Siddhartha Shakya

I am a Chief Researcher at the EBTIC Research Centre at Khalifa University, where I lead a team of researchers working on applications of Artificial Intelligence (AI) on Industrial problems. In addition to overseeing cutting-edge research, I mentor and supervise both undergraduate and postgraduate students at Khalifa University, fostering the next generation of AI innovators.

I hold an MSc in Intelligent Systems from the University of Sussex, UK (2002), and a PhD in Artificial Intelligence from Robert Gordon University, UK (2006). My expertise spans a broad spectrum of AI and machine learning, including big data analytics, evolutionary algorithms, computational optimization, Bayesian statistics, and probabilistic models. With extensive industrial research experience, I have successfully applied these techniques to high-impact business challenges across diverse sectors, including industrial forecasting, planning, design, control, and automation.

Academically, I have done extensive research in Estimation of Distribution Algorithms (EDAs), a branch of nature-inspired evolutionary algorithms, and have developed a novel Markov Network-based evolutionary algorithm, Distribution Estimation using Markov Networks (DEUM). Throughout my career, I have co-authored a book on computational optimization, published over 90 research papers, and filed more than 10 patents. My contributions have earned me numerous awards and recognitions. I also bring expertise in operations research, with a focus on pricing and revenue management. My recent research explores advanced machine learning techniques such as generative AI, large language models, and transformers, integrated with neuro-evolution to address large-scale sequential modeling challenges. These include demand forecasting, predictive maintenance, and time series analysis.

In my roles at BT and EBTIC, I have actively collaborated with leading universities in the UK and the UAE, successfully supervising over 5 PhD students and 10 MSc students. My work has consistently driven innovation, bridging the gap between theoretical advancements and practical, high-impact applications. 
 

Publications

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Research Interests

  • Evolutionary Computation
  • Deep Neural Networks
  • Neuroevolution and LLMs
  • Probabilistic Graphical Models
  • Large Scale Simulation
  • Operations Research
  • Artificial Intelligence

Misc 

 
 
 

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