Interview 01: Research work in Gene clustering algorithm for cancer detection


We are introducing a new category in our blogs where we would publish interviews from various fields which may motivate our readers.

We start this wonderful journey with the interview of Dr Asit Kr. Das, Mrs Sunanda Das and Mr Arka Das.

We sincerely hope that this interview and coming interviews would motivate others working in the field of machine learning, deep learning and data mining.

Q1. Thank you for your time with MieRobot team.We are so happy to host all three of you. Could you introduce yourself and your area of work for our audience, please?

Dr Asit Kr. Das is an Associate Professor of Computer Science and Technology at IIEST, Shibpur, Howrah,India. His research interests include Data Mining and Pattern Recognition, Text Categorization, Rough Set Theory, Bioinformatics etc. Google Scholar Link.

Mrs Sunanda Das is an Assistant Professor of Computer Science and Engineering at Neotia Institute of Technology, Management and Science, West Bengal, India. Her research interests include Data Mining and Pattern Recognition, Bio-informatics, Rough set Theory etc. Google Scholar Link.

Mr Arka Ghosh is a researcher of Indian Statistical Institute, Kolkata,India. His research interests include Evolutionary Algorithm, Machine Learning, Data Mining, Soft Computing. Google Scholar link.

Q2. Tell us in simple words how your publications can be applied to real-world problems?

Our research is based on computational intelligence and pattern analysis techniques. The purpose is to analyse microarray data and enable extraction of more meaningful information from it.

Each of diseased or normal samples of microarray data has expression profiles that are characteristic of their type. Clustering algorithm helps to group genes with similar expression profiles.

Microarray analysis is widely accepted for diagnosis and classification of human cancers. We have presented few approaches evolved for the analysis of microarray data for a cancer diagnosis to obtain general and reliable gene profiles that could be universally used in clinical laboratories.

Q3. India faces a shortage of research scholars like all of you. What could be done to motivate young Indians to take up research?

Maximum universities and institutes in India generally do not focus on research. Here values for degrees and qualification are given more priority than research and education.

So, the first important thing is to establish university curriculum in a way which helps to motivate the young students to bring their new innovative ideas with financial support.

There is uncertainty about future in young’s mind if research is taken as a career. It is our duty to make them realise their potential in their studies; encourage them to take up research careers in Science, and ensure the growth of the best scientific minds from grass level to top level for research and development in the country.

Q4. Tell us one challenge that you faced as a team and what you did you do to overcome it?

Finding the suitable research topic is the foundation on which everything else rests, so it is more important to choose carefully for conducting the research in order to move forward.

We as a team solve the challenges faced from selecting the research topic up to the completion of research development.

Q5. Which subjects should young engineers focus in college to work in the area of data mining, machine learning and data science in the future?

The data mining subject gives knowledge on data mining techniques for both structured data and unstructured data. Data science is a concept to unify statistics, data analysis to understand and analyse actual phenomena of data.

It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science.

One should go through the subjects having sub-domains of machine learning, classification, cluster analysis, data mining, databases, and visualisation to choose a career in this field

Rapid demand in data science gives a lot of opportunities to study and work. So, one should go through the subjects having sub-domains of machine learning, classification, cluster analysis, data mining, databases, and visualisation to choose a career in this field.

Q6. What do you think about MieRobot.com?

MieRobot is a motivated platform for making robots. In today’s era, it may become the digital guidebook for ones who are interested in the area of robotics. For the beginner’s also it is a very friendly platform to start work on it.

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