Armin Saghafian

Data Scientist

https://talent.gravityer.com/armin-saghafian

Member since June 28, 2026

Key Strengths

Demonstrated strong interest and practical experience in various aspects of Deep Learning and Machine Learning through personal projects.
Experience with Python, a core language for Data Science.
Exposure to advanced topics like Text-to-Image evaluation, Reinforcement Learning (MAPPO, GAIL, AIRL), and Graph Classification.
Participation in an ECCV 2024 Workshop, indicating engagement with cutting-edge research.

Cultural & Operational Fit

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Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

graph-classification-robustness-EECE-571F

February 21, 2026 – Present

Course project for Advanced Topics in Deep Learning 571F

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T2I-FineEval

March 9, 2025 – May 10, 2025

[ECCV 2024 Workshop EVAL-FoMo] T2I-FineEval: Fine-Grained Compositional Metric for Text-to-Image Evaluation

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noise-refinement

March 8, 2025 – March 9, 2025

noise-refinement — GitHub repository

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MA-GAIL-AIRL-pytorch

October 3, 2024 – May 4, 2025

An implementation of CAREL framework on Babyai and Semantic HELM.

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CAREL

October 1, 2024 – October 7, 2024

An implementation of CAREL framework on Babyai and Semantic HELM.

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CE418-SAD

February 29, 2024 – January 21, 2025

Solutions to Dr. Habibi's CE418: Systems Analysis and Design (Sharif University of Technology - Spring 2024) Assignments

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MGAIL_Original

August 10, 2023 – October 3, 2024

MGAIL_Original — GitHub repository

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MAPPO-Attention

June 13, 2023 – Present

MAPPO-Attention — GitHub repository

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MNIST-digit-Classification

April 16, 2023 – April 16, 2023

I used a residual neural network (ResNet) to classify handwritten digits in MNIST dataset.

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Image-Captioning-LSTM

March 30, 2023 – March 30, 2023

I made an image captioning model using LSTM and encoder-decoder architecture on the Flickr8k dataset.

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Key Strengths

Demonstrated strong interest and practical experience in various aspects of Deep Learning and Machine Learning through personal projects.
Experience with Python, a core language for Data Science.
Exposure to advanced topics like Text-to-Image evaluation, Reinforcement Learning (MAPPO, GAIL, AIRL), and Graph Classification.
Participation in an ECCV 2024 Workshop, indicating engagement with cutting-edge research.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily academic or personal research-oriented, focusing on advanced ML/DL topics. This indicates a strong drive for learning and exploration, which could be a good cultural fit for a research-heavy or innovative team. However, the lack of team projects or professional experience makes it difficult to assess collaboration or broader organizational fit. The projects align well with a Data Scientist role, particularly one focused on research or advanced model development.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback are available.

Armin Saghafian

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit