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Emdad Khan

Emdad Khan
Emdad Khan
  • Adjunct Professor of Computer Science

Dr. Khan’s research areas include Natural Language Processing, Big Data, Intelligent Agent, Artificial Intelligence, Machine Learning, Human-Computer Interaction, and their applications, especially, in the areas of Internet / Intelligent Internet and Biological Systems. Dr. Khan also focuses on multi-disciplinary education with an emphasis on innovation and entrepreneurship to help global development – economic, social, cultural, and more with emphasis on increased peace & prosperity.


  • BS Electrical Engineering – Bangladesh University of Engineering & Technology, Bangladesh
  • MS Electrical Engineering – University of New Orleans, USA
  • MS Engineering Management, Stanford University, USA
  • PhD Computer Science – University of California, Santa Cruz, USA

Patents, Papers, and Books

Holds 23 Patents, published over 75 Journal & Conference papers and 2 books

Author of “Internet for Everyone: Reshaping the Global Economy by Bridging the Digital Divide” 978-1-4620-4251-7 (SC ISBN), 978-1-4620-4250-0 (HC ISBN), 2011

Wrote a chapter in “Fusion of Neural Networks, Fuzzy Systems, and Genetic Algorithms: Industrial Applications, ISBN 0849398045,1998.

Sample Papers:

  1. E. Khan, “Lifelong Machine Learning with Logic, Semantics and Natural Language Processing”, International Conference on Artificial Intelligence (ICAI 2019), July 29 -Aug 1, 2019, Las Vegas, NV.
  2. E. Khan, “Next generation web – intelligent search, question answering, summarization and more”, INTERNATIONAL JOURNAL of COMPUTERS AND COMMUNICATIONS, (NAUN & UNIVERSITY PRESS), Vol. 9,  June 2015.
  3. E. Khan, “Natural Language Processing, Big Data, Bioinformatics and  Biology”, INTERNATIONAL JOURNAL OF BIOLOGY AND BIOMEDICAL ENGINEERING (NAUN & UNIVERSITY PRESS), June 2014.


Dr. Khan founded InternetSpeech with the vision to develop innovative technology for accessing information on the Internet anytime, anywhere, using just an ordinary telephone and the human voice. As a pioneer in the Internet voice space, Khan is a frequent speaker at Natural Language, Voice-Recognition, AI, Machine Learning, Internet applications, and other academic & industry conferences and trade shows. He holds 23 patents and has published over 75 journal & conference papers on the advent of Intelligent Internet, Content Rendering, Lifelong Machine Learning, Natural Language Processing/Understanding/Generation, Big Data, Bioinformatics, Software Engineering, Neural Nets, fuzzy logic, Intelligent Systems, VLSI, and optics. Khan’s acute technical knowledge and keen understanding of emerging markets have played an important role in the development of InternetSpeech’s products/services/technologies netECHO (Voice Internet that delivers complete Internet access via voice and any phone) and Semantic Engine using Brain-Like & Brain-Inspired Algorithms/Approaches, SEBLA.

Khan invented, defined, developed, and deployed worldwide new intelligent software products for micro-controller-based home appliances. He has been in the industry for 20 years (worked at Intel, Fairchild, and National Semiconductor) and academia for over 10 years.

Current Research Interests

Dr. Khan’s current major interest is to use brain-like and brain-inspired algorithms to solve some open problems, especially, NLU (Natural Language Understanding) and AI (Artificial Intelligence) to allow users to interact with the Internet (or other sources) using natural language, and thus help their economic, social, and other developments. Solving the NLU and AI problems using a semantic engine & logic has numerous applications including Intelligent Search, Intelligent Information Retrieval, Big Data, Question & Answer System, Summarization, Analytics, and more. These can be used in finance, economics, biology, agriculture, and many other business areas; and are critical for Economic, Social, Cultural, and other developments with increased World Peace, with a special focus on Education, Innovation, and Entrepreneurship.

Today’s AI is heavily influenced by the growing success of Machine Learning (ML). A fully capable Learning System would need to have most learning capabilities of a human – self-learning, creating knowledge, learning from experience, determining what to be learned and the like, and called Lifelong Machine Learning (LML). With the impressive growth of the use of Machine Learning (ML – including Deep Learning, Transfer learning, etc.) and Artificial Intelligence (AI) in many applications, the need for LML is becoming more attractive. By creating knowledge and learning from previous knowledge or experience continuously across tasks and across domains, LML can help AI-ML grow further. AI itself also needs to have the most logical, cognitive & inferencing capabilities of humans to be accepted as more trustworthy, reliable, capable, dependable, and complete AI. NLP, ML, LML, and logic among others are key drivers to solve open AI problems.

His recent interest is also exploring how the human brain uses vital communications, biological alphabets, and associated language to gain an understanding of meanings of the communications, a basic necessity to clearly understand how biological systems work. AI, NLP, ML, LML will help this process. Science of Creative Intelligence & Vedic Science will also help, especially with NLP/NLU/NLG as human natural language is the expressing means of intelligence and thoughts which are directly related with Pure consciousness in the Unified Field.


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