie Mellon UniversityUnited States A Systematic Evaluation of Large Language Models of Code Committee Member in Program Committee within the MAPS-track
Martin HirzelHirzel, Martin IBM ResearchUnited States Automatically Debugging AutoML Pipelines Using Maro: ML Automated Remediation Oracle
Aftab HussainHussain, Aftab University of HoustonUnited States Syntax-Guided Program Reduction for Understanding Neural Code Intelligence Models
I Jeevana Priya InalaInala, Jeevana Priya MITUnited States Committee Member in Program Committee within the MAPS-track
K Łukasz KaiserKaiser, Łukasz OpenAI Can Transformers Code?
Eirini KalliamvakouKalliamvakou, Eirini GitHub Productivity Assessment of Neural Code Completion
Aditya KanadeKanade, Aditya Indian Institute of Science, Bangalore Committee Member in Program Committee within the MAPS-track
Seohyun KimKim, Seohyun MetaUnited States Predictive Synthesis of API-Centric Code
L Hugh LeatherLeather, Hugh University of Edinburgh, UK A Graph Neural Network-based performance model for Deep Learning Applications
X. Alice LiLi, X. Alice GitHub Productivity Assessment of Neural Code Completion
Yujia LiLi, Yujia Deepmind Competitive Programming with AlphaCode
M José Wesley de Souza MagalhãesMagalhães, José Wesley de Souza University of Edinburgh ExeBench: An ML-scale dataset of executable C functions
N Daye NamNam, Daye CMU, Carnegie Mellon University Predictive Synthesis of API-Centric Code
Graham NeubigNeubig, Graham Carnegie Mellon University A Systematic Evaluation of Large Language Models of Code
O Michael F. P. O'BoyleO'Boyle, Michael F. P. University of EdinburghUnited Kingdom ExeBench: An ML-scale dataset of executable C functions
Q xianshan ququ, xianshan Predictive Synthesis of API-Centric Code
R Md Rafiqul Islam RabinRabin, Md Rafiqul Islam University of HoustonUnited States Syntax-Guided Program Reduction for Understanding Neural Code Intelligence Models
Baishakhi RayRay, Baishakhi Columbia UniversityUnited States Predictive Synthesis of API-Centric Code Improving Software Reliability using Machine Learning Committee Member in Program Committee within the MAPS-track
Andrew RiceRice, Andrew GitHub Productivity Assessment of Neural Code Completion
Devon RifkinRifkin, Devon GitHub Productivity Assessment of Neural Code Completion
S Xujie SiSi, Xujie McGill University, Canada Committee Member in Program Committee within the MAPS-track
Shawn SimisterSimister, Shawn GitHub Productivity Assessment of Neural Code Completion
Rishabh SinghSingh, Rishabh Google BrainUnited States Committee Member in Program Committee within the MAPS-track
Shikhar SinghSingh, Shikhar University of Texas A Graph Neural Network-based performance model for Deep Learning Applications
Ganesh SittampalamSittampalam, Ganesh GitHub Productivity Assessment of Neural Code Completion
Benoit SteinerSteiner, Benoit Facebook A Graph Neural Network-based performance model for Deep Learning Applications
Charles SuttonSutton, Charles Google ResearchUnited States Session Chair of Afternoon (part of MAPS) Session Chair of Morning I (part of MAPS) Committee Member in Organizing Committee within the MAPS-track Committee Member in Organizing Committee within the MAPS-track
T Earl T. BarrT. Barr, Earl University College London Committee Member in Program Committee within the MAPS-track
Hao TangTang, Hao Cornell University From Perception to Programs: Regularize, Overparameterize, and Amortize
Jesmin Jahan TithiTithi, Jesmin Jahan Intel Corporation, ACM-Selects, ACM-COPE, Stony Brook University, USAUnited States Committee Member in Organizing Committee within the MAPS-track
Jason TsayTsay, Jason IBM ResearchUnited States Automatically Debugging AutoML Pipelines Using Maro: ML Automated Remediation Oracle
W Abdul WasayWasay, Abdul Intel Labs and UCSDUnited States Committee Member in Program Committee within the MAPS-track
Jackson WoodruffWoodruff, Jackson University of Edinburgh ExeBench: An ML-scale dataset of executable C functions
X Frank F. XuXu, Frank F. Carnegie Mellon University A Systematic Evaluation of Large Language Models of Code
Z Albert ZieglerZiegler, Albert GitHub Productivity Assessment of Neural Code Completion