Noor Shaker | Academic Influence

Noor Shaker's AcademicInfluence.com Rankings

Noor Shaker

Computer Science

#12342

World Rank

#13178

Historical Rank

Machine Learning

#5823

World Rank

#5910

Historical Rank

Artificial Intelligence

#6265

World Rank

#6369

Historical Rank

Database

#9842

World Rank

#10429

Historical Rank

computer-science Degrees

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Computer Science

Noor Shaker's Degrees

PhD Computer Science University of Copenhagen

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Best Online PhD of Computer Science (Doctorates) 2025

Why Is Noor Shaker Influential?

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According to Wikipedia, Noor Shaker is a Syrian British entrepreneur and computer scientist who co-founded the AI for drug discovery start-up Glamorous AI. Glamorous AI was acquired by the US-based company X-Chem in Nov 2021. Before Glamorous AI, Noor founded the drug discovery start-up GTN Ltd and served as CEO for more than two years. She stepped down as CEO in August 2019. The company entered liquidation in March 2020. In 2018, she received a CogX UK Rising Star Award from Prime Minister Theresa May for "AI technology that will transform drug discovery to treat chronic diseases".

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Noor Shaker's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Procedural Content Generation in Games (2016) (337)
Towards Automatic Personalized Content Generation for Platform Games (2010) (241)
The 2010 Mario AI Championship: Level Generation Track (2011) (142)
Evolving levels for Super Mario Bros using grammatical evolution (2012) (115)
Imitating human playing styles in Super Mario Bros (2013) (98)
Fusing Visual and Behavioral Cues for Modeling User Experience in Games (2013) (78)
Ropossum: An Authoring Tool for Designing, Optimizing and Solving Cut the Rope Levels (2013) (77)
A comparative evaluation of procedural level generators in the Mario AI framework (2014) (72)
The Mario AI Championship 2009-2012 (2013) (69)
Crowdsourcing the Aesthetics of Platform Games (2013) (69)
Constructive generation methods for dungeons and levels (2016) (65)
Evolving Playable Content for Cut the Rope through a Simulation-Based Approach (2013) (60)
Mixed-initiative content creation (2016) (55)
Evolving Personalized Content for Super Mario Bros Using Grammatical Evolution (2012) (50)
A Game-Based Corpus for Analysing the Interplay between Game Context and Player Experience (2011) (50)
Automatic generation and analysis of physics-based puzzle games (2013) (47)
Assessing Believability (2012) (41)
The turing test track of the 2012 Mario AI Championship: Entries and evaluation (2013) (37)
Feature analysis for modeling game content quality (2011) (33)
The platformer experience dataset (2015) (32)
The search-based approach (2016) (29)
Grammars and L-systems with applications to vegetation and levels (2016) (28)
The Mario AI Championship (2010) (27)
SMUG: Scientific Music Generator (2015) (26)
Digging Deeper into Platform Game Level Design: Session Size and Sequential Features (2012) (26)
Towards player’s affective and behavioral visual cues as drives to game adaptation (2012) (22)
Alone We Can Do So Little, Together We Can Do So Much: A Combinatorial Approach for Generating Game Content (2014) (21)
Evaluating content generators (2016) (21)
Towards Generic Models of Player Experience (2015) (20)
Towards player-driven procedural content generation (2012) (19)
Towards Detecting Clusters of Players using Visual and Gameplay Behavioral Cues (2012) (18)
A Procedural Method for Automatic Generation of Spelunky Levels (2015) (11)
Transfer learning for cross-game prediction of player experience (2016) (11)
A Progressive Approach to Content Generation (2015) (10)
Towards Understanding the Nonverbal Signatures of Engagement in Super Mario Bros (2014) (10)
Fractals, noise and agents with applications to landscapes (2016) (9)
A Quantitative Approach for Modelling and Personalizing Player Experience in First-Person Shooter Games (2013) (8)
The experience-driven perspective (2016) (8)
Intrinsically motivated reinforcement learning: A promising framework for procedural content generation (2016) (8)
Evolving Random Forest for Preference Learning (2015) (8)
Active player modelling (2013) (8)
Preference learning with evolutionary Multivariate Adaptive Regression Spline model (2015) (6)
Does your profile say it all? Using demographics to predict expressive head movement during gameplay (2012) (6)
Active Learning for Player Modeling (2015) (5)
Multimodal Corpora : How should multimodal corpora deal with the situation ? (4)
A Generative Deep Learning Approach for the Discovery of SARS CoV2 Protease Inhibitors (2020) (4)
SSML for Arabic Language (2008) (3)
A Projection-Based Approach for Real-Time Assessment and Playability Check for Physics-Based Games (2015) (3)
A Novel Machine Learning Approach Uncovers New and Distinctive Inhibitors for Cyclin-Dependent Kinase 9 (2020) (3)
Chapter 3 Constructive generation methods for dungeons and levels (2015) (3)
Sparse hierarchical representation learning on molecular graphs (2019) (1)
Aalborg Universitet A Progressive Approach to Content Generation (2015) (1)
Chapter 11 Mixed-initiative content creation (2016) (1)
The Platformer Experience Dataset CONFERENCE (2015) (0)
Aalborg Universitet Evolving Random Forest for Preference Learning (2015) (0)
ROCEEDINGS OF THE TENTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INTERACTIVE DIGITAL ENTERTAINMENT (AIIDE-14) (2014) (0)
Assessment of the prevalence of Pseudomonas aeruginosa among Iraqi patients with acne and study of their antibiotic susceptibility patterns (2022) (0)
PaTux: An Authoring Tool for Level Design through Pattern Customisation Using Non-Negative Matrix Factorization (2014) (0)
Chapter 1 Assessing Believability (2011) (0)
Chapter 10 The experience-driven perspective (2016) (0)
TENSOR NETWORK MACHINE LEARNING SYSTEM (2018) (0)
Chapter 12 Evaluating content generators (2016) (0)

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What Schools Are Affiliated With Noor Shaker?

Noor Shaker is affiliated with the following schools:

What Are Noor Shaker's Academic Contributions?

Noor Shaker is most known for their academic work in the field of computer science. They are also known for their academic work in the fields of

Noor Shaker has made the following academic contributions:

Procedural Content Generation in Games