International Conference on Computational Statistics & Big Data Analysis

Date: 27th & 28th May 2026 | Time: 8.00 am – 12:00 pm (IST) | Location: Online

Sample Abstract

Phone: 8977760443 Email: support@onegrasp.com

Overview

The International Conference on Computational Statistics & Big Data Analysis offers an interactive platform for statisticians, data scientists, and computational experts to explore the intersection of statistical methodology, data analytics, and high-performance computing. The conference emphasizes algorithmic advances, scalable modeling, and data-driven innovation in managing, processing, and interpreting large datasets across disciplines. It aims to promote collaboration in developing efficient analytical techniques and computational frameworks for tackling complex problems in science, business, and technology.

Structure and Sessions (Who Does What)

Inaugural Session: Opening remarks by the Conference Chair and keynote on “The Evolution of Computational Statistics in the Age of Big Data.”
Technical Paper Sessions: Research presentations addressing statistical computing, big data processing, predictive analytics, and algorithmic development.
Panel Discussion: Interdisciplinary debate among industry and academic experts on challenges in large-scale data analysis and computation.
Student & Research Forum: Early-career researchers present computational models, frameworks, and applications leveraging big data.
Closing Session: Recognition of participants through certificates, mementos, and best paper awards followed by concluding remarks.

Participate and Contribute (Who Benefits)

Professionals and academicians in statistics, data analytics, and computer science.
Researchers from industry and academia focusing on machine learning, scientific computing, and statistical modeling.
Students and innovators engaged in algorithmic design and big data-driven experimentation.
Participants benefit from networking, research publication, and global exposure to industrial applications and academic breakthroughs in computational data science.

Benefits for Attendees

Certificate of participation (based on feedback submission)
Memento for presenters and moderators
Publication of accepted abstracts in indexed conference proceedings (Scopus/WoS/Elsevier/Sci as applicable)

Abstract Topics / Call for Papers (CFP) Tracks

Computational Statistics and Algorithmic Methods
Big Data Analytics and Scalable Computing
Machine Learning and Artificial Intelligence Applications
High-Dimensional Data Analysis
Statistical Simulation and Monte Carlo Methods
Cloud-Based and Parallel Computing in Statistics
Predictive Modeling and Statistical Learning
Numerical Optimization and Data Mining
Bayesian Computation and Inference Techniques
Statistical Visualization and Data Communication
Big Data in Healthcare, Finance, and Environment
Ethics, Privacy, and Reproducibility in Data Analytics

Detailed Program Grid

Time (IST)	Day 1	Day 2
08:00 – 08:15	Opening Ceremony & Welcome	Recap and Opening Remarks
08:15 – 09:00	Keynote: Computational Challenges in Big Data Analytics	Keynote: Future Frontiers in Statistical Computing
09:00 – 10:15	Technical Session I – Statistical Computing and Algorithms	Technical Session IV – Applied Big Data Analytics
10:15 – 10:30	Break	Break
10:30 – 11:15	Technical Session II – Simulation, Inference & Optimization	Technical Session V – Machine Learning & Computational Applications
11:15 – 11:45	Panel Discussion: Integrating Data Science and Computation	Student & Research Forum: Innovative Data Science Projects
11:45 – 12:00	Day Summary & Announcements	Awards & Closing Ceremony

Submit Abstract & Registration

Conference Dates	Conference Title	Timing (IST)	Abstract Submission Deadline	Registration Deadline
27th, 28th May 2026	International Conference on Computational Statistics & Big Data Analysis	8:00 AM – 12:00 PM	18th May 2026	20th May 2026

Abstract Guidelines

Word Count: 300–350 words (including title, author(s), affiliation, email, and 5 keywords)
Font: Times New Roman, 12 pt, 1.5 spacing
File Format: .doc or .docx only
All submissions will undergo double-blind peer review before acceptance

Conclusion

This international conference highlights leading-edge developments in computational statistics and large-scale data analysis. Participants will engage in discussions on emerging algorithms, analytics frameworks, and data modeling techniques, contributing to a deeper understanding of how computation drives advanced research and informed decision-making across sectors.

Registration

Type of participation

Early Bird Registration

April 22, 2026

Mid Registration Deadline

May 6, 2026

Late Registration Deadline

May 20, 2026

No. of Participants ($159 each under Speaker / Poster (Virtual)) :

No of Accompanying Persons ($ 200 each )

Registration Summary

Registration Price (Per Person - Speaker / Poster (Virtual)):

$159

Participants:

Total Registration Price:

$159

Total Price:

$159

By clicking "Proceed to Pay", you agree to the privacy policy, terms & conditions and cancellation policy.

Note: For more information on registration queries, please contact: support@onegrasp.com

Registration includes:

For In-person attendees

Entry to all conference sessions, poster presentations, and the exhibition area
Conference kit comprising a name tag, program booklet, and abstract book
Two coffee breaks and lunch are provided for each day of the conference
Accreditation Certificate issued by the Organizing Committee

For Virtual Attendees

This category enables participants to present virtually at the conference from the convenience of their home or workplace without the need for in-person attendance. It includes:

Access to all presentations
An E-abstract book and program
An E-certificate for presentation and participation
A CPD (Continuous Professional Development) Certificate with Credits

Terms and Conditions

By enrolling in the conference, you hereby express your acceptance of the terms and conditions stated herewith.

The organization retains the authority to modify the program, date, and/or location at its discretion, without prior notification.

The organization cannot be held accountable for any loss or damage incurred due to substitutions, adjustments, delays, or cancellations of an event caused by unforeseen factors beyond its control. Such factors encompass, but are not limited to, force majeure, natural disasters, acts of sabotage, accidents, labor disputes, acts of terrorism, strikes, or hostilities.

The organization reserves the right and possesses the exclusive discretion to cancel any conference at any time under circumstances that are unavoidable and unanticipated. The organizer will not assume any additional liability towards the participant.

Registrations will remain valid for rescheduled events or future editions if the conference must be postponed due to circumstances beyond the organizer's control. Refund policies do not apply under these conditions.

In the instance of cancellation, the organization will make reasonable and appropriate alternative arrangements, which may include posting the cancellation notice on the relevant event website to inform those who have secured bookings or purchased tickets for the event.

Attendees are responsible for reviewing this information before the event. We strongly recommend regularly checking the conference website for updates.

The organizers shall not be held responsible for personal injuries or for the loss or damage to personal belongings of attendees, either during the conference.

Important COVID-19 Update for Participants

In case of any natural calamities, those who are unable to attend in person due to travel restrictions or health concerns, enable your virtual participation. Details on accessing the virtual platform will be provided 2 months prior to the conference. And on your request the registration will transfer to future editions.

We will provide regular updates on the conference website regarding any changes to the event format, health and safety measures, and other relevant information. Please check the website periodically for the latest updates.