Bio
Dr. Satish Gajawada is an independent scientist and inventor based in Hyderabad, India. He is an alumnus of IIT Roorkee and is credited as the creator of Artificial Human Optimization (AHO). His research focuses on novel optimization algorithms and nature-inspired computing.
Educational Journey
Indian Institute of Technology Roorkee
B.Tech/M.Tech, IDD, Computer Science with Specialization in IT, IIT Roorkee. CGPA - 7.23, 2012. • Artificial Satisfaction, Deep Loving, Nature++ Inspired Computing
2012Indian Institute of Technology Roorkee
Alumnus, Indian Institute of Technology Roorkee, Uttaranchal, India. Independent Inventor and Scientist. Founder and Father of Artificial Human Optimization. Inventor of Artificial Soul Optimization and Artificial God Optimization. The Creator of Artificial Satisfaction. Inventor of Deep Loving Field. The Designer of Nature Plus Plus Inspired Computing. The Creator of Artificial Heart Neural Networks Field. The Inventor of Artificial Excellence Field, India
Experience
Research
Artificial Excellence – A New Branch of Artificial Intelligence
"Artificial Excellence" is a new field which is invented in this article. Artificial Excellence is a new field which belongs to Artificial Human Optimization field. Artificial Human Optimization is a sub-field of Evolutionary Computing. Evolutionary Computing is a sub-field of Computational Intelligence. Computational Intelligence is an area of Artificial Intelligence. Hence after the publication of this article, "Artificial Excellence (AE)" will become popular as a new branch of Artificial Intelligence (AI). A new algorithm titled "Artificial Satish Gajawada and Durga Toshniwal Algorithm (ASGDTA)" is designed in this work. The definition of AE is given in this article followed by many opportunities in the new AE field. The Literature Review of Artificial Excellence field is shown after showing the definition of Artificial Intelligence. The new ASGDTA Algorithm is explained followed by Results and Conclusions.
Artificial Heart Neural Networks – An Idea
Artificial Neural Networks Field (ANN Field) is an exciting field of research. ANN field took its inspiration from Human Brain. The heart and Brain are very important for the survival of Humans. Research Scientists published many articles by giving importance to Brain. But scientists have not yet explored much on the Heart which is another important part in addition to the Brain. The primary purpose of publishing this article is to show a path to ANN field Research Scientists by introducing the concept of “Heart†into Artificial Neural Networks. In this paper, we coined and defined “Artificial Heart Neuron,†which is the basic part of Artificial Heart Neural Networks Field (AHNN Field) in addition to Artificial Neuron. This work takes its inspiration from both Heart and Brain.
Nature Plus Plus Inspired Computing – The Superset of Nature Inspired Computing
The term "Nature Plus Plus Inspired Computing" is coined by us in this article. The abbreviation for this new term is "N++IC." Just like the C++ programming language is a superset of C programming language, Nature Plus Plus Inspired Computing (N++IC) field is a superset of the Nature Inspired Computing (NIC) field. We defined and introduced "Nature Plus Plus Inspired Computing Field" in this work. Several interesting opportunities in N++IC Field are shown for Artificial Intelligence Field Scientists and Students. We show a literature review of the N++IC Field after showing the definition of Nature Inspired Computing (NIC) Field. The primary purpose of publishing this innovative article is to show a new path to NIC Field Scientists so that they can come up with various innovative algorithms from scratch. As the focus of this article is to introduce N++IC to researchers across the globe, we added N++IC Field concepts to the Particle Swarm Optimization algorithm and created the "Children Cycle Riding Algorithm (CCR Algorithm)." Finally, results obtained by CCR Algorithm are shown, followed by Conclusions.
Deep Loving – The Friend of Deep Learning
Artificial Intelligence and Deep Learning are good fields of research. Recently, the brother of Artificial Intelligence titled "Artificial Satisfaction" was introduced in literature [10]. In this article, we coin the term “Deep Lovingâ€. After the publication of this article, "Deep Loving" will be considered as the friend of Deep Learning. Proposing a new field is different from proposing a new algorithm. In this paper, we strongly focus on defining and introducing "Deep Loving Field" to Research Scientists across the globe. The future of the "Deep Loving" field is predicted by showing few future opportunities in this new field. The definition of Deep Learning is shown followed by a literature review of the "Deep Loving" field. The World's First Deep Loving Algorithm (WFDLA) is designed and implemented in this work by adding Deep Loving concepts to Particle Swarm Optimization Algorithm. Results obtained by WFDLA are compared with the PSO algorithm.
Artificial Satisfaction – The Brother of Artificial Intelligence
John McCarthy (September 4, 1927 – October 24, 2011) was an American computer scientist and cognitive scientist. The term “Artificial Intelligence†was coined by him (Wikipedia, 2020). Satish Gajawada (March 12, 1988 – Present) is an Indian Independent Inventor and Scientist. He coined the term “Artificial Satisfaction†in this article (Gajawada, S., and Hassan Mustafa, 2019a). A new field titled “Artificial Satisfaction†is introduced in this article. “Artificial Satisfaction†will be referred to as “The Brother of Artificial Intelligence†after the publication of this article. A new algorithm titled “Artificial Satisfaction Algorithm (ASA)†is designed and implemented in this work. For the sake of simplicity, Particle Swarm Optimization (PSO) Algorithm is modified with Artificial Satisfaction Concepts to create the “Artificial Satisfaction Algorithm (ASA).†PSO and ASA algorithms are applied on five benchmark functions. A comparision is made between the results obtained. The focus of this paper is more on defining and introducing “Artificial Satisfaction Field†to the rest of the world rather than on implementing complex algorithms from scratch.
