Dr. Pushparaj Shetty D.  is working as a faculty at National Institute of Technology Karnataka (NITK) Surathkal since 2000. He is presently holding the position of Associate Professor in department of Mathematical and computational sciences at NITK Surathkal. He obtained his B.E in Computer Science and Engineering in 1999 from Mangalore University and M.E in Computer Science and Engineering in 2005 from Indian Institute of Engineering Science and Technology, Shibpur, Kolkata (formerly Bengal Engg. and Science University). He obtained his Ph.D from the Computer Science and Applications group, Department of Mathematics at the Indian Institute of Technology Delhi (July 2014). His research interests are in the area of wireless sensor networks, graph algorithms and their applications in engineering, cloud computing and high performance computing. He has co-authored more than 25 research papers in peer-reviewed journals and conferences including few book chapters. He is a senior member of IEEE, senior member of ACM, and life member of Computer Society of India (CSI) and Institution of Engineers India (IEI). Dr. Pushparaj is volunteering as the Chair of IEEE Mangalore Subsection for the year 2021.Dr. Surendra Shetty is currently a Professor & Head, Department of Master of Computer Applications, NMAM Institute of Technology, Nitte. He had completed his B.Sc. in 2001 and he obtained his Master of Computer Applications in 2004 from Visvesvaraya Technological University, Belagavi. Dr. Surendra Shetty had been awarded his doctoral degree for his research work “Audio Data Mining Using Machine Learning Techniques” in 2013 from University of Mangalore. He has published more than 30 research papers in different international journals and conferences. He is currently guiding six research scholars. Dr. Surendra Shetty authored two book chapters in different publications entitled “Machine Learning Approach for Carnatic Music Analysis” and “Applications of Unsupervised Techniques for Clustering of Audio Data”.  He has received research grant of 20 lakhs from VGST (GoK) for carrying out research on “Automatic Natural Language Processing and Speech Disorder Problems in Kannada Language”. He has 16 years of teaching experience. His research areas of interest are cryptography, data mining, pattern recognition, speech recognition, MIS, software engineering and testing.

• Air Quality Prediction using Machine Learning.- Machine Learning Based Ensemble Network Security System.- Machine Learning based Air Pollution Prediction.- Intelligent IoT-based Product Dispenser and Billing System.- Speech Emotion Recognition using K-Nearest Neighbor Classifier.- Variants of Fuzzy C-means on MRI Modality for Cancer Image Archives.- Medical Image Encryption using SCAN Technique and Chaotic Tent Map System.- An Approach to Noisy Synthetic Color Image Segmentation using Unsupervised Competitive Self Organizing Map.- Implementing Face Search using HAAR cascade.- A Fast Block-based Technique to Detect Copy-move Forgery in Digital Images.- Bottlenecks in Finite Impulse Response Filter Architectures on a Reconfigurable Platform.- A Detail Analysis and Implementation of HAAR Cascade Classifier.- Sentiment Analysis of Twitter Posts in English, Kannada and Hindi Languages.- An Efficient Algorithm for Fruit Ripeness Detection.- A Comparative Study of Efficient Classification Models.- A Neural Attention Model for Automatic Question Generation using Dual Encoders.

Dr. Pushparaj Shetty D.  is working as a faculty at National Institute of Technology Karnataka (NITK) Surathkal since 2000. He is presently holding the position of Associate Professor in department of Mathematical and computational sciences at NITK Surathkal. He obtained his B.E in Computer Science and Engineering in 1999 from Mangalore University and M.E in Computer Science and Engineering in 2005 from Indian Institute of Engineering Science and Technology, Shibpur, Kolkata (formerly Bengal Engg. and Science University). He obtained his Ph.D from the Computer Science and Applications group, Department of Mathematics at the Indian Institute of Technology Delhi (July 2014). His research interests are in the area of wireless sensor networks, graph algorithms and their applications in engineering, cloud computing and high performance computing. He has co-authored more than 25 research papers in peer-reviewed journals and conferences including few book chapters. He is a senior member of IEEE, senior member of ACM, and life member of Computer Society of India (CSI) and Institution of Engineers India (IEI). Dr. Pushparaj is volunteering as the Chair of IEEE Mangalore Subsection for the year 2021.Dr. Surendra Shetty is currently a Professor & Head, Department of Master of Computer Applications, NMAM Institute of Technology, Nitte. He had completed his B.Sc. in 2001 and he obtained his Master of Computer Applications in 2004 from Visvesvaraya Technological University, Belagavi. Dr. Surendra Shetty had been awarded his doctoral degree for his research work “Audio Data Mining Using Machine Learning Techniques” in 2013 from University of Mangalore. He has published more than 30 research papers in different international journals and conferences. He is currently guiding six research scholars. Dr. Surendra Shetty authored two book chapters in different publications entitled “Machine Learning Approach for Carnatic Music Analysis” and “Applications of Unsupervised Techniques for Clustering of Audio Data”.  He has received research grant of 20 lakhs from VGST (GoK) for carrying out research on “Automatic Natural Language Processing and Speech Disorder Problems in Kannada Language”. He has 16 years of teaching experience. His research areas of interest are cryptography, data mining, pattern recognition, speech recognition, MIS, software engineering and testing.

• Air Quality Prediction using Machine Learning.- Machine Learning Based Ensemble Network Security System.- Machine Learning based Air Pollution Prediction.- Intelligent IoT-based Product Dispenser and Billing System.- Speech Emotion Recognition using K-Nearest Neighbor Classifier.- Variants of Fuzzy C-means on MRI Modality for Cancer Image Archives.- Medical Image Encryption using SCAN Technique and Chaotic Tent Map System.- An Approach to Noisy Synthetic Color Image Segmentation using Unsupervised Competitive Self Organizing Map.- Implementing Face Search using HAAR cascade.- A Fast Block-based Technique to Detect Copy-move Forgery in Digital Images.- Bottlenecks in Finite Impulse Response Filter Architectures on a Reconfigurable Platform.- A Detail Analysis and Implementation of HAAR Cascade Classifier.- Sentiment Analysis of Twitter Posts in English, Kannada and Hindi Languages.- An Efficient Algorithm for Fruit Ripeness Detection.- A Comparative Study of Efficient Classification Models.- A Neural Attention Model for Automatic Question Generation using Dual Encoders.