# Graham Kendall > British scientist **Wikidata**: [Q5592974](https://www.wikidata.org/wiki/Q5592974) **Wikipedia**: [English](https://en.wikipedia.org/wiki/Graham_Kendall) **Source**: https://4ort.xyz/entity/graham-kendall ## Summary Graham Kendall is a British computer scientist and artificial intelligence researcher known for his work in meta-heuristic algorithms and optimization problems. He is a professor emeritus at the University of Nottingham Malaysia Campus and has contributed to advancements in computational problem-solving. ## Biography - Born: July 21, 1961, in London - Nationality: United Kingdom - Education: University of Nottingham (PhD, advised by Edmund K. Burke) - Known for: Applying meta-heuristic algorithms to optimization problems, particularly the nesting problem - Employer(s): University of Nottingham Malaysia Campus (professor emeritus) - Field(s): Computer science, artificial intelligence, optimization algorithms ## Contributions Graham Kendall has made significant contributions to the field of computer science, particularly in the development and application of meta-heuristic algorithms. His doctoral thesis, *Applying meta-heuristic algorithms to the nesting problem utilising the no fit polygon*, (2018) explored the use of these algorithms in solving complex optimization problems. His research has influenced the development of more efficient computational methods for industrial and service sector applications. Kendall has also been involved in academic leadership, serving as a professor emeritus at the University of Nottingham Malaysia Campus. His work has been recognized through various academic identifiers, including his ISNI, VIAF, and ORCID records, which document his extensive contributions to research and education. ## FAQs ### Q: What is Graham Kendall known for? A: Graham Kendall is known for his work in applying meta-heuristic algorithms to optimization problems, particularly the nesting problem, and his contributions to artificial intelligence research. ### Q: Where did Graham Kendall earn his PhD? A: Graham Kendall earned his PhD from the University of Nottingham, advised by Edmund K. Burke. ### Q: What is Graham Kendall's current academic role? A: Graham Kendall is a professor emeritus at the University of Nottingham Malaysia Campus. ### Q: What is Graham Kendall's field of expertise? A: Graham Kendall specializes in computer science, artificial intelligence, and optimization algorithms. ### Q: What is Graham Kendall's notable academic thesis? A: Graham Kendall's notable academic thesis is *Applying meta-heuristic algorithms to the nesting problem utilising the no fit polygon*, published in 2018. ## Why They Matter Graham Kendall's work in meta-heuristic algorithms and optimization has had a significant impact on the field of computer science. His research has contributed to the development of more efficient computational methods for solving complex problems, particularly in industrial and service sectors. As a professor emeritus, he has mentored numerous students and researchers, shaping the next generation of computational problem-solvers. His contributions have been widely recognized through academic citations and identifiers, ensuring his work remains influential in the field. ## Notable For - Professor emeritus at the University of Nottingham Malaysia Campus - Author of the doctoral thesis *Applying meta-heuristic algorithms to the nesting problem utilising the no fit polygon* (2018) - Recognized researcher with multiple academic identifiers, including ISNI, VIAF, and ORCID - Contributions to artificial intelligence and optimization algorithms - Leadership in academic research and education ## Body ### Early Life and Education Graham Kendall was born on July 21, 1961, in London, United Kingdom. He pursued his higher education at the University of Nottingham, where he completed his PhD under the supervision of Edmund K. Burke. His doctoral thesis, *Applying meta-heuristic algorithms to the nesting problem utilising the no fit polygon*, was published in 2018 and remains a significant contribution to the field of optimization algorithms. ### Academic Career Graham Kendall's academic career has been marked by his contributions to computer science and artificial intelligence. He has held various academic positions, including professor emeritus at the University of Nottingham Malaysia Campus. His research has focused on meta-heuristic algorithms and their applications in solving complex optimization problems. Kendall's work has been widely recognized through his academic identifiers, including his ISNI, VIAF, and ORCID records, which document his extensive contributions to research and education. ### Research Contributions Graham Kendall's research has had a significant impact on the field of computer science. His work on meta-heuristic algorithms and optimization problems has influenced the development of more efficient computational methods. His doctoral thesis, *Applying meta-heuristic algorithms to the nesting problem utilising the no fit polygon*, is a landmark publication in the field. Kendall's research has been cited in various academic sources, ensuring its lasting influence on the discipline. ### Recognition and Legacy Graham Kendall's contributions to computer science and artificial intelligence have earned him recognition in the academic community. His work has been documented through multiple academic identifiers, including his ISNI, VIAF, and ORCID records. As a professor emeritus, he continues to mentor students and researchers, shaping the future of computational problem-solving. Kendall's legacy is one of innovation and excellence in the field of computer science. ## References 1. Virtual International Authority File 2. [ORCID Public Data File 2023](https://pub.orcid.org/v3.0/0000-0003-2006-5103/employment/16557330) 3. Mathematics Genealogy Project 4. International Standard Name Identifier 5. E-Theses Online Service 6. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0003-2006-5103/external-identifiers/38826) 7. [ORCID Public Data File 2020](https://pub.orcid.org/v3.0_rc1/0000-0003-2006-5103/external-identifiers/191194) 8. IdRef 9. CONOR.SI