Selected Journals and Conferences

2023

• Amal F, Arjun BJ, Jaideep Kumar P, Pranesh D, Statistically Aided Binary Multi-Objective Grey Wolf Optimizer: A New Feature Selection Approach for Classification, Journal of supercomputing, Springer (SCI, IF: 2.5).
• Runad K, P Das, S N. SCEOMOO: A novel Subspace Clustering approach using Evolutionary algorithm, Off-spring generation and Multi-Objective Optimization, Applied soft computing, Elsevier (SCI, IF:8.2).
• P P Dev, P Das, R Hazari.  MSDeepNet: A novel multi-stream deep neural network for real-world anomaly detection in surveillance videos, DeLTA2023 (Accepted), Rome, Italy.
• Ghosh R, Phadikar S, Deb N, Sinha N, Das P, Ghaderpour E, Automatic Eye-blink and Muscular Artifact Detection and Removal from EEG Signals using k-NN Classifier and LSTM Networks, IEEE Sensors Journal (SCI, IF:4.3).

2022

• Shreya, S, Pranesh D, Binu JA, A new framework for disease prediction: Using dimensionality reduction and feature selection, Soft Computing Theories and Applications.

2021

• Binu Jose, A, P Das.  A multi-objective approach for inter-cluster and intra-cluster distance analysis for Numeric Data, Soft Computing Theories and Applications.
• Ghosh R, Deb N, Sengupta K, Phukan A, Choudhury N, Kashyap S, Phadikar S, Saha R, Das P, Sinha N, Dutta P,  SAM 40: Dataset of 40 Subject EEG Recordings to Monitor the Induced-Stress while performing Stroop Color-Word Test, Arithmetic Task and Mirror Image Recognition Task, Data in Brief, Elsevier (SCI).

2020

• Saha, R, Biswas S, Sarmah S, Das P, Karmakar S, Design and implementation of routing algorithm to enhance network lifetime in wban, Wireless Personal Communications, Springer (SCI, IF: 2.0).
• Saha, R, Biswas S, Sarmah S, Karmakar S, Das P, A working prototype using DS18B20 temperature sensor and Arduino for health monitoring, SN Computer Science, Springer, Scopus.

2018

• Das P, Das DK, Dey S, A modified Bee Colony Optimization (MBCO) and its hybridization with k-means for an application to data clustering, Applied Soft Computing. 70:590–603, Elsevier (SCI, IF:8.2).
• Das, P, Das DK, Dey S.  2018.  A new class topper optimization algorithm with an application to data clustering, IEEE Transactions on Emerging Topics in Computing (SCI, IF:6.5).

2017

• Das P, Das DK, Dey S, A Multi-objective Modified Particle Swarm Optimization (MMPSO) technique with an application to data clustering,14th IEEE India Council International Conference (INDICON).
• Das P, Das DK, Dey S, PSO, BCO and K-means Based Hybridized Optimization Algorithms for Data Clustering, IEEE International Conference on Information Technology (ICIT), Bhubaneswar.

2013

• Das P, Khilar PM, VFT: A virtualization and fault tolerance approach for cloud computing, IEEE Conference on Information & Communication Technologies (ICT), Kanyakumari.
• Das, P, Virtualization and fault tolerance in cloud computing.

• Data Mining

• Computational Intelligence

• Machine Learning

• Nature-inspired optimization algorithms 

Database Management Systems, Data Structures & Algorithms, Data Mining, Data Analytics, Optimization and Machine Learning. 

1. A Prototype for Intelligent Coconut Harvester: An Application to Artificial Intelligence (AI) and Internet of Things (IoT) (Role: PI, Status: Ongoing, Amount:15.93 Lacks, Funding: SERB-SRG)

2. Classification and Identification of Parkinson’s Disease (PD) Patient for Proper Treatment Strategies (Role: PI, Status: Completed, Amount: 5.33 Lacks, Funding: AICTE-NPIU).

3. Monitoring Stress in Students using EEG (Role: CO-PI, Status: Completed, Amount: 15.43 Lacks, Funding: AICTE-NPIU).

4. A Framework for Patient-in-transit Healthcare Ensuring Seamless Health Data Transmission (Role: CO-PI, Status: Completed, Amount: 14.95 Lacks, Funding: AICTE-NPIU).

Academic Achievements

IEEE, ACM

DBMS CS3002D

Semester: Monsoon

Offered: 2022

DBMS Theory (CS3002D)

Semester: Monsoon

Offered: 2021

Machine Learning

Semester: Monsoon

Offered: 2021

Data Structures Lab(CS2094D)

Semester: Winter

Offered: 2021

Topics in data analytics (CS4061D)

Semester: Winter

Offered: 2021

B.Tech Project students

Machine Learning and Computational Intelligence Research Group

Introduction:

Nowadays huge amounts of data gets generated at every instance of time from heterogeneous resources. Preprocessing, analysing, discovering patterns and designing models from such a huge amount of data with higher dimensions is really a challenging task. Big data analytics, data mining, machine learning, deep learning and computational intelligence techniques can analyse and identify trends and patterns from the data. Data analytics and machine learning techniques can review and analyse  large volumes of data and discover specific trends and patterns that would not be apparent to humans.

Objectives:

• Solving real life problems by using various machine learning approaches

• Social network data analytics

• Designing classification, prediction  and machine learning models to solve real life problems

• Big data analytics

• Design and development of new optimization algorithms

• Bring more  sponsored research projects

• Collaborate with reputed Institutes, Universities, Industries and R&D Labs

Group Members:

Dr. S D Madhu Kumar, Professor, CSED, NITC

Dr. Jay prakash, Assistant Professor, CSED, NITC

Dr. Pranesh Das, Assistant Professor, CSED, NITC

Dr. Raju Hazari, Assistant Professor, CSED, NITC

M.Tech Scholars

PhD Scholars

Google Scholar Link

DBLP  Link