• Ph.D. (Computer Science & Engineering), 2017 from NSIT, University of Delhi
• M.Tech. (Computer Science Engineering), 2007-2009 from NSIT, University of Delhi
• B.Tech (Computer Science Engineering), 1998-2002 from Giani Zial Singh College of Engineering & Technology, Punjab Technical University
• 2002-2004: Lecturer (CSE), Shaheed Udham Singh College of Engineering and Technology, Mohali
• 2004-2006: Lecturer (CSE), Somany Institute of Technology & Management, Rewari
• 2006-2009: Lecturer (CSE), KIIT College of Engineering, Gurgaon
• 2009-2010: Senior Lecturer (CSE), KIIT College of Engineering, Gurgaon
• 2010-2012: Assistant Professor & Head (CSE & IT), KIIT College of Engineering, Gurgaon
• 2012-2015: Teaching cum Research Faculty (TRF), NSIT, New Delhi
• 2015- : Associate Professor (CSE), K.R. Mangalam University, Gurgaon
Ms. Parneeta Dhaliwal is working as Associate Professor in CSE Department, SOET, KRMU. Since 2002, she has taught many courses to Computer Science Engineering students at NSIT, KIIT, SITM, and SUSCET. In addition to teaching conventional CSE courses like Data Structures, Computer Architecture, and Data Mining, she has also developed various algorithms in Massive Online Analysis Tool.
She has published several research papers in International reputed Journals and International Conferences. She has given several talks in National level workshop and seminars. She has been the main organizer at International conference at KIIT College of Engineering.
1. Data Structure and Algorithms
2. Computer Architecture
3. Data Mining
4. Operating System
5. Object Oriented Programming
6. Fundamentals of Computers and Programming in C
- Data Structure and Algorithms
- Computer Architecture
- Data Mining
- Operating System
- Object Oriented Programming
- Fundamentals of Computers and Programming in C
Publication in Books:
- Sidhu Parneeta, Bhatia MPS (2014), “Extended Dynamic Weighted Majority Using Diversity to Handle Drifts”, New Trends in Databases and Information Systems, Advances in Intelligent Systems and Computing , Volume 241, 2014, pp 389-395 Springer International Publishing, DOI 10.1007/978-3-319-01863-8_41.
Publication in Conferences:
- Sidhu Parneeta, Ravi Abhishek, Malik Dhruv, Bhatia MPS (2015),” An approach to handle novel classes: Weighted Novel Class Detection Algorithm”, has been accepted for presentation in IEEE INDICON 2015 to be held in Dec. 2015, New Delhi.
- Sidhu Parneeta, Bhatia MPS, Bindal Aditya(2013), “A Novel Online Ensemble Approach for Concept Drift in Data Streams “, In Proceedings of 2nd IEEE Int’l Conf. on Image Information Processing (ICIIP),pp. 550-555, Dec, 2013.
- Sidhu Parneeta, Bhatia MPS, Bindal Aditya(2013), “Empirical support for Weighted Majority, Early Drift Detection Method and Dynamic Weighted Majority,” In Proceedings of IEEE Int’l Conf. on Machine Intelligence Research and Advancement, ICMIRA, Dec 2013.
- Sidhu Parneeta, Bhatia MPS (2012), “Online Approach to handle Concept Drifting Data Streams using Diversity” at the 7th Annual Machine Learning Symposium, New York Academy of Sciences Conference Center October 19, 2012, New York.
- Sidhu Parneeta, Bhatia MPS, Ravi Abhishek and Jherwal Kirti(2015),“ Double Weighted Methodology: A weighted ensemble approach to handle concept drift in data streams” In IEEE Proceedings of 2nd International Conference on Recent Trends in Information Systems (ReTIS) to be held in July, 2015, Kolkata.
- Sidhu Parneeta, Bhatia MPS, Bansal Priti(2010),” Survey on Techniques for Data Stream Mining,” National Conference on Emerging Trends in Computer Science and Information Technology, ETCSIT, Jan 2010.
- Bansal Priti, S. Sabharwal, Sidhu Parneeta (2009), “An Investigation of Strategies for Finding Test Order During Integration Testing of Object Oriented Applications”, In Proceedings of IEEE International Conference on Methods and Models in Computer Science, 2009.
- Sidhu Parneeta, Bhatia MPS (2015), “A novel online ensemble approach to handle concept drifting data streams: Diversified Dynamic Weighted Majority”, International Journal of Machine Learning and Cybernetics, Springer, 2015, DOI 10.1007/s13042-015-0333-x.
- Sidhu Parneeta, Bhatia MPS (2015),” An online ensembles approach for handling concept drift in data streams: diversified online ensembles detection”, International Journal of Machine Learning and Cybernetics, Springer, 2015, DOI 10.1007/s13042-015-0366-1.
- Sidhu Parneeta, Bhatia MPS,“Online Approach to handle concept drifting data streams using diversity”, has been accepted by The International Arab Journal of Information Technology.
- Sidhu Parneeta, Bhatia MPS (2015), “Empirical Support for Concept Drifting Approaches: Results Based on New Performance Metrics”, International Journal of Intelligent Systems and Applications,2015.
- Sidhu Parneeta, Bhatia MPS, Bansal Priti (2010), “A Cluster-based Approach for Outlier Detection in Dynamic Data Streams (KORM: k-median OutlieR Miner),” Journal of Computing, Volume 2, Issue 2, February 2010, https://sites. google. com/ site/journalofcomputing/
- Agarwal Priti, Sabharwal Sangeeta and Dhaliwal Parneeta (2010),” Integration Test Order For C++ Applications,” JOURNAL OF COMPUTING, VOLUME 2, ISSUE 9, SEPTEMBER 2010, ttps://sites.google.com/site/journalofcomputing/
- P. Sidhu, MPS Bhatia, “A two ensemble system to handle concept drifting data streams: Recurring Dynamic Weighted Majority “, IJMLC, Springer,Online First, pp.1-16, 2017.DOI 10.1007/s13042-017-0738-9
- P.Dhaliwal, MPS Bhatia, “Effective Handling of Recurring Concept Drifts in Data Streams”, Indian Journal of Science and Technology, Vol. 10(30), pp. 1-6, 2017.