The Potential of Synergistic Static, Dynamic and Speculative Loop Nest Optimizations for Automatic Parallelization - Riyadh Baghdadi; Albert Cohen 001; Cédric Bastoul; Louis-Noël Pouchet; Lawrence Rauchwerger (CoRR, 2011)

PENCIL: Towards a Platform-Neutral Compute Intermediate Language for DSLs - Riyadh Baghdadi; Albert Cohen 001; Serge Guelton; Sven Verdoolaege; Jun Inoue 001; Tobias Grosser; Georgia Kouveli; Alexey Kravets; Anton Lokhmotov; Cedric Nugteren; Fraser Waters; Alastair F. Donaldson (CoRR, 2013)

Improved loop tiling based on the removal of spurious false dependences. - Riyadh Baghdadi; Albert Cohen 001; Sven Verdoolaege; Konrad Trifunovic (ACM Trans. Archit. Code Optim., 2013)

VOBLA: a vehicle for optimized basic linear algebra. - Ulysse Beaugnon; Alexey Kravets; Sven van Haastregt; Riyadh Baghdadi; David Tweed; Javed Absar; Anton Lokhmotov (LCTES, 2014)

PENCIL: A Platform-Neutral Compute Intermediate Language for Accelerator Programming. - Riyadh Baghdadi; Ulysse Beaugnon; Albert Cohen 001; Tobias Grosser; Michael Kruse; Chandan Reddy 001; Sven Verdoolaege; Adam Betts; Alastair F. Donaldson; Jeroen Ketema; Javed Absar; Sven van Haastregt; et al. (PACT, 2015)

Improving tiling, reducing compilation time, and extending the scope of polyhedral compilation. (Amélioration du tuilage, réduction du temps de compilation, et extension de l'utilisabilité de la compilation polyédrique). - Mohamed Riyadh Baghdadi (2015)

A Common Backend for Hardware Acceleration on FPGA. - Emanuele Del Sozzo; Riyadh Baghdadi; Saman P. Amarasinghe; Marco D. Santambrogio (ICCD, 2017)

A Unified Backend for Targeting FPGAs from DSLs. - Emanuele Del Sozzo; Riyadh Baghdadi; Saman P. Amarasinghe; Marco D. Santambrogio (ASAP, 2018)

GraphIt - A High-Performance DSL for Graph Analytics. - Yunming Zhang; Mengjiao Yang 001; Riyadh Baghdadi; Shoaib Kamil 001; Julian Shun; Saman P. Amarasinghe (CoRR, 2018)

GraphIt: a high-performance graph DSL. - Yunming Zhang; Mengjiao Yang 001; Riyadh Baghdadi; Shoaib Kamil 001; Julian Shun; Saman P. Amarasinghe (Proc. ACM Program. Lang., 2018)

Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code. - Riyadh Baghdadi; Jessica Ray; Malek Ben Romdhane; Emanuele Del Sozzo; Abdurrahman Akkas; Yunming Zhang; Patricia Suriana; Shoaib Kamil 001; Saman P. Amarasinghe (CGO, 2019)

Seq: a high-performance language for bioinformatics. - Ariya Shajii; Ibrahim Numanagic; Riyadh Baghdadi; Bonnie Berger; Saman P. Amarasinghe (Proc. ACM Program. Lang., 2019)

Learning to optimize halide with tree search and random programs. - Andrew Adams; Karima Ma; Luke Anderson 001; Riyadh Baghdadi; Tzu-Mao Li; Michaël Gharbi; Benoit Steiner; Steven Johnson; Kayvon Fatahalian; Frédo Durand; Jonathan Ragan-Kelley (ACM Trans. Graph., 2019)

Seq (OOPSLA 2019 Artifact). - Ariya Shajii; Ibrahim Numanagic; Riyadh Baghdadi; Bonnie Berger; Saman P. Amarasinghe (Zenodo, 2019)

SALSA: A Domain Specific Architecture for Sequence Alignment. - Lorenzo Di Tucci; Riyadh Baghdadi; Saman P. Amarasinghe; Marco D. Santambrogio (IPDPS Workshops, 2020)

TIRAMISU: A Polyhedral Compiler for Dense and Sparse Deep Learning. - Riyadh Baghdadi; Abdelkader Nadir Debbagh; Kamel Abdous; Fatima-Zohra Benhamida; Alex Renda; Jonathan Elliott Frankle; Michael Carbin; Saman P. Amarasinghe (CoRR, 2020)

A Deep Learning Based Cost Model for Automatic Code Optimization. - Riyadh Baghdadi; Massinissa Merouani; Mohamed-Hicham Leghettas; Kamel Abdous; Taha Arbaoui; Karima Benatchba; Saman P. Amarasinghe (MLSys, 2021)

Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights. - Shail Dave; Riyadh Baghdadi; Tony Nowatzki; Sasikanth Avancha; Aviral Shrivastava; Baoxin Li (Proc. IEEE, 2021)

Q-gym: An Equality Saturation Framework for DNN Inference Exploiting Weight Repetition. - Cheng Fu 002; Hanxian Huang; Bram Wasti; Chris Cummins; Riyadh Baghdadi; Kim M. Hazelwood; Yuandong Tian; Jishen Zhao; Hugh Leather (PACT, 2022)

Caviar: an e-graph based TRS for automatic code optimization. - Smail Kourta; Adel Abderahmane Namani; Fatima Benbouzid-Si Tayeb; Kim M. Hazelwood; Chris Cummins; Hugh Leather; Riyadh Baghdadi (CC, 2022)

An Integrated Artificial Bee Colony Algorithm for Scheduling Jobs and Flexible Maintenance with Learning and Deteriorating Effects. - Nesrine Touafek; Fatima Benbouzid-Si Tayeb; Asma Ladj; Alaeddine Dahamni; Riyadh Baghdadi (ICCCI, 2022)

Permutation Flowshop Scheduling Problem Considering Learning, Deteriorating Effects and Flexible Maintenance. - Nesrine Touafek; Asma Ladj; Fatima Benbouzid-Si Tayeb; Alaeddine Dahamni; Riyadh Baghdadi (KES, 2022)

Progress Report: A Deep Learning Guided Exploration of Affine Unimodular Loop Transformations. - Massinissa Merouani; Khaled Afif Boudaoud; Iheb Nassim Aouadj; Nassim Tchoulak; Fatima Benbouzid-Sitayeb; Karima Benatchba; Hugh Leather; Riyadh Baghdadi (CoRR, 2022)

A Deep Learning Model for Loop Interchange. - Lina Mezdour; Khadidja Kadem; Massinissa Merouani; Amina Selma Haichour; Saman P. Amarasinghe; Riyadh Baghdadi (CC, 2023)

Perception, performance, and detectability of conversational artificial intelligence across 32 university courses. - Hazem Ibrahim; Fengyuan Liu; Rohail Asim; Balaraju Battu; Sidahmed Benabderrahmane; Bashar Alhafni; Wifag Adnan; Tuka Alhanai; Bedoor K. AlShebli; Riyadh Baghdadi; Jocelyn J. Bélanger; Elena Beretta; et al. (CoRR, 2023)

A Deep Learning Model for Loop Interchange: Paper Artifact. - Lina Mezdour; Khadidja Kadem; Massinissa Merouani; Amina Selma Haichour; Saman P. Amarasinghe; Riyadh Baghdadi (Zenodo, 2023)

A Hybrid Machine Learning Model for Code Optimization. - Yacine Hakimi; Riyadh Baghdadi; Yacine Challal (Int. J. Parallel Program., 2023)

Curriculum Learning for Small Code Language Models. - Marwa Naïr; Kamel Mohammed Yamani; Lynda Said L'Hadj; Riyadh Baghdadi (ACL (Student Research Workshop), 2024)

Exploring the Knowledge Mismatch Hypothesis: Hallucination Propensity in Small Models Fine-tuned on Data from Larger Models. - Phil Wee; Riyadh Baghdadi (BDCAT, 2024)

Zero-shot Object Navigation with Vision-Language Foundation Models Reasoning. - Shuaihang Yuan; Muhammad Shafique 001; Mohamed Riyadh Baghdadi; Farshad Khorrami; Anthony Tzes; Yi Fang 006 (ICARA, 2024)

SPACED: A Novel Deep Learning Method for Community Detection in Social Networks. - Mohammed Tirichine; Nassim Ameur; Younes Boukacem; Hatem M. Abdelmoumen; Hodhaifa Benouaklil; Samy Ghebache; Boualem Hamroune; Malika Bessedik; Fatima Benbouzid-Si Tayeb; Riyadh Baghdadi (WEBIST, 2024)

Automatic Generation of Python Programs Using Context-Free Grammars. - Kamel Mohammed Yamani; Marwa Nair; Riyadh Baghdadi (CoRR, 2024)

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers. - Massinissa Merouani; Khaled Afif Boudaoud; Iheb Nassim Aouadj; Nassim Tchoulak; Islem Kara Bernou; Hamza Benyamina; Fatima Benbouzid-Si Tayeb; Karima Benatchba; Hugh Leather; Riyadh Baghdadi (CoRR, 2024)

Combining Neural Architecture Search and Automatic Code Optimization: A Survey. - Inas Bachiri; Hadjer Benmeziane; Smaïl Niar; Riyadh Baghdadi; Hamza Ouarnoughi; Abdelkrime Aries (CoRR, 2024)

A Reinforcement Learning Environment for Automatic Code Optimization in the MLIR Compiler. - Nazim Bendib; Iheb Nassim Aouadj; Riyadh Baghdadi (CoRR, 2024)

Data-Efficient Performance Modeling via Pre-training. - Chunting Liu; Riyadh Baghdadi (CC, 2025)

Leveraging High-Resolution Features for Improved Deep Hashing-Based Image Retrieval. - Aymene Berriche; Mehdi Zakaria Adjal; Riyadh Baghdadi (ECIR (2), 2025)

Sign-Symmetry Learning Rules are Robust Fine-Tuners. - Aymene Berriche; Mehdi Zakaria Adjal; Riyadh Baghdadi (CoRR, 2025)

Pearl: Automatic Code Optimization Using Deep Reinforcement Learning. - Djamel Rassem Lamouri; Iheb Nassim Aouadj; Smail Kourta; Riyadh Baghdadi (CoRR, 2025)

Supporting Dynamic Program Sizes in Deep Learning-Based Cost Models for Code Optimization. - Yacine Hakimi; Riyadh Baghdadi; Yacine Challal (ACM Trans. Archit. Code Optim., 2025)

Neural Architecture Search with Mixed Bio-inspired Learning Rules. - Imane Hamzaoui; Riyadh Baghdadi (CoRR, 2025)