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Hello! I'm Saeed Amal

I'm a Postdoctoral at the Stanford University, i'm interested in the research  areas of Recommender systems, Deep learning, machine learning, Information Retrieval, Information Extraction, User Modeling, Human Computer Intection

Saeed Amal

Postdoctoral
Medicine School at Stanford University
Deep learning , Machine learning, Recommender systems, Information Retrieval, Information extraction and User modelling

Email:

Saed.amal@gmail.com 

 

Office:
Stanford University
Medicine School
Palo Alto
California
USA
EXPERIENCE
 
2020-Present

Data Scientist and NLP researcher

Dynamic Yield

2019-2020

Data Scientist and NLP researcher

2017-2019

Data Scientist and NLP researcher

2013-2016

VP R&D

2009-2013

Software engineer

2005-2009

Software engineer

General Electric ltd.

General Motors ltd.

Cardiacx Medical

Attunity Israel Ltd.

Amdocs Israel Ltd.

EDUCATION
 
2021-present

Postdoctoral

Stanford University

Recommender Systems, Deep learning, Machine learning, Information Retrieval, Information Extraction

2013-2019

PhD 

Haifa University

Machine learning, Information Retrieval, Information Extraction, User Modeling

2006-2009

M.Sc. Computer Science

Haifa University

Information Retrieval

2001-2005

B.Sc. Computer Sience

Technion - Israel Institute of Technology

Computer engineering

PUBLICATIONS
 
 

 

Journal papers:

  • Amal, S., Tsai, CH., Brusilovsky, P., Kuflik T. and Minkov, E. Relational Social Recommendation: Application to the Academic Domain. In Journal of Expert Systems with Applications. Volume 124. Pages 182-195. (2019).

 

  • Amal, S., Adam, M., Brusilovsky, P. and Minkov, E., Kuflik T. Persons Entities Profiling: Integrating and Visualizing Online Entity-related Information. (Will be submitted to JASIST in 2020).

Conference papers:

  • Amal, S., Kuflik T. and Minkov, E. Harvesting Entity-relation Social Networks from the Web: Potential and Challenges. In the Proceedings of the ACM Conference: the 25th User Modelling, Adaptation and Personalization (UMAP'17), Bratislava, Slovakia. Pages 351-352. (2017).

 

  • Amal, S., Adam M., Brusilovsky, P., Minkov, E. and Kuflik T. Visualizing Entity-Relation Profiles: Evaluation for Scholars. In Review for Proceedings of the ACM Conference: Advanced Visual Interfaces (AVI'20), Ischia, Italy (2020).

 Posters/Demos:

  • Amal, S., Adam M., Tsai, CH., Brusilovsky, P., Minkov, E. and Kuflik T. Enhancing Explainability of Social Recommendation Using 2D Graphs and Word Cloud Visualizations. In Companion Proceedings of the ACM Conference: the 24th ACM Conference on Intelligence User Interfaces (IUI'19), Los-Angeles, USA. Pages 21-22. (2019).

  • Amal, S., Adam M., Brusilovsky, P., Minkov, E. and Kuflik T. Demonstrating Personalized Multifaceted Visualization of People Recommendation to Conference Participants. In Companion Proceedings of the ACM Conference: the 28th User Modelling, Adaptation and Personalization (UMAP'20), Genoa, Italy. (2020).

Workshop papers:

  • Amal, S., Tsai, CH., Brusilovsky, P., Minkov, E., Kuflik T. Explainable Social Recommendation with Heterogeneous Entity-Based Network: Preliminary Results. In the Proceedings of the ACM IntRS workshop at RecSys Conference: the IntRS at the 12th ACM Conference on Recommender Systems (INTRS'18), Vancouver, Canada (2018).