My Role: Publicity Co-Chair
The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is one longest established and leading international conferences in the areas of data mining and knowledge discovery. It will be organized in Delhi during May 10-14, 2021 by both JNU and IIIT Hyderabad. It provides an international forum for researchers and industry practitioners to share their latest developments, new ideas, original research results and practical development experiences from all KDD related areas including data mining, statistical and symbolic machine learning, databases, knowledge acquisition and automatic scientific discovery, data visualization, and knowledge-based systems. See more ....
My Role: Publicity Co-Chair
The 8th International Conference on Big Data Analytics (BDA 2020) will be held during December 15-18, 2020 at Ashoka University, India. The conference will be organized by Ashoka University. BDA 2020 provides an international forum for researchers and industry practitioners to share their original research results, practical experiences and thoughts on big data from different perspectives including storage models, data access, computing paradigms, analytics, information sharing and privacy, redesigning mining algorithms, open issues and future research trends. See more ....
My Role: Technical Program Chair
The 3rd International Conference on Machine Intelligence and Signal Processing (MISP) 2021 will be organized by Sri Lanka Technological Campus (SLTC) on January 23-24, 2021. This conference will be conducted online giving a platform for researchers all over the globe interested in the areas of data mining, artificial intelligence, optimization, machine learning methods/ algorithms, signal processing theory and methods, and applications to human brain disorders like epilepsy, Alzheimer, sleep disorders etc. Other applications of machine learning and signal processing techniques are also welcome. See more ....
Five days GIAN course on "Learning from Data Streams"
My Role: Host faculty
Today an enormous amount of data is coming from various sources like sensor networks, financial transactions, traffic monitoring, sets of web pages, etc. in the form of data streams. The volume of data is rapidly increasing due to the development of information and communication technologies. Data comes mostly in the form of streams. Learning from this ever-growing amount of data requires flexible learning models that self-adapt over time. In addition, these models must take into account many constraints: real-time processing, high-velocity, and dynamic multi-form change such as concept drift and novelty. This course on Learning from Data Streams focuses on recent techniques and software for real-time processing of data streams. The primary objectives of the course are as follows:
IEEE CIS Summer School 2019 "Big Data Analytics and Stream Processing:Tools, Techniques and Application"
My Role:Course Coordinator
In today's world, Big data analytics and stream processing have taken great hype due to the digitization of the environment along with the integration of smart data computing services and interconnectivity. This digitized world offers huge applications especially in the fields of agriculture, healthcare, smart education, economy, energy, industry, and a lot more. Most of the required data is gathered by the countless number of sensor devices being applied in the vicinity of humans to identify certain activities or scenarios. In order to process such a huge never-ending stream of data, there is a need to re-think the way data is processed for both cases i.e. data-at-rest and data-in-motion. In order to have knowledge about the latest trend in this field, the IEEE CIS Summer School on Big data analytics and stream processing was aimed at highlighting the tools, techniques, and applications from the perspective of future intensive applications. To serve this purpose, this IEEE CIS Summer School featured a large number of keynote speakers/plenary/invited talks on advanced topics and also offered a good platform for the participants for the innovative and entrepreneurial ideas. See more ....
My Role: Organising Chair
The International Conference on Machine Intelligence and Signal Processing (MISP-2019) was held at Indian Institute of Information Technology, Allahabad, India, on September 7-10, 2019. This conference was meant for researchers all over the globe interested in the areas of data mining, artificial intelligence, optimization, machine learning methods/ algorithms, signal processing theory and methods, and applications to human brain disorders like epilepsy, Alzheimer, sleep disorders etc. Other applications of machine learning and signal processing techniques wered also welcome. See more ....
Special Session on "Non-parallel Support Vector Machine Classifiers" at IEEE SMC 2019, Bari, Italy.
My Role: Co-Organiser
This special session aimed to bring together the current research progress (from both academia and industry) on novel non-parallel support vector machine classifiers to address above mentioned challenges. Further, this special session also provided insight about other viable alternatives for researcher (especially from industry) who extensively need classifiers but lack the expertise in using machine learning techniques effectively. . For more information click here
Special Session on "Computational intelligence for biomedical data and imaging" in IEEE SSCI 2018)at Bengaluru, India during November 18-21, 2018.
My Role: Co-Organiser
pecial Session on "Computational intelligence for biomedical data and imaging" in IEEE SSCI 2018)at Bengaluru, India during November 18-21, 2018. This special session aimed to bring together the current research progress (from both academia and industry) on novel machine learning methods to address the challenges to biomedical complex data. Special attention also devoted to handle feature selection, class imbalance, and data fusion in biomedical and machine learning applications. It was aimed to attract medical experts who have access to interesting sources of data but lack the expertise in using machine learning techniques effectively. For more information click here
"Real-Time Stream Analytics and Machine Learning for Cyber-Physical Systems (RTSML4CPS)".
My Role: Organiser
This proposed workshop was be hosted in conjunction with the International Conference on Distributed Computing and Networking (ICDCN 2018) at IIT BHU During January 4-7, 2018. click here
GIAN course on "Parallel and Distributed Data Stream Mining", December 18- 22, 2017.
My Role: Course Coordinator and Instructor
Data is being continuously collected from a variety of sensor sources, such as Twitter feeds, news streams, and environmental sensors. It is a significant challenge to continuously monitor such data and derive insights in a timely manner. This course on data stream analysis focused on methods and software for deriving patterns and aggregates from data streams in real-time. The course was focus on (1) Parallel and distributed methods for data stream mining, (2) Methods for mining from graphical data, where each stream item represents a relationship between entities. Objectives
The main objectives of the course were: