WMO Arts & Science College is a premier higher educational institution situated in the most beautiful Western Ghats. The College is affiliated with the University of Calicut and holds the highest NAAC point in the district A Grade with 3.12 points. The institution has been empowering the backward minorities, orphans and destitute upholding ethical and moral values. The campus bound with academic and serene vicinity that conducive to educational and extracurricular developments.

WMO Arts and Science College, established in 1995 by the Wayanad Muslim orphanage, WMO Arts and Science College is an institute run by the Muslim minority community. Majority of the population in the district consists of Scheduled Caste, Scheduled Tribes, and other Backward Communities. Earlier, they were not in a position to acquire higher education. The orphanage committee planned to start the college with a view of uplifting the youth especially the orphans, and educating them irrespective of caste, religion, or creed. Since then, the college has been playing a vital role igniting thousands of students in and around the district of Wayanad, equipping them with international standards in all sectors of life.

Aspiring for all round development of each student entering the portals of the college, this institution is open to learners of all castes and creeds facilitating healthy academic atmosphere.

Strive for academic excellence, creativity and social commitment to the citizens, especially the backward minorities, the orphans and the destitute, upholding the ethical and religious values.

Situated in an eye-catching hilly area at Muttil in Wayanad district WMO Arts and Science College is by the side of Calicut-Mysore National Highway (212), 6 kms north of Kalpetta, the district headquarters.

The department of statistics was established in the year 2017. It is successfully run under the leadership of Principal Dr. Fareed and has Postgraduate Program in Statistics now.

The Conference is an initiative to bring the concept of Statistical Machine Learning into the minds of researchers and Post Graduate students. Statistical Machine Learning is a set of tools for understanding data. These tools broadly come under two classes: supervised learning & unsupervised learning. Machine Learning helps in analysing the data as well as identifying trends. Thus, discover the patterns in the user data and make predictions for answering business questions and solving medical problems of Covid - 19.

Statistical Machine Learning and its Applications to Covid-19

SUBTHEMES: Hidden Markov Chain Model (HMM) Hierarchical Bayes Model Long-short-term-memory model (LSTM) Mechanistic models based on SEIR (referring to Susceptible, Exposed, Infected, and Recovered states) framework or its modified version. Time series prediction models such as ARIMA/Grey Model Agent type models (ie. simulating individual activities for a population) Impact of Covid-19 vaccination in India General statistical model Artificial Intelligence in Covid-19 drug discovery and development Big data in Covid-19 analysis Knowledge representation in Covid-19 analysis Pattern recognition in Covid-19 risk analysis Machine learning for Covid-19 tracking and prediction models Applications of the Internet of Things in healthcare Computer vision in Covid-19 related medical imaging Software and/or Hardware in computer-assisted studies Social network analysis for study of spread of disease

Mr. Mohammed Jamal, Chairman & Manager,
WMO Arts & Science College, Muttil, Wayand, Kerala

Adv. K. Moidu, Convenor, Management Committee
Dr. T.P.Muhammad Fareed, Principal

Dr. T C Mini, Head, Dept. of Statistics

Dr.Sangitha Kulthinal, Senior Professor, University of Helsinki, Finland
Dr. N Raju, Rtd. Professor, University of Calicut
Dr. P. Anil Kumar, Head, Dept. of Statistics, Devagiri St. Joseph's College
Dr. K K Hamsa, Senior Faculty, WMO Arts & Science College

Mr. Madhusudanan K, Faculty, WMO Arts & Science College
Mr. Shakeelurrahman, Faculty, WMO Arts & Science College
Ms. Vihitha, II MSc Student
Ms. Arshada, I MSc Student
Mr. Shajahan, I MSc Student