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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
portfolio
Jooyan
Published:
An online platform for coding practice, skill assessments, and technical interviews.
PyDebiaser
Published:
An open-source library for measuring and mitigating social biases in Transformer language models.
AstroAgents
Published:
A multi-agent AI system that generates scientific hypotheses from mass spectrometry data.
LifeTracer
Published:
Discriminating biotic from abiotic organics in meteorites using ML on mass spectrometry data.
cryoSENSE
Published:
Guided diffusion and compressive sensing for high-throughput cryo-EM image reconstruction.
ProtoMech
Published:
Discovering computational circuits in protein language models via cross-layer transcoders.
ASTRA
Published:
A multi-agent AI that autonomously reconstructs prebiotic reaction networks for the amino acids.
publications
Effective Data Augmentation Methods for Multi-label Classification Language Understanding Tasks
Published in Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval), 2022
Links: Paper (ACL Anthology)
Recommended citation: D. Saeedi, A. Panahi, S. Saeedi, A. Fong. (2022). "Effective Data Augmentation Methods for Multi-label Classification Language Understanding Tasks." Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval).
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AstroAgents: Agentic AI for Scientific Discovery
Published in ICLR 2025 Workshop on Agentic AI for Science / AMS 2025 (Oral Presentation), 2025
A multi-agent AI system that generates scientific hypotheses from mass spectrometry data.
Recommended citation: D. Saeedi, D. K. Buckner, J. C. Aponte, A. Aghazadeh. (2025). "AstroAgents: Agentic AI for Scientific Discovery." ICLR 2025 Workshop on Agentic AI for Science / AMS 2025 (Oral).
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Machine Learning Analysis of Mass Spectrometry Data Can Differentiate Organic Distributions in Meteoritic and Terrestrial Geologic Samples
Published in 56th Lunar and Planetary Science Conference (LPSC), Abstract 2729 (Oral Presentation), 2025
Links: Abstract (NASA NTRS, PDF)
Recommended citation: D. K. Buckner, D. Saeedi, T. Walton, J. C. Aponte, A. Aghazadeh. (2025). "Machine Learning Analysis of Mass Spectrometry Data Can Differentiate Organic Distributions in Meteoritic and Terrestrial Geologic Samples." 56th Lunar and Planetary Science Conference (LPSC), Abstract 2729.
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Challenges and Opportunities in Using Amino Acids to Decode Carbonaceous Chondrites and Asteroid Parent-Body Processes
Published in Astrobiology, 2025
Links: Paper (Astrobiology)
Recommended citation: J. C. Aponte, H. L. McLain, D. Saeedi, A. Aghazadeh, J. E. Elsila, D. P. Glavin, J. P. Dworkin. (2025). "Challenges and Opportunities in Using Amino Acids to Decode Carbonaceous Chondrites and Asteroid Parent-Body Processes." Astrobiology.
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GT-NLP at SemEval-2025 Task 11: EmoRationale — Evidence-Based Emotion Recognition via Retrieval-Augmented Generation
Published in Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), 2025
Links: Paper (ACL Anthology)
Recommended citation: D. Saeedi, A. Kheirandish, S. Saeedi, H. Sahour, A. A. Panahi, I. Naeeni. (2025). "GT-NLP at SemEval-2025 Task 11: EmoRationale, Evidence-Based Emotion Recognition via Retrieval-Augmented Generation." SemEval-2025.
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Discriminating Abiotic and Biotic Organics in Meteorite and Terrestrial Samples Using Machine Learning on Mass Spectrometry Data
Published in PNAS Nexus, 4(11), pgaf334, 2025
Machine learning on two-dimensional gas chromatography–mass spectrometry data distinguishes biotic from abiotic organics in meteorites and terrestrial samples.
Recommended citation: D. Saeedi, D. Buckner, T. Walton, J. C. Aponte, A. Aghazadeh. (2025). "Discriminating abiotic and biotic organics in meteorite and terrestrial samples using machine learning on mass spectrometry data." PNAS Nexus, 4(11), pgaf334.
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cryoSENSE: Compressive Sensing Enables High-throughput Microscopy with Sparse and Generative Priors on the Protein Cryo-EM Image Manifold
Published in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026
Generative priors on the cryo-EM image manifold enable higher-throughput microscopy via compressive sensing.
Recommended citation: D. Saeedi*, Z. Shabeeb*, D. Tsui*, V. Jamali, A. Aghazadeh. (2026). "cryoSENSE: Compressive Sensing Enables High-throughput Microscopy with Sparse and Generative Priors on the Protein Cryo-EM Image Manifold." IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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Protein Circuit Tracing via Cross-layer Transcoders
Published in International Conference on Machine Learning (ICML), 2026
Discovering computational circuits inside protein language models with cross-layer transcoders.
Recommended citation: D. Tsui, K. Talreja, D. Saeedi, A. Aghazadeh. (2026). "Protein Circuit Tracing via Cross-layer Transcoders." International Conference on Machine Learning (ICML).
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Circuit Tracing in Autoregressive Protein Language Models
Published in ICML 2026 Workshop on Mechanistic Interpretability, 2026
Links: Paper (arXiv)
Recommended citation: D. Tsui, W. Deinzer, D. Saeedi, A. Aghazadeh. (2026). "Circuit Tracing in Autoregressive Protein Language Models." ICML 2026 Workshop on Mechanistic Interpretability.
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ProtoMech: Protein Circuit Tracing via Cross-layer Transcoders
Published in ICML 2026 Workshop on Mechanistic Interpretability, 2026
Links: OpenReview
Recommended citation: D. Tsui, K. Talreja, D. Saeedi, A. Aghazadeh. (2026). "ProtoMech: Protein Circuit Tracing via Cross-layer Transcoders." ICML 2026 Workshop on Mechanistic Interpretability.
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Generative Priors for Cryo-EM Image Reconstruction
Published in ICML 2026 Workshop on Generative and Agentic AI for Biology (GenBio), 2026
* Equal contribution.
Recommended citation: D. Saeedi*, Z. Shabeeb*, D. Tsui*, V. Jamali, A. Aghazadeh. (2026). "Generative Priors for Cryo-EM Image Reconstruction." ICML 2026 Workshop on Generative and Agentic AI for Biology (GenBio).
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Autonomous Multi-Agent Reconstruction of Prebiotic Reaction Networks Reveals Organizational Features of Amino Acid Synthesis
Published in Preprint, 2026
ASTRA, a multi-agent AI system, reconstructs prebiotic reaction networks for the twenty canonical amino acids and reveals system-level organization in their synthesis.
Recommended citation: D. Saeedi, N. Pokhrel, L. Gao, C. Wen, E. Bruce, J. C. Aponte, A. Stockton, A. Aghazadeh. (2026). "Autonomous Multi-Agent Reconstruction of Prebiotic Reaction Networks Reveals Organizational Features of Amino Acid Synthesis." Preprint.