Mohammadamin Shafiei


I'm currently enrolled as a first-year student in the M.Sc. program for Human-centered Artificial Intelligence at University of Milan . My experience encompasses a range of tools and resources in the field of artificial intelligence. Specifically, I have a strong interest in Graph Neural Networks, Natural Language Processing (NLP), Human-computer interaction(HCI), and LLMs. Furthermore, I'm fascinated by the convergence of AI and social sciences, including areas like Computational Social Science, Social Computing, Social Network Analysis, and Recommendation Systems. The study of bias and fairness in AI is also a captivating area of exploration for me.

Feel free to reach out to me via mail!

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Awards: In 2011, I graduated as top of my year from secondary school and received the e-fellows scholarship and was admitted to the Germany Mathematics Society and the German Physics Society. In 2017 I received the Dean's List Award for Academic Excellence for my Master's degree. During my PhD studies, I was a scholar of the International Max Planck Research School for Intelligent Systems (IMPRS-IS). Our research projects Occupancy Networks, DVR, and ConvOnet were selected to be among the 15 most influencial CVPR / ECCV papers of 2019 and 2020. In 2021, we received the CS teaching award for our computer vision lecture as well as the AIGameDev scientific award for our GRAF project and the CVPR Best Paper Award for GIRAFFE (news coverage).

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Experiences

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NLP applications in Psychology
Supervisor: Prof. Mohammad Atari | Sep. 2023 - Apr. 2024
Engaged in exploring NLP applications within the field of Psychology, including the development of computational psychological tools and the compilation of Persian psychological datasets.
University of Massachusetts Amherst

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Similarity measurement on Temporal Graph
Supervisor: Prof. Sadegh Aliakbari | Jun. 2022 - Feb. 2023
Proposed a model that predicts whether a graph is the next generation of another using Autoencoders and Siamese Networks.
Shahid Beheshti University

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Software Defect Prediction via Deep Learning
Supervisor: Prof. Mojtaba Vahidi-Asl | Sep. 2021 - Sep. 2022
Developed a Deep Learning method to determine whether a program is faulty or not using visualization and Deep Learning techniques.
Shahid Beheshti University

Education

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University of Milan
Human-centered Artificial Intelligence
Master of Science
Sep. 2023 - Present
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Shahid Beheshti University
Computer Engineering
Bachelor of Science
Sep. 2018 - Feb. 2023

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