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Posts
Building Blocks for Deep Learning: Crafting an MLP with Triton
Published:
In our previous post, we dipped our toes into the world of Triton by writing simple custom kernels. We learned how to add a scalar to a tensor and perform element-wise multiplication, understanding the fundamental concepts of launching kernels and managing GPU memory. Read more
Building Blocks for Deep Learning: Your First Custom Kernel with Triton
Published:
So, you’ve heard the buzz about OpenAI’s Triton and its ability to let you craft custom GPU kernels? Maybe you’re facing performance bottlenecks with standard deep learning operations, or perhaps you have a unique algorithm that existing libraries don’t quite cover. Whatever your reason, you’re in the right place! This winter break, I decided to dive into the fascinating world of high-performance GPU programming, and one of the most exciting tools I’ve discovered is Triton. Read more
portfolio
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publications
Syntax-Guided Transformers: Elevating Compositional Generalization and Grounding in Multimodal Environments
The Conference on Empirical Methods in Natural Language Processing Genbench Workshop (EMNLP), 2023
In this work, we proposed the syntax guided transformer to improve the compositional generalization in grounding. Read more
Recommended citation: Kamali, Danial, and Parisa Kordjamshidi. "Syntax-Guided Transformers: Elevating Compositional Generalization and Grounding in Multimodal Environments." GenBench: The first workshop on generalisation (benchmarking) in NLP. 2023. https://aclanthology.org/2023.genbench-1.10.pdf
@inproceedings{kamali2023syntax \n ,title={Syntax-Guided Transformers: Elevating Compositional Generalization and Grounding in Multimodal Environments} \n,author={Kamali, Danial and Kordjamshidi, Parisa} \n,booktitle={GenBench: The first workshop on generalisation (benchmarking) in NLP}\n,pages={130}\n,year={2023}\n}
Using Persuasive Writing Strategies to Explain and Detect Health Misinformation
Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), 2024
In this work we introduce a persuasive strategy detection dataset and show using their labels can improve misinformation detection and explanation. Read more
Recommended citation: Kamali, D., Romain, J., Liu, H., Peng, W., Meng, J., & Kordjamshidi, P. (2023). Using Persuasive Writing Strategies to Explain and Detect Health Misinformation. arXiv preprint arXiv:2211.05985. https://aclanthology.org/2024.lrec-main.1501.pdf
@inproceedings{kamali-etal-2024-using, title = "Using Persuasive Writing Strategies to Explain and Detect Health Misinformation", author = "Kamali, Danial and Romain, Joseph D. and Liu, Huiyi and Peng, Wei and Meng, Jingbo and Kordjamshidi, Parisa", editor = "Calzolari, Nicoletta and Kan, Min-Yen and Hoste, Veronique and Lenci, Alessandro and Sakti, Sakriani and Xue, Nianwen", booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)", month = may, year = "2024", address = "Torino, Italia", publisher = "ELRA and ICCL", url = "https://aclanthology.org/2024.lrec-main.1501", pages = "17285--17309", }
NeSyCoCo: A Neuro-Symbolic Concept Composer for Compositional Generalization
Association for the Advancement of Artificial Intelligence (AAAI), 2025
Abstract
NeSyCoCo is a neuro-symbolic visual reasoning framework that tackles generalization in vision-language tasks and more specially compositional generalization. Read more
@article{Kamali_Barezi_Kordjamshidi_2025, title={NeSyCoCo: A Neuro-Symbolic Concept Composer for Compositional Generalization}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/32439}, DOI={10.1609/aaai.v39i4.32439}, number={4}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Kamali, Danial and Barezi, Elham J. and Kordjamshidi, Parisa}, year={2025}, month={Apr.}, pages={4184-4193} }
NePTune: A Neuro-Pythonic Framework for Tunable Compositional Reasoning on Vision-Language
International Conference on Learning Representations (ICLR), 2026
NePTune translates a question into a Python program that combines imperative control flow with soft logic over scores from a vision-language model, and runs it without training. Read more
@inproceedings{kamali2026neptune, title={Ne{PT}une: A Neuro-Pythonic Framework for Tunable Compositional Reasoning on Vision-Language}, author={Danial Kamali and Parisa Kordjamshidi}, booktitle={The Fourteenth International Conference on Learning Representations}, year={2026}, url={https://openreview.net/forum?id=8H0TkSusWI} }
SATURN: Symbolic Spatial Reasoning for Multi-Perspective Grounding
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2026
SATURN answers frame-of-reference questions by running a short program of soft spatial predicates over an estimated 3D scene, and we also release 3D FORCE, a diagnostic benchmark for composing spatial relations across perspectives. Read more
@misc{kamali2026saturnsymbolicspatialreasoning, title={SATURN: Symbolic Spatial Reasoning for Multi-Perspective Grounding}, author={Danial Kamali and Tanawan Premsri and Shreya Rajpal and Amir Zadeh and Chuan Li and Parisa Kordjamshidi}, year={2026}, eprint={2606.22694}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2606.22694}, }
talks
Talk 1 on Relevant Topic in Your Field
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown! Read more
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field. Read more
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post. Read more
