Masoud Mazloom is a distinguished expert in the fields of AI and data science, holding a Ph.D. in computer science and amassing over 20 years of hands-on experience in the industry. Throughout his career, Masoud has showcased his proficiency in leveraging machine learning models and data mining algorithms to extract valuable insights from image, video, and textual data. He has a strong track record of applying these techniques to tackle challenging business problems across various domains.

 

Masoud's career highlights include roles such as CEO at the Innovation Center for Data Science in Iran, where he focused on establishing and empowering the community and ecosystem of Industrialized AI and data science. He has also served as a researcher and lecturer at esteemed institutions like Ferdowsi University of Mashhad in Iran and the University of Amsterdam in the Netherlands. Notably, Masoud has made significant contributions to the field through his involvement in projects such as developing multimodal financial analytics, building receipt understanding pipelines, and creating Document2Graph models for automating processes at ABN AMRO Bank N.V.

 

In addition to his professional endeavors, Masoud has actively engaged in academia by teaching and supervising students in data science programs, presenting at conferences, and participating in research projects. He has a robust publication record with over 30 scientific papers to his name, accumulating more than 900 citations. Mazloom's expertise spans a wide range of technical skills, including programming languages like C++, Python, and tools such as PyTorch for neural networks and Elasticsearch for search engines.

 

Furthermore, Masoud has demonstrated strong soft skills, particularly in communication and team leadership. He has effectively supervised students at various academic levels, collaborated with interdisciplinary teams, and led data scientists to derive actionable insights from raw data. His ability to interpret and analyze complex data problems, visualize data effectively, and create insightful reports has been instrumental in driving successful outcomes in his projects.

 

 

Postdoctoral Scholar

Informatics Institute, University of Amsterdam, The Netherlands 2015 – 2018

Topic: Brand Centrality, Emotions and Virality in Social Media

 

Ph.D. in Computer Science

Informatics Institute, University of Amsterdam, The Netherlands 2011 – 2015

Thesis: In search of video event semantic

M.Sc. in Computer Science

Mathematics Department, Sharif University of Technology, Iran 2002 – 2005

Thesis: Human identification from face appearance

 

B.Sc. in Computer Engineering

Computer Department, University of Tehran, Iran 1996 - 2001