Welcome

Sarp Aykent.

Senior Applied Scientist at Microsoft

My primary research is in natural language processing and AI; I also explore geometric deep learning and 3D equivariant graph neural networks for molecular science. I received my Ph.D. from the Department of Computer Science and Software Engineering at Auburn University.

Recent Publications

Image for GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks

GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks

Sarp Aykent, Tian Xia

The Thirteenth International Conference on Learning Representations (ICLR 2025)

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APA

Aykent, S., & Xia, T. (2025). GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks. The Thirteenth International Conference on Learning Representations. https://openreview.net/forum?id=5wxCQDtbMo
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Vancouver

Aykent S, Xia T. GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks. In: The Thirteenth International Conference on Learning Representations [Internet]. 2025. Available from: https://openreview.net/forum?id=5wxCQDtbMo
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Aykent, S. and Xia, T. (2025) “GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks,” The Thirteenth International Conference on Learning Representations. Available at: https://openreview.net/forum?id=5wxCQDtbMo.
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MLA

Aykent, Sarp, and Tian Xia. “GotenNet: Rethinking Efficient 3D Equivariant Graph Neural Networks.” The Thirteenth International Conference on Learning Representations, 2025, https://openreview.net/forum?id=5wxCQDtbMo.
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Image for SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning

SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning

Sarp Aykent, Tian Xia

Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)

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APA

Aykent, S., & Xia, T. (2023). SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning. Thirty-Seventh Conference on Neural Information Processing Systems.
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Vancouver

Aykent S, Xia T. SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning. In: Thirty-seventh Conference on Neural Information Processing Systems. 2023.
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Harvard

Aykent, S. and Xia, T. (2023) “SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning,” Thirty-seventh Conference on Neural Information Processing Systems.
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MLA

Aykent, Sarp, and Tian Xia. “SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning.” Thirty-Seventh Conference on Neural Information Processing Systems, 2023.
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Image for GBPnet

GBPNet: Universal Geometric Representation Learning on Protein Structures

Sarp Aykent, Tian Xia

Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD 2022)

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APA

Aykent, S., & Xia, T. (2022). GBPNet: Universal Geometric Representation Learning on Protein Structures. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, KDD ’22.
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Vancouver

Aykent S, Xia T. GBPNet: Universal Geometric Representation Learning on Protein Structures. In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. Washington, DC, USA: Association for Computing Machinery; 2022. (KDD ’22).
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Aykent, S. and Xia, T. (2022) “GBPNet: Universal Geometric Representation Learning on Protein Structures,” Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. Washington, DC, USA: Association for Computing Machinery (KDD ’22).
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MLA

Aykent, Sarp, and Tian Xia. “GBPNet: Universal Geometric Representation Learning on Protein Structures.” Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining [Washington, DC, USA], KDD ’22, 2022.
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