Artificial Intelligence and Machine Vision models gives a better society

March 26-28 2021


  • Introduce the recent trends in Artificial Intelligence and Machine vision to today's society
  • For the researchers to enhance their knowledge through discussions
  • Intended for the academic community as well as practicing engineers, consultants and industry fellows
  • Focused group is the scholars who are working in virology, medical field, data analytics, natural language, speech processing and allied areas of Artificial Intelligence
  • Artificial intelligence and Machine vision comprise of Intelligence algorithms and how effectively we can incorporate the intelligence in a machine

Important dates to remember:

Event Open Closed
Extended Abstract Submission 5th January 2021 6th March 2021
Notification of acceptance Before 15th March 2021
Registration of participants 17th March 2021 21th March 2021
Conference Dates 26-28 March 2021


Patron :      Prof. V P Mahadevan Pillai, Vice-Chancellor, University of Kerala, INDIA

Organising Committee Members

  • Dr. D. Muhammad Noorul Mubarak, Department of Computer Science, University of Kerala, INDIA
  • Prof. K. G. Gopchandran, Department of Opto-electronics, University of Kerala, INDIA
  • Prof. Jaya D. S., Department of Environmental Science, University of Kerala, INDIA
  • Dr. Jayamol Mathews, Department of Computer Science, University of Kerala, INDIA
  • Dr. Thara P., Department of Future Studies, University of Kerala, INDIA
  • Dr. Biji C. L., Department of Computational Biology and Bioinformatics, University of Kerala, INDIA
  • Ms.Sreelekshmi S., Department of Computer Science, University of Kerala, INDIA
  • Mr.Ranjith Katta, Department of Computer Science, University of Kerala, INDIA
  • Mr.Surjith Kumar J. K., Department of Computer Science, University of Kerala, INDIA

Technical Program Committee Members

  • Dr. Aji S (Chair),University of Kerala,INDIA
  • Prof. Deep Kusum, IIT Roorkee,INDIA
  • Prof. Dr.Jai Sankar, NIT Warangal,INDIA
  • Prof. Narottam Chand Kaushal, NIT Harmirpur,INDIA
  • Prof. Balasubramanian, MS University,INDIA
  • Prof. Bini, IIIT Kottayam,INDIA
  • Dr. Satheesh Kumar, University of Kerala, INDIA
  • Prof. Salim A, College of Engineering Trivandrum, INDIA
Dr. Vinod Chandra S S Ms. Philomina Simon
Professor Assisstant Professor
Department of Computer Science Department of Computer Science
University of Kerala University of Kerala
0471-2308360 8137806393

Target audience

  • Focused group is the scholars who are working in virology, medical field, data analytics, natural language, speech processing and allied areas of Artificial Intelligence.

Invited Speakers

Prof.Jan Sijbers
Professor, University in Antwerp, Belgium

Prof. Jan Sijbers graduated in Physics in 1993. In 1998, he received a PhD in Physics from the University of Antwerp, entitled Signal and Noise Estimation from Magnetic Resonance Images". He was an FWO Postdoc at the University of Antwerp and the Delft University of Technology from 2002-2008. In 2010, he was appointed as a senior lecturer at the University of Antwerp. In 2014, he became a full professor. He is Senior Area Editor of IEEE Transactions on Image Processing as well as Associated Editor of IEEE Transactions on Medical Imaging. Jan Sijbers is the head of imec-Vision Lab and co-founder of IcoMetrix and Deltaray. His main interest are in image reconstruction, processing, and analysis with focus on Magnetic Resonance Imaging and X-ray Computed Tomography.

Prof. Milan Tuba
Vice Rector for International Relations, Singidunum University,SERBIA

According to Prof. Milan Tuba in his work "Convolutional Neural Networks Optimization and Applications", Artificial intelligence and machine learning, as its subfield, have a high impact on science as well as on the applications used in everyday life. These applications solve tasks in various fields such as healthcare, security, agriculture, astronomy, autonomous vehicles, and many more. Frequent task in these applications is classification and, in large number of cases, classification of digital images. Digital image classification has been widely studied in past decades and significant progress has been made several years ago with the introduction of the convolutional neural networks. Convolutional neural networks represent a special class of deep neural networks which exploits spatial correlation of input data (neighboring pixels in digital images). While building a CNN, with the powerful tools that are available nowadays, is a rather simple task, the improvements in the classification accuracy compared to the existing methods are outstanding. Even though it is relatively easy to implement and modify CNNs, finding the optimal configuration and architecture is a very challenging task due to large number of hyper-parameters such as number and type of layers, number of neurons in each layer, kernel size, optimization algorithm, etc. The CNN should be ajdusted for each task individually since the optimal CNN for one task is not necessarily optimal for another. Currently, an efficient method for tuning CNNs’ hyperparameters and determining its architecture does not exist. The common method for establishing CNN’s configuration is by guessing and estimating (guestimating) better values for the hyper-parameters. Since adjusting CNNs’ hyperparameters for the concrete problem represents a hard optimization problem, it can be tackled by swarm intelligence algorithms. This process is time consuming but several studies have shown that adjusting CNNs’ hyperparameters by swarm intelligence algorithms improves the classification accuracy

Dr. M. R. Kaimal
Ph.D. Chairman and Professor at the Department of Computer Science at Amrita School of Engineering, Amritapuri, Kerala INDIA

Dr. Kaimal earned his Ph. D. in 1978 from the Mehta Research Institute, now known as the Harish Chandra Institute in Allahabad under the guidance of (Late) Padmabhushan Prof. P. L. Bhatnagar and Prof. Phoolan Prasad. During the years 1981-1984, he served as Visiting Fellow at the National Institute of Health in Bethesda, Maryland in USA. He was Professor and Head of the Department of Computer Science during the period March 1987 - April 2009. He also served as Dean of the Faculty of Applied Sciences at the University of Kerala during the periods 1993-1995 and 2004-2006. In August 2008, he served as Visiting Scientist at the Mobile Intelligent and Autonomous Systems (MIAS) Unit, CSIR in South Africa. He has worked on a major ISRO-funded research project titled Development of Methodologies based on Neuro-Fuzzy and Genetic Algorithms for Modelling and Control of Systems.Dr. Kaimal has over 30 years of teaching and research experience. In his illustrious career, he has published about 60 papers in top journals including the Journal of Math, Imaging and Vision, Computer Journal, IEEE Signal Proc. Letters, International Journal of Engineering Science, Transactions of ASME, IEEE Transactions, Fuzzy Systems, Sadhana and Foundations of Computer Science.His current research focuses on Artificial Intelligence and its applications to Image Processing and Knowledge Discovery. Other areas of interest include Machine Learning Algorithms, Pattern Recognition, Data Compression and Coding Algorithms.

Dr. Ashwin Ashok
Assistant Professor , Department of Computer Science, Georgia State University(GSU),GEORGIA

Dr. Ashwin Ashok is working as Assistant Professor in the Dept. of Computer Science and the Director of the MORSE Studio research lab at Georgia State University (GSU). His research group focuses on emerging technologies in Mobile and Robotic Systems through experiential research. His work spans areas in visible light and camera communications, mobile and wearable systems, robotics, vehicular networking, computer vision, and mHealth. He completed his postdoctoral research from Carnegie Mellon University in 2016, under the mentorship of Prof. Peter Steenkiste and Dr. Fan Bai, and his Ph.D. from Wireless Information Network Lab (WINLAB) at Rutgers University in 2014, under the mentorship of Profs. Marco Gruteser, Narayan Mandayam and Kristin Dana.

Dr. Ananthalakshmi Ammal
Senior Director & Head, Cyber Security Group, CDAC, Thiruvananthapuram, INDIA.

Dr. Ananthalakshmi Ammal is Senior Director at Centre for Development of Advanced Computing (CDAC), a premier Research and Development organization of the Ministry of Electronics and Information Technology (MeitY) Government of India. She is heading the Cyber Security Group at Thiruvananthapuram Centre. With career spanning over three and half decades in various domains of Information Technology, Smt. Ananthalakshmi Ammal has played the key role in Nation’s prestigious e-Governance,Cyber Security and Cyber Forensics initiatives.She is also the Chief Investigator of many nationally important projects such as National Cyber Coordination Centre (NCCC), Technology development of Forensics Data Analytics, Security Data Analytics, etc. She has a modest number of research publications and currently her research interests include Digital Forensics, Network Management Systems, Software Defined Networks and Security Analytics. Her team is supporting the Law Enforcement Agencies in cybercrime analysis, setting up of cyber forensic labs and imparting training on Digital Forensics.

Dr Deep Kusum
Professor , Department of Mathematics, Indian Institute of Technology, Roorkee,INDIA

Dr Deep Kusum is working as Professor in the Department of Mathematics, Indian Institute of Technology, Roorkee, India. She has obtained her Ph.D in Mathematics from University of Roorkee and Post Doctorate in Parellel Computing from Loughborough University, UK in 2020. recently she got Best Paper Award from International Conference on Operations Research and Decision Sciences, IIM Visakhapatanam in 2019. Her area of interest areOperations Research, Design of Nature Inspired Optimization Techniques, Numerical Optimization, Evolutionary Algorithms, Swarm Intelligence, Parallel Computing , Parallel Nature Inspired Optimization, Membrane Computing, P-Systems, GPU computing, Soft Computing , Computational Intelligence, Neural Networks, Fuzzy, Applications, Forecasting of Landslides, Avalanches, Earthquake, Finance, Applications

Dr. Devu Manikantan Shila
Founder & CEO at, Greater Orlando, Florida, USA

Dr. Devu M Shila, Founder and CEO of (, is a seasoned leader in building and transitioning privacy-preserving mobile/wearable based human behavioral analytics products. She was the Principal Investigator and product leader for several advanced cyber security and privacy programs funded by DARPA, DHS S&T, DOE, Army, NSF where her team, including scientists, engineers, psychologists and medical experts, developed novel biosignature analytical algorithms based on adversarial resistant deep neural networks unobtrusively obtained from smartphone and IoT sensors to authenticate and infer the health state of the users. Her research interests include development and application of advanced AI such as adversarial deep learning, lifelong learning, generative adversarial networks, differential privacy and big data technologies in cyber security and healthcare domain. Prior to founding, she was the Director, Research, and Innovation, at United Technologies Research Center and co-founded Cyber Physical Systems Lab in 2012. She has authored over 60+ peer-reviewed journal and conference papers and is the inventor of 10+ US patents. She has a Ph.D. and M.S in Computer Science and Engineering from Illinois Institute of Technology, Chicago in 2011. Dr. Shila has received numerous accolades, best paper awards and research grants and was 2017 Connecticut Women of Innovation finalist. More information on Dr. Shila’s publications can be found at

Dr. Smitha S Nair
Head, Centre for Postgraduate Studies, Middle East College, Sultanate of Oman

Dr. Smitha heads the Centre of Postgraduate Studies in Middle East College, Sultanate of Oman. She holds B. Tech (Computer Science and Engineering) from the University of Calicut, India, M. Tech (Computer Science) from the University of Kerala, India, Ph. D (Computational biology) from Manipal University, India and PGCert (Academic Practices in Higher Education) from Coventry University, UK. She has more than fifteen years of teaching and research experience. Her primary research interest is interdisciplinary including Biomedical Informatics. She has a number of research publications in reputed journals and conferences. She is a recipient of several research grants from The Research Council of Oman. She has achieved the status of Senior Fellow of The Higher Education Academy in recognition of attainment against the UK Professional Standards Framework for Teaching and Learning support in higher education.

Dr. John Jose
Assistant Professor, Department of Computer Science & Engineering, Indian Institute of Technology Guwahati,INDIA

Dr. John Jose works in the domain of multicore computer architecture.He attained his Ph.D from Indian Institute of Technology Madras, M.Tech FromVellore Institute of Technology, Vellore. His research group in Multicore Architecture and Systems (MARS) Lab explore problems in Network on Chip (NoC) and Cache Optimisation in Tiled Chip Multi-Processors, Wireless On Chip Interconnects and Edge/Fog Computing, Machine Learning based accelerators for NoCs.

Dr. Raju G
Professor, Department of Computer Science & Engineering, School of Engineering and Technology, Christ University,Banglore,INDIA

Dr. Raju G is presently working as Professor,Department of Computer Science & Engineering, Kangeri Campus.He has years of experience in the Field of Machine Learning , Neural networks and related field of Artificial Intelligence. He took is MSc in 1986 from Univeristy of Kerala and in 1991 he took Master in Computer Application and Ph.D in 2003 from University of Kerala.He got IBAE awards Distinguished Educator award from the organization GISR Foundation and The American College of Dubai.

Mr. Shine Jayamohanan
Associate Tech Specialist,CANADA

Mr. Shine Jayamohanan is currently working as Associate Tech Specialist in an IT Firm Canada. He has bagged his Post graduation (Master of Computer Applications) from Mahatma Gandhi University, Kerala. He has been engaging more than 12 years in IT industry in multiple domains such as healthcare, retail and telecom and in various capacities. He has successfully delivered various projects in prominent organizations - NttData, HCL Technologies, Dell International and GE Healthcare. His area of interest are Big Data Mining, Machine Learning, Deep Learning, Cloud Computing and Natural Language Processing.

Dr.Anand Hareendran S
Associate Professor, Department of Computer Science, Muthooth Engineering College, Ernakulum,INDIA

Dr.Anand Hareendran S, Associate Professor & HoD, Department of Computer Science, Muthooth Engineering College, Ernakulum, received his Ph.D. degree with Specializations in Machine Learning Algorithms from University of Kerala in 2016 and M.E. Degree from Anna University. His current research interest are in Bio-Inspired Algorithms , Natural Language Processing, Artificial Intelligence.

Dr Raji C.G.
Professor and Head ,Computer Science & Engineering department in MEA Engineering College,Malappuram,INDIA

Dr Raji C.G is working as Professor in Computer Science & Engineering department in MEA Engineering College, Perinthalmanna, Kerala, India which is a NAAC accredited institution and affiliated to APJ Abdul Kalam Technological University, Thiruvananthapuram, Kerala.India. She has obtained her Ph.D in Computer Science & Engineering from Manonmaniam Sundaranar University.Her thesis primarily examines neural network based computational methods for medical prognosis. She got an overall experience of 16+ years in the fields of academic teaching, research and administration. She has published several research papers in internationally reputed journals, Book chapter and conferences. She is serving as a reviewer for various International journals and conferences. Her area of Interest are Health Informatics,Machine Learning,Deep Learning, Artificial Neural Networks.She was the Chairman of question paper setter panel of MCA in Calicut University. She is also serving as the member of syllabus revision panel of MCA in Calicut University. She is recognized as research supervisor in APJ Abdul Kalam Technological University, Thiruvananthapuram, Kerala.

Call for Papers for ICAIS 2021

Call for Papers details are as follows:

Second International Conference on Artificial Intelligence and Applications (ICAIS 2021) is a forum for presenting new advances and research results in the fields of Artificial Intelligence. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. The scope of the conference covers all theoretical and practical aspects of the Artificial Intelligence.

• Fuzzy logic Techniques & Algorithm
• AI Algorithms
• Artificial Intelligence Tools & Applications
• Automatic Control
• Bioinformatics
• Natural Language Processing
• Image Processing
• Computer Vision
• Data Mining and Machine Learning Tools
• Heuristic and AI Planning Strategies and Tools
• Computational Theories of Learning
• Hybrid Intelligent Systems
• Information Retrieval and Text Mining
• Video Processing
• Intelligent System Architectures
• Bioinspired Optimization Algorithms
• Knowledge-based Systems
• Multimedia & Cognitive Informatics
• Deep Neural Networks
• Pattern Recognition
• Robotics
• Semantic Web Techniques and Technologies
• Soft Computing Theory and Applications
• Software and Hardware Architectures
• Web Intelligence Applications and Search

Call for abstracts:

Extended abstracts showcasing the artificial intelligence and applications are invited for presentation. All abstracts must be original and should follow the prescribed abstract guidelines. Selected abstracts will be given the opportunity for paper presentation. Selected extended abstracts will be published in the proceedings with ISBN and authors are free to publish full length papers elsewhere.

Extended abstract guidelines:

• Extended abstract should not exceed two pages.
• Identify the presenting author by underlining his/her name in the author list.
• The entire document should be prepared on an A-4 sized paper in single page using Springer LNCS format with a maximum of 2 - 3 pages.
• Extended abstract should contain an abstract, introduction, methodology, results and brief discussion, and conclusion in the springer format.

All presenting authors should register.(Free)   Register Now

Brochure       Programme schedule      

All the papers must be submitted through email :

Sample Springer Paper Template (MS Word)
Sample Springer Paper Template (LaTex)

About Conference

This International conference is to introduce the recent trends in Artificial Intelligence and Machine vision to today's society. Artificial Intelligence and Machine Vision is an allied area of computer science that includes Pattern Recognition, Intelligence Algorithms and Deep Learning. The machines are made intelligent through Intelligence algorithms by training and testing. Another focus of this conference is for the researchers to enhance their knowledge through discussions. Internationally widespread Artificial intelligence applications designed for human need. It includes before and after the effects of COVID 19 society.The forum is intended for the academic community as well as practicing engineers, consultants and industry fellows. Another focused group is the scholars who are working in virology, medical field, data analytics, natural language, speech processing and allied areas of Artificial Intelligence. Eminent Professors and leading industrial fellows will deliver lectures for the conference, enhancing the participants' knowledge. A selected few students can also drive their opportunities in this proposed conference.

About the University

One of the first 16 Universities in India, the University of Kerala (Re-accredited by NAAC with A-grade) was founded as the University of Travancore in the erstwhile princely state of Travancore in 1937. At present, the University has sixteen faculties and forty one departments of teaching and research in addition to study centres and other departments. Teaching, Research and Knowledge extension are the mandate of the Departments. They primarily focus on post-graduate (masters) programmes, MPhil programmes (1-year research degree) and doctoral research. The total number of full-time students in the University Departments is above 2000 including research students and a modest number of foreign students. The Institute of Distance Education offers a number of under-graduate and post graduate programmes which cater to more than 7000 students, all over the country and abroad. Read more...

About the Department

The Department of Computer Science, University of Kerala, was established in 1985. It offers M.Sc. in Computer Science, M.Tech. in Computer Science (with specialization in Digital Image Computing), M.Phil. and Ph.D. in Computer Science. The Department gives at most importance on Research and Development besides regular teaching. Over the past few years the department has acquired national and international importance. The department has a track record of producing highly skilled professionals in the field of Computer Science. Many of the alumni are well placed in Institutes of National Importance, Central/State universities, R&D organisations like ISRO, CDAC, Educational Institutions and different MNCs. The department has produced more than 30 Ph.D.s so far. The students and faculty members have published a good number of research papers in reputed International Journals/Conference Proceedings published by IEEE, Springer, Elsevier, Wiley etc. Many of our students and faculty members have received national and international recognitions. Department of Computer Science is the only department in Kerala to bag the National Award for Best M.Tech. Thesis three times from Indian National Academy of Engineering (INAE), New Delhi. The faculty members of the department have received prestigious awards such as AICTE Career Award for Young Teachers, IEI Young Engineer Award, SSI Young System Scientist Award etc. to name a few. Read more...