My Role: General Chair
ISEC is the annual conference of iSOFT, the India chapter of ACM SIGSOFT India. The 16th edition of the conference will be held at IIIT Allahabad, India. The goal of the conference is to provide a forum for researchers and practitioners from both academia and industry to meet and share research problems, experiences, and cutting-edge advancements in the field of software and systems engineering. ISEC2023 invites the submission of technical papers describing original and unpublished results of foundational, theoretical, empirical, and applied software and systems engineering research. See more……..
My Role: General Chair
ICONIP 2022 is the International Conference on Neural Information Processing (ICONIP) is an annual conference that brings together researchers from different countries in the fields of pattern recognition, neuroscience, intelligent control, information security and brain-machine interface to exchange ideas and discuss possible collaborations. Global researchers interested in collaboration with colleagues from South Asia are also most welcome. ICONIP is the annual flagship conference organized by the Asia Pacific Neural Network Society (APNNS). The mission of the Asia-Pacific Neural Network Society is to promote active interactions among researchers, scientists, and industry professionals who are working in Neural Networks and related fields in the Asia-Pacific region. The 29th ICONIP 2022 aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progresses and achievements. The ICONIP 2022 will include keynotes, tutorials, workshops, special sessions and regular research paper presentations, etc. See more….
Five days GIAN course on “Learning from Data Streams” UPCOMING
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:
- Exposing participants to the fundamentals of Data Stream.
- Identifying common patterns and use cases for real time stream processing.
- Vast coverage and exposure to various algorithmic techniques such as data stream clustering, ubiquitous data mining, pattern mining, novelty detection with the aim to encourage participants for future research in this field.
- Understand the high level architecture of data streaming tools such as Massive Online Analysis (MOA), Apache Spark and Apache Flink.
- Since real time stream processing is having very wider applicability, therefore this course is aimed at the more general audience including mathematician, statistician, and computer scientists, electrical and electronic engineer.
My Role: General Chair
The 9th International Conference on Big Data Analytics (BDA 2021) will be held online during December 15-18, 2021. The conference will be organized by Indian Institute of Information Technology Allahabad, India. BDA 2021 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: 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 ….
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: Organizing 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-Organizer
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-Organizer
Special 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: Organizer
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:
- Introduce the student to use cases of stream processing, the data stream model and graph stream model
- Present algorithmic techniques for graph stream processing, including random sampling, graph sketches, and merge-and-reduce.
- Show their application to problems such as subgraph counting, graph connectivity, random sampling from graphs, graph matchings, etc
- Present current techniques on monitoring parallel and distributed streams, including algorithms in the continuous distributed monitoring model, and the parallel streaming model
- Provide practical perspective on building software for stream processing
- Provide experience with an open source tool, Apache Flink
For more information… click here