Unleashing India's Financial Potential with AI & Data Science
Shaping India's Financial Future: The Power of AI and Data Science
Join us at the DSA Conference in Taj Exotica Resort & Spa, Goa, India, for a transformative exploration of India's financial future. This exclusive gathering brings together leading experts from around the globe to delve into the groundbreaking potential of AI and data science in driving financial innovation and growth.
Nestled amidst the picturesque Goan coastline, Taj Exotica Resort & Spa offers a luxurious and serene setting for this groundbreaking conference. Immerse yourself in thought-provoking discussions, interactive workshops, and networking opportunities as we forge a path toward a more prosperous and technologically advanced financial landscape.
We aim to foster a collaborative environment where innovative ideas can flourish and drive financial success.
A Data-Driven Revolution: Shaping the Future of Finance
Whether you're a seasoned data scientist, financial executive, policy maker, financial regulator, banker or investor, this conference offers an unparalleled opportunity to expand your knowledge and network with industry leaders. Explore the intersection of data science, AI, and global finance at our exclusive gathering.
Key Highlights:
Expert Insights: Learn from renowned experts in data science, AI, investing, and finance.
Cutting-Edge Research: Discover the latest advancements in data-driven insights and their applications to global finance.
Thought-Provoking Discussions: Engage in interactive sessions on critical topics shaping the future of the field.
Networking Opportunities: Connect with like-minded professionals from around the world.
Conference Themes:
AI and Data Science in Finance
Scenario Planning and Risk Management
Central Bank Policy and Global Markets
Emerging Markets and the BRICS
US Dollar Scenarios and Global Financial Risks
Blockchain Technology and its Impact on Finance
Unforgettable Experience:
The Taj Exotica Resort & Spa, Goa, provides a luxurious and inspiring setting for this transformative conference. Enjoy the stunning natural beauty, rich cultural heritage, and world-class amenities while connecting with industry peers and shaping the future of finance.
Join us at the DSA Conference in Taj Exotica Resort & Spa, Goa, India, for a transformative exploration of India's financial future. This exclusive gathering brings together leading experts from around the globe to delve into the groundbreaking potential of AI and data science in driving financial innovation and growth.
Nestled amidst the picturesque Goan coastline, Taj Exotica Resort & Spa offers a luxurious and serene setting for this groundbreaking conference. Immerse yourself in thought-provoking discussions, interactive workshops, and networking opportunities as we forge a path toward a more prosperous and technologically advanced financial landscape.
We aim to foster a collaborative environment where innovative ideas can flourish and drive financial success.
A Data-Driven Revolution: Shaping the Future of Finance
Whether you're a seasoned data scientist, financial executive, policy maker, financial regulator, banker or investor, this conference offers an unparalleled opportunity to expand your knowledge and network with industry leaders. Explore the intersection of data science, AI, and global finance at our exclusive gathering.
Key Highlights:
Expert Insights: Learn from renowned experts in data science, AI, investing, and finance.
Cutting-Edge Research: Discover the latest advancements in data-driven insights and their applications to global finance.
Thought-Provoking Discussions: Engage in interactive sessions on critical topics shaping the future of the field.
Networking Opportunities: Connect with like-minded professionals from around the world.
Conference Themes:
AI and Data Science in Finance
Scenario Planning and Risk Management
Central Bank Policy and Global Markets
Emerging Markets and the BRICS
US Dollar Scenarios and Global Financial Risks
Blockchain Technology and its Impact on Finance
Unforgettable Experience:
The Taj Exotica Resort & Spa, Goa, provides a luxurious and inspiring setting for this transformative conference. Enjoy the stunning natural beauty, rich cultural heritage, and world-class amenities while connecting with industry peers and shaping the future of finance.
We are in the process of finalizing dates and details.
Sign up for updates - dates & details coming soon - secure your spot at this exclusive event!
Sign up for updates - dates & details coming soon - secure your spot at this exclusive event!
Investors: Individuals and institutions looking to improve decision-making using data science techniques and data-driven financial technologies.
Traders: Professionals involved in buying and selling financial instruments, who can benefit from AI-powered trading strategies and tools.
AI and Data Science Professionals:
Data Scientists
AI/Machine Learning Engineers
AI Researchers
Software Engineers
Product Managers
UX Designers
Financial professionals interested in AI and data-driven insights: Anyone working in the financial industry who wants to stay up-to-date on the latest trends and innovations.
Government Officials and Regulators Involved in Financial Technology Policy: Policymakers and regulators shaping the regulatory landscape for AI-driven financial services.
Financial Regulators: Policymakers responsible for overseeing the financial industry can benefit from understanding the implications of AI and data science on financial stability, consumer protection, and market integrity.
Central Bankers: Monetary authorities can leverage AI and data science to improve forecasting, risk management, and monetary policy implementation.
Entrepreneurs and investors in the FinTech space: Individuals involved in starting and funding new financial technology companies.
Academics and researchers studying the intersection of finance and technology: Scholars and researchers exploring the theoretical and practical aspects of AI in finance.
Economists: Researchers and analysts can explore the economic implications of AI-driven financial innovation, including its impact on growth, employment, and inequality.
Actuaries: Professionals involved in risk assessment and pricing can use AI and data science to improve their models and enhance risk management practices.
Insurance Professionals: Insurance companies can benefit from AI and data science to improve underwriting, claims processing, and fraud detection.
Accountants: Accountants can leverage AI and data science to streamline processes, enhance audit quality, and gain deeper insights into financial data.
Traders: Professionals involved in buying and selling financial instruments, who can benefit from AI-powered trading strategies and tools.
AI and Data Science Professionals:
Data Scientists
AI/Machine Learning Engineers
AI Researchers
Software Engineers
Product Managers
UX Designers
Financial professionals interested in AI and data-driven insights: Anyone working in the financial industry who wants to stay up-to-date on the latest trends and innovations.
Government Officials and Regulators Involved in Financial Technology Policy: Policymakers and regulators shaping the regulatory landscape for AI-driven financial services.
Financial Regulators: Policymakers responsible for overseeing the financial industry can benefit from understanding the implications of AI and data science on financial stability, consumer protection, and market integrity.
Central Bankers: Monetary authorities can leverage AI and data science to improve forecasting, risk management, and monetary policy implementation.
Entrepreneurs and investors in the FinTech space: Individuals involved in starting and funding new financial technology companies.
Academics and researchers studying the intersection of finance and technology: Scholars and researchers exploring the theoretical and practical aspects of AI in finance.
Economists: Researchers and analysts can explore the economic implications of AI-driven financial innovation, including its impact on growth, employment, and inequality.
Actuaries: Professionals involved in risk assessment and pricing can use AI and data science to improve their models and enhance risk management practices.
Insurance Professionals: Insurance companies can benefit from AI and data science to improve underwriting, claims processing, and fraud detection.
Accountants: Accountants can leverage AI and data science to streamline processes, enhance audit quality, and gain deeper insights into financial data.
Financial Scenario Planning, Modeling and Prediction
Keynote: A renowned financial expert discussing the transformative impact of data science and AI on scenario planning, financial modeling and predictive analytics.
Panel Discussion: Industry leaders debating the ethical implications of AI-driven financial predictions.
Workshops: Hands-on sessions on time series analysis, risk analysis and modeling, and sentiment analysis.
Lightning Talks: Short presentations on innovative research and applications in this area.
Algorithmic Trading and Investment Strategies
Case Studies: Real-world examples of successful AI-powered trading strategies.
Algorithm Investment & Trading: How to develop innovative investment and trading algorithms.
Roundtable Discussions: Exploring the challenges and opportunities of high-frequency trading.
Fireside Chat: A conversation with a prominent hedge fund manager on the future of AI in finance.
Financial Technology (FinTech) and Innovation
Startup Showcase: Presentations from promising FinTech startups.
Investor Panel: Discussions on funding trends and investment opportunities in FinTech.
Regulatory Roundtable: Exploring the regulatory landscape for AI-driven financial services.
Future Trends Session: Experts sharing their vision for the future of FinTech and its impact on society.
Optional Conference Topics
Data Science & AI in Global Finance & Investing: Explore the transformative power of data science and artificial intelligence in revolutionizing global finance and investing. Delve into cutting-edge applications such as data science and AI-powered investment decision making, algorithmic trading, risk assessment, fraud detection, and portfolio optimization.
Central Banks Policy: Gain insights into the evolving landscape of central bank policies worldwide. Analyze the impact of monetary policies, quantitative easing, and interest rate adjustments on global financial markets and economic stability.
Emerging Markets Investing: Discover the opportunities and challenges presented by emerging markets. Understand the factors driving growth, assess investment risks, and explore strategies for navigating these dynamic economies.
BRICS Policy: Examine the collective influence of the BRICS nations (Brazil, Russia, India, China, and South Africa) on the global financial landscape. Analyze their economic policies, trade relations, and geopolitical dynamics.
US Dollar Scenarios: Evaluate the future trajectory of the US dollar as the world's reserve currency. Consider potential scenarios, including its appreciation, depreciation, or a shift towards a multipolar currency system.
Blockchain Technology: Explore the disruptive potential of blockchain technology in finance. Discuss its applications in areas such as cryptocurrency, smart contracts, decentralized finance (DeFi), and supply chain management.
Global Financial Risk: Identify and assess emerging global financial risks, including geopolitical tensions, climate change, cyber threats, and systemic failures. Develop strategies for mitigating these risks and building resilience.
Additional Conference Features
Networking Events: Social gatherings and receptions to facilitate connections among attendees.
Workshops and Tutorials: Hands-on training sessions for attendees of varying skill levels.
Keynote: A renowned financial expert discussing the transformative impact of data science and AI on scenario planning, financial modeling and predictive analytics.
Panel Discussion: Industry leaders debating the ethical implications of AI-driven financial predictions.
Workshops: Hands-on sessions on time series analysis, risk analysis and modeling, and sentiment analysis.
Lightning Talks: Short presentations on innovative research and applications in this area.
Algorithmic Trading and Investment Strategies
Case Studies: Real-world examples of successful AI-powered trading strategies.
Algorithm Investment & Trading: How to develop innovative investment and trading algorithms.
Roundtable Discussions: Exploring the challenges and opportunities of high-frequency trading.
Fireside Chat: A conversation with a prominent hedge fund manager on the future of AI in finance.
Financial Technology (FinTech) and Innovation
Startup Showcase: Presentations from promising FinTech startups.
Investor Panel: Discussions on funding trends and investment opportunities in FinTech.
Regulatory Roundtable: Exploring the regulatory landscape for AI-driven financial services.
Future Trends Session: Experts sharing their vision for the future of FinTech and its impact on society.
Optional Conference Topics
Data Science & AI in Global Finance & Investing: Explore the transformative power of data science and artificial intelligence in revolutionizing global finance and investing. Delve into cutting-edge applications such as data science and AI-powered investment decision making, algorithmic trading, risk assessment, fraud detection, and portfolio optimization.
Central Banks Policy: Gain insights into the evolving landscape of central bank policies worldwide. Analyze the impact of monetary policies, quantitative easing, and interest rate adjustments on global financial markets and economic stability.
Emerging Markets Investing: Discover the opportunities and challenges presented by emerging markets. Understand the factors driving growth, assess investment risks, and explore strategies for navigating these dynamic economies.
BRICS Policy: Examine the collective influence of the BRICS nations (Brazil, Russia, India, China, and South Africa) on the global financial landscape. Analyze their economic policies, trade relations, and geopolitical dynamics.
US Dollar Scenarios: Evaluate the future trajectory of the US dollar as the world's reserve currency. Consider potential scenarios, including its appreciation, depreciation, or a shift towards a multipolar currency system.
Blockchain Technology: Explore the disruptive potential of blockchain technology in finance. Discuss its applications in areas such as cryptocurrency, smart contracts, decentralized finance (DeFi), and supply chain management.
Global Financial Risk: Identify and assess emerging global financial risks, including geopolitical tensions, climate change, cyber threats, and systemic failures. Develop strategies for mitigating these risks and building resilience.
Additional Conference Features
Networking Events: Social gatherings and receptions to facilitate connections among attendees.
Workshops and Tutorials: Hands-on training sessions for attendees of varying skill levels.
Taj Exotica Resort & Spa, Goa is a luxurious beachfront resort nestled in the southern Indian state of Goa. Renowned for its opulent accommodations, world-class amenities, and stunning views of the Arabian Sea, this resort offers a serene and indulgent getaway. With its pristine private beach, state-of-the-art spa, and a variety of recreational activities, Taj Exotica provides an unforgettable experience for travelers seeking relaxation, luxury, and cultural immersion.
The Taj Exotica Resort offers a variety of adventures for guests to enjoy:
Beach Adventures: The resort has a private beach where guests can swim, sunbathe, play volleyball, or try water sports like kayaking, windsurfing, or parasailing.
Spa and Wellness: The resort's Jiva Spa offers a variety of treatments, including Ayurvedic massages, yoga, and meditation.
Cultural Experiences: Guests can learn about Goan culture through cooking classes, cultural performances, or guided tours to local attractions.
Fitness and Recreation: The resort has a fitness center, swimming pool, tennis court, and table tennis.
Nature Walks: Guests can take guided nature walks through the nearby forests and learn about the local flora and fauna.
The Taj Exotica Resort offers a variety of adventures for guests to enjoy:
Beach Adventures: The resort has a private beach where guests can swim, sunbathe, play volleyball, or try water sports like kayaking, windsurfing, or parasailing.
Spa and Wellness: The resort's Jiva Spa offers a variety of treatments, including Ayurvedic massages, yoga, and meditation.
Cultural Experiences: Guests can learn about Goan culture through cooking classes, cultural performances, or guided tours to local attractions.
Fitness and Recreation: The resort has a fitness center, swimming pool, tennis court, and table tennis.
Nature Walks: Guests can take guided nature walks through the nearby forests and learn about the local flora and fauna.
This conference will bring together financial professionals, data scientists, AI engineers, investors, traders and policymakers to explore the transformative impact of Artificial Intelligence and Data Science on the financial sector, with a specific focus on the unique landscape of India.
We invite submissions for presentations, papers, workshops, and lightning talks across a range of compelling topics. We encourage submissions that present original research, innovative applications, case studies, and insightful analyses.
Main Conference Subject Areas
Financial Scenario Planning, Modeling and Prediction
This track will delve into the critical role of AI and data science in enhancing financial foresight. We seek contributions on:
Keynote: Submissions are invited for a keynote address by a renowned financial expert discussing the transformative impact of data science and AI on scenario planning, financial modeling, and predictive analytics.
Panel Discussion: Proposals for participation in a panel debate among industry leaders on the ethical implications of AI-driven financial predictions.
Workshops: Hands-on sessions focusing on advanced techniques in time series analysis, robust risk analysis and modeling, and sophisticated sentiment analysis for financial markets.
Lightning Talks: Short, impactful presentations on innovative research and novel applications within financial scenario planning, modeling, and prediction.
Algorithmic Trading and Investment Strategies
This track will explore the cutting-edge of automated trading and investment methodologies. We are particularly interested in:
Case Studies: Real-world examples demonstrating successful AI-powered trading strategies and their measurable outcomes.
Algorithm Investment & Trading: Presentations detailing the development of innovative investment and trading algorithms, including methodologies, backtesting results, and performance analysis.
Roundtable Discussions: Proposals for discussions exploring the challenges and opportunities presented by high-frequency trading, including regulatory considerations and market impact.
Fireside Chat: Submissions for a conversation with a prominent hedge fund manager on the future of AI in finance and its long-term implications for investment management.
Financial Technology (FinTech) and Innovation
This track will showcase the latest advancements and disruptive forces in financial technology. We welcome submissions related to:
Startup Showcase: Presentations from promising FinTech startups highlighting their innovative solutions and business models.
Investor Panel: Discussions on current funding trends, emerging investment opportunities, and challenges within the FinTech ecosystem.
Regulatory Roundtable: Exploring the evolving regulatory landscape for AI-driven financial services, including data privacy, compliance, and consumer protection.
Future Trends Session: Experts sharing their vision for the future of FinTech, its potential societal impact, and emerging technological paradigms.
Optional Conference Topics
In addition to the main subject areas, we also welcome submissions on the following optional, yet highly relevant, topics:
Data Science & AI in Global Finance & Investing: Explore the transformative power of data science and artificial intelligence in revolutionizing global finance and investing. Delve into cutting-edge applications such as data science and AI-powered investment decision-making, algorithmic trading, risk assessment, fraud detection, and portfolio optimization.
Central Banks Policy: Gain insights into the evolving landscape of central bank policies worldwide. Analyze the impact of monetary policies, quantitative easing, and interest rate adjustments on global financial markets and economic stability.
Emerging Markets Investing: Discover the opportunities and challenges presented by emerging markets. Understand the factors driving growth, assess investment risks, and explore strategies for navigating these dynamic economies.
BRICS Policy: Examine the collective influence of the BRICS nations (Brazil, Russia, India, China, and South Africa) on the global financial landscape. Analyze their economic policies, trade relations, and geopolitical dynamics.
US Dollar Scenarios: Evaluate the future trajectory of the US dollar as the world's reserve currency. Consider potential scenarios, including its appreciation, depreciation, or a shift towards a multipolar currency system.
Blockchain Technology: Explore the disruptive potential of blockchain technology in finance. Discuss its applications in areas such as cryptocurrency, smart contracts, decentralized finance (DeFi), and supply chain management.
Global Financial Risk: Identify and assess emerging global financial risks, including geopolitical tensions, climate change, cyber threats, and systemic failures. Develop strategies for mitigating these risks and building resilience.
Submission Types
We invite submissions across several categories to accommodate diverse contributions:
Oral Presentations (20 minutes): Share your research findings, innovative applications, case studies, or best practices.
Technical Papers (Full Length, 8-12 pages, IEEE format): Submit original, unpublished research that undergoes a rigorous peer-review process. Accepted papers will be published in the conference proceedings.
Experience & Insight Papers (4-6 pages, formatted for readability): This category is designed for practitioners, industry leaders, and innovators to share valuable lessons learned, practical case studies, real-world implementations, and insightful perspectives. These papers should focus on practical applications, best practices, and actionable insights that can benefit the broader community, even if they do not present novel research methodologies or extensive theoretical contributions. Submissions will undergo a peer-review process focused on clarity, relevance, and the practical value of the shared experiences.
Poster Presentations: Showcase preliminary results, ongoing research, or innovative concepts visually. Includes a dedicated poster session for discussion.
Panel Proposals (60 minutes): Suggest and moderate a discussion among 3-5 experts on a controversial, emerging, or complex topic in finance.
Workshop Proposals (60 minutes): Propose an interactive, hands-on session focused on practical skills, tools, or methodologies.
Submission Guidelines
Abstract: All submissions (except workshop proposals) must include a concise abstract (maximum 300 words) summarizing the problem, approach, key findings/insights, and conclusions.
Author Information: Include full names, affiliations, and a brief professional biography (max 100 words per author).
Keywords: Provide 3-5 relevant keywords.
Originality: Submissions must represent original work that has not been previously published or is not under review elsewhere.
Audience Consideration: Presenters should be prepared to convey complex technical or business concepts clearly to a diverse audience, including both technical and non-technical attendees.
Formatting: Specific formatting guidelines for full papers will be provided upon submission portal opening.
Review Process
All submissions will undergo a rigorous peer-review process by the Program Committee, comprising leading experts in AI, data science, and related business domains. Submissions will be evaluated based on:
Relevance to conference themes
Originality and novelty of contributions
Technical merit and soundness (for technical papers)
Clarity, organization, and presentation quality
Potential impact and practical applicability
Further details on submission deadlines and the submission portal will be provided on the conference website. We encourage early submissions.
We look forward to your valuable contributions!
We invite submissions for presentations, papers, workshops, and lightning talks across a range of compelling topics. We encourage submissions that present original research, innovative applications, case studies, and insightful analyses.
Main Conference Subject Areas
Financial Scenario Planning, Modeling and Prediction
This track will delve into the critical role of AI and data science in enhancing financial foresight. We seek contributions on:
Keynote: Submissions are invited for a keynote address by a renowned financial expert discussing the transformative impact of data science and AI on scenario planning, financial modeling, and predictive analytics.
Panel Discussion: Proposals for participation in a panel debate among industry leaders on the ethical implications of AI-driven financial predictions.
Workshops: Hands-on sessions focusing on advanced techniques in time series analysis, robust risk analysis and modeling, and sophisticated sentiment analysis for financial markets.
Lightning Talks: Short, impactful presentations on innovative research and novel applications within financial scenario planning, modeling, and prediction.
Algorithmic Trading and Investment Strategies
This track will explore the cutting-edge of automated trading and investment methodologies. We are particularly interested in:
Case Studies: Real-world examples demonstrating successful AI-powered trading strategies and their measurable outcomes.
Algorithm Investment & Trading: Presentations detailing the development of innovative investment and trading algorithms, including methodologies, backtesting results, and performance analysis.
Roundtable Discussions: Proposals for discussions exploring the challenges and opportunities presented by high-frequency trading, including regulatory considerations and market impact.
Fireside Chat: Submissions for a conversation with a prominent hedge fund manager on the future of AI in finance and its long-term implications for investment management.
Financial Technology (FinTech) and Innovation
This track will showcase the latest advancements and disruptive forces in financial technology. We welcome submissions related to:
Startup Showcase: Presentations from promising FinTech startups highlighting their innovative solutions and business models.
Investor Panel: Discussions on current funding trends, emerging investment opportunities, and challenges within the FinTech ecosystem.
Regulatory Roundtable: Exploring the evolving regulatory landscape for AI-driven financial services, including data privacy, compliance, and consumer protection.
Future Trends Session: Experts sharing their vision for the future of FinTech, its potential societal impact, and emerging technological paradigms.
Optional Conference Topics
In addition to the main subject areas, we also welcome submissions on the following optional, yet highly relevant, topics:
Data Science & AI in Global Finance & Investing: Explore the transformative power of data science and artificial intelligence in revolutionizing global finance and investing. Delve into cutting-edge applications such as data science and AI-powered investment decision-making, algorithmic trading, risk assessment, fraud detection, and portfolio optimization.
Central Banks Policy: Gain insights into the evolving landscape of central bank policies worldwide. Analyze the impact of monetary policies, quantitative easing, and interest rate adjustments on global financial markets and economic stability.
Emerging Markets Investing: Discover the opportunities and challenges presented by emerging markets. Understand the factors driving growth, assess investment risks, and explore strategies for navigating these dynamic economies.
BRICS Policy: Examine the collective influence of the BRICS nations (Brazil, Russia, India, China, and South Africa) on the global financial landscape. Analyze their economic policies, trade relations, and geopolitical dynamics.
US Dollar Scenarios: Evaluate the future trajectory of the US dollar as the world's reserve currency. Consider potential scenarios, including its appreciation, depreciation, or a shift towards a multipolar currency system.
Blockchain Technology: Explore the disruptive potential of blockchain technology in finance. Discuss its applications in areas such as cryptocurrency, smart contracts, decentralized finance (DeFi), and supply chain management.
Global Financial Risk: Identify and assess emerging global financial risks, including geopolitical tensions, climate change, cyber threats, and systemic failures. Develop strategies for mitigating these risks and building resilience.
Submission Types
We invite submissions across several categories to accommodate diverse contributions:
Oral Presentations (20 minutes): Share your research findings, innovative applications, case studies, or best practices.
Technical Papers (Full Length, 8-12 pages, IEEE format): Submit original, unpublished research that undergoes a rigorous peer-review process. Accepted papers will be published in the conference proceedings.
Experience & Insight Papers (4-6 pages, formatted for readability): This category is designed for practitioners, industry leaders, and innovators to share valuable lessons learned, practical case studies, real-world implementations, and insightful perspectives. These papers should focus on practical applications, best practices, and actionable insights that can benefit the broader community, even if they do not present novel research methodologies or extensive theoretical contributions. Submissions will undergo a peer-review process focused on clarity, relevance, and the practical value of the shared experiences.
Poster Presentations: Showcase preliminary results, ongoing research, or innovative concepts visually. Includes a dedicated poster session for discussion.
Panel Proposals (60 minutes): Suggest and moderate a discussion among 3-5 experts on a controversial, emerging, or complex topic in finance.
Workshop Proposals (60 minutes): Propose an interactive, hands-on session focused on practical skills, tools, or methodologies.
Submission Guidelines
Abstract: All submissions (except workshop proposals) must include a concise abstract (maximum 300 words) summarizing the problem, approach, key findings/insights, and conclusions.
Author Information: Include full names, affiliations, and a brief professional biography (max 100 words per author).
Keywords: Provide 3-5 relevant keywords.
Originality: Submissions must represent original work that has not been previously published or is not under review elsewhere.
Audience Consideration: Presenters should be prepared to convey complex technical or business concepts clearly to a diverse audience, including both technical and non-technical attendees.
Formatting: Specific formatting guidelines for full papers will be provided upon submission portal opening.
Review Process
All submissions will undergo a rigorous peer-review process by the Program Committee, comprising leading experts in AI, data science, and related business domains. Submissions will be evaluated based on:
Relevance to conference themes
Originality and novelty of contributions
Technical merit and soundness (for technical papers)
Clarity, organization, and presentation quality
Potential impact and practical applicability
Further details on submission deadlines and the submission portal will be provided on the conference website. We encourage early submissions.
We look forward to your valuable contributions!
Unleashing India's Financial Potential with AI & Data Science
From Big Data to Big Insights: Deep Dive into Mining Massive Datasets
Join us for an immersive conference exploring the processes, techniques and technologies to efficiently extract valuable insights from massive datasets. This conference will delve into the fundamental concepts and techniques of Mining Massive Datasets (MMD), exploring how to effectively harness the power of big data.
What to Expect:
Fundamental concepts and techniques of data mining and machine learning for massive datasets.
Explore the underlying technologies, algorithms, and tools to extract valuable insights from large-scale data.
Gain hands-on experience in processing, analyzing, and modeling massive datasets.
Networking Opportunities: Connect with like-minded professionals and build valuable relationships with industry leaders.
Key Topics:
Distributed Systems and Frameworks:
Deep dive into HDFS and Cloud Storage for efficient data storage.
Comparative analysis of Apache Spark and Apache Flink for parallel data processing.
Understanding batch and stream processing paradigms.
Data Mining Techniques:
Similarity Search: Mastering minhashing and locality-sensitive hashing for recommendation systems and anomaly detection.
Frequent Itemset Mining: Discovering association rules and market-basket analysis for retail and healthcare.
Clustering: Grouping data points with k-means, hierarchical clustering, and DBSCAN for customer segmentation and image clustering.
Advanced Topics:
Graph Analytics: Unraveling complex relationships with social network analysis and graph mining for fraud detection and knowledge graph construction.
Dimensionality Reduction: Simplifying data with SVD and LSI for text mining and feature engineering.
Machine Learning for Massive Datasets: Scaling machine learning algorithms and leveraging cloud-based platforms.
Why Attend?
Master the Fundamentals: Gain a solid understanding of the core concepts and techniques of data mining and machine learning.
Learn from Experts: Hear from practicing data scientists who are shaping the future of data science.
Gain Expertise: Learn from top experts in the field of machine learning and data engineering.
Stay Ahead of the Curve: Discover the latest trends and advancements.
Network with Industry Leaders: Connect with like-minded professionals and build valuable relationships.
Advance Your Career: Enhance your skills and knowledge to advance your career in data science.
What to Expect:
Fundamental concepts and techniques of data mining and machine learning for massive datasets.
Explore the underlying technologies, algorithms, and tools to extract valuable insights from large-scale data.
Gain hands-on experience in processing, analyzing, and modeling massive datasets.
Networking Opportunities: Connect with like-minded professionals and build valuable relationships with industry leaders.
Key Topics:
Distributed Systems and Frameworks:
Deep dive into HDFS and Cloud Storage for efficient data storage.
Comparative analysis of Apache Spark and Apache Flink for parallel data processing.
Understanding batch and stream processing paradigms.
Data Mining Techniques:
Similarity Search: Mastering minhashing and locality-sensitive hashing for recommendation systems and anomaly detection.
Frequent Itemset Mining: Discovering association rules and market-basket analysis for retail and healthcare.
Clustering: Grouping data points with k-means, hierarchical clustering, and DBSCAN for customer segmentation and image clustering.
Advanced Topics:
Graph Analytics: Unraveling complex relationships with social network analysis and graph mining for fraud detection and knowledge graph construction.
Dimensionality Reduction: Simplifying data with SVD and LSI for text mining and feature engineering.
Machine Learning for Massive Datasets: Scaling machine learning algorithms and leveraging cloud-based platforms.
Why Attend?
Master the Fundamentals: Gain a solid understanding of the core concepts and techniques of data mining and machine learning.
Learn from Experts: Hear from practicing data scientists who are shaping the future of data science.
Gain Expertise: Learn from top experts in the field of machine learning and data engineering.
Stay Ahead of the Curve: Discover the latest trends and advancements.
Network with Industry Leaders: Connect with like-minded professionals and build valuable relationships.
Advance Your Career: Enhance your skills and knowledge to advance your career in data science.
We are in the process of finalizing dates and details.
Sign up for updates - dates & details coming soon - secure your spot at this exclusive event!
Sign up for updates - dates & details coming soon - secure your spot at this exclusive event!
AI and Data Science Professionals:
Data Scientists
AI/Machine Learning Engineers
Data Engineers
AI Researchers
Software Engineers
Product Managers
UX Designers
Business and Leadership Audience:
C-Suite Executives (CEOs, CTOs, CIOs): Leaders who need to understand the strategic implications of big data and data-driven decision-making.
Business Analysts: Professionals who use data to analyze business performance and identify opportunities.
Product Managers: Individuals responsible for developing data-driven products and services.
Investors, Traders and Venture Capitalists:
Investors: Benefit from optimizing investment decision-making processes.
Traders: Benefit from processing, analyzing, and modeling massive datasets.
Venture Capitalists: Professionals who fund early-stage technology companies.
Government and Policymakers:
Government Officials: Policymakers who need to understand the impact of big data on society and regulations.
Data Privacy Officers: Professionals responsible for ensuring data privacy and security.
Regulatory Agencies: Organizations that oversee data usage and compliance.
Other Potential Attendees:
Academics and Researchers: Individuals from universities and research institutions.
Students and Aspiring Data Professionals: Students and early-career professionals interested in learning about big data.
Consultants: Professionals who advise organizations on data strategy and implementation.
Data Journalists: Individuals who use data to tell stories and inform the public.
Data Scientists
AI/Machine Learning Engineers
Data Engineers
AI Researchers
Software Engineers
Product Managers
UX Designers
Business and Leadership Audience:
C-Suite Executives (CEOs, CTOs, CIOs): Leaders who need to understand the strategic implications of big data and data-driven decision-making.
Business Analysts: Professionals who use data to analyze business performance and identify opportunities.
Product Managers: Individuals responsible for developing data-driven products and services.
Investors, Traders and Venture Capitalists:
Investors: Benefit from optimizing investment decision-making processes.
Traders: Benefit from processing, analyzing, and modeling massive datasets.
Venture Capitalists: Professionals who fund early-stage technology companies.
Government and Policymakers:
Government Officials: Policymakers who need to understand the impact of big data on society and regulations.
Data Privacy Officers: Professionals responsible for ensuring data privacy and security.
Regulatory Agencies: Organizations that oversee data usage and compliance.
Other Potential Attendees:
Academics and Researchers: Individuals from universities and research institutions.
Students and Aspiring Data Professionals: Students and early-career professionals interested in learning about big data.
Consultants: Professionals who advise organizations on data strategy and implementation.
Data Journalists: Individuals who use data to tell stories and inform the public.
Scaling Data Processing: Distributed Systems and Frameworks
Distributed File Systems: The Foundation of Big Data
Deep dive into HDFS, Cloud Storage, and their role in storing massive datasets.
Explore the advantages and trade-offs of different storage solutions.
Distributed Processing Frameworks: Unleashing the Power of Parallelism
Comparative analysis of Apache Spark and Apache Flink.
Hands-on demonstrations of real-world data processing pipelines.
Data Processing Paradigms: Batch vs. Stream
Discuss the strengths and weaknesses of batch and stream processing.
Explore hybrid approaches and real-time analytics use cases.
Uncovering Hidden Patterns: Data Mining Techniques
Similarity Search: Finding Your Matches in the Haystack
In-depth exploration of minhashing and locality-sensitive hashing.
Practical applications in recommendation systems and anomaly detection.
Frequent Itemset Mining: Discovering the Rules of the Game
Dive into association rule mining and market-basket analysis.
Learn how to apply these techniques to retail, healthcare, and other domains.
Clustering: Grouping Together What Belongs Together
Explore various clustering algorithms, including k-means, hierarchical clustering, and DBSCAN.
Hands-on exercises in customer segmentation and image clustering.
Advanced Topics in Data Mining and Machine Learning
Graph Analytics: Unraveling Complex Relationships
Social network analysis and graph mining techniques.
Real-world applications in fraud detection and knowledge graph construction.
Dimensionality Reduction: Simplifying the Complex
In-depth discussion of SVD and LSI.
Practical applications in text mining and feature engineering.
Machine Learning for Massive Datasets: Scalable Algorithms and Techniques
Explore scalable machine learning algorithms, including gradient descent and distributed deep learning.
Hands-on experience with cloud-based machine learning platforms.
Distributed File Systems: The Foundation of Big Data
Deep dive into HDFS, Cloud Storage, and their role in storing massive datasets.
Explore the advantages and trade-offs of different storage solutions.
Distributed Processing Frameworks: Unleashing the Power of Parallelism
Comparative analysis of Apache Spark and Apache Flink.
Hands-on demonstrations of real-world data processing pipelines.
Data Processing Paradigms: Batch vs. Stream
Discuss the strengths and weaknesses of batch and stream processing.
Explore hybrid approaches and real-time analytics use cases.
Uncovering Hidden Patterns: Data Mining Techniques
Similarity Search: Finding Your Matches in the Haystack
In-depth exploration of minhashing and locality-sensitive hashing.
Practical applications in recommendation systems and anomaly detection.
Frequent Itemset Mining: Discovering the Rules of the Game
Dive into association rule mining and market-basket analysis.
Learn how to apply these techniques to retail, healthcare, and other domains.
Clustering: Grouping Together What Belongs Together
Explore various clustering algorithms, including k-means, hierarchical clustering, and DBSCAN.
Hands-on exercises in customer segmentation and image clustering.
Advanced Topics in Data Mining and Machine Learning
Graph Analytics: Unraveling Complex Relationships
Social network analysis and graph mining techniques.
Real-world applications in fraud detection and knowledge graph construction.
Dimensionality Reduction: Simplifying the Complex
In-depth discussion of SVD and LSI.
Practical applications in text mining and feature engineering.
Machine Learning for Massive Datasets: Scalable Algorithms and Techniques
Explore scalable machine learning algorithms, including gradient descent and distributed deep learning.
Hands-on experience with cloud-based machine learning platforms.
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Cultural Experiences: Guests can learn about Goan culture through cooking classes, cultural performances, or guided tours to local attractions.
Fitness and Recreation: The resort has a fitness center, swimming pool, tennis court, and table tennis.
Nature Walks: Guests can take guided nature walks through the nearby forests and learn about the local flora and fauna.
The Taj Exotica Resort offers a variety of adventures for guests to enjoy:
Beach Adventures: The resort has a private beach where guests can swim, sunbathe, play volleyball, or try water sports like kayaking, windsurfing, or parasailing.
Spa and Wellness: The resort's Jiva Spa offers a variety of treatments, including Ayurvedic massages, yoga, and meditation.
Cultural Experiences: Guests can learn about Goan culture through cooking classes, cultural performances, or guided tours to local attractions.
Fitness and Recreation: The resort has a fitness center, swimming pool, tennis court, and table tennis.
Nature Walks: Guests can take guided nature walks through the nearby forests and learn about the local flora and fauna.
We're excited to announce our Call for Presentations & Papers for a premier conference dedicated to the cutting-edge of scalable data processing and data mining. This event will bring together leading data professionals and innovators to share their insights, discoveries, and practical applications in this rapidly evolving field. We invite you to contribute your expertise and join us in exploring the future of big data.
We're looking for compelling presentations, papers, workshops, and lightning talks that offer original research, innovative solutions, real-world case studies, and insightful analyses.
Main Conference Subject Areas
Scaling Data Processing: Distributed Systems and Frameworks
This track focuses on the foundational and advanced aspects of processing large-scale datasets efficiently. We encourage submissions on:
Distributed File Systems: The Foundation of Big Data
Deep dives into HDFS, Cloud Storage, and their crucial role in storing massive datasets.
Explorations of the advantages and trade-offs of different storage solutions in various contexts.
Distributed Processing Frameworks: Unleashing the Power of Parallelism
Comparative analyses of Apache Spark and Apache Flink, including performance benchmarks and use cases.
Hands-on demonstrations of real-world data processing pipelines built with these frameworks.
Data Processing Paradigms: Batch vs. Stream
Discussions on the strengths and weaknesses of batch and stream processing.
Explorations of hybrid approaches and real-time analytics use cases across different industries.
Uncovering Hidden Patterns: Data Mining Techniques
This track delves into methodologies for extracting valuable insights and patterns from large datasets. We're particularly interested in:
Similarity Search: Finding Your Matches in the Haystack
In-depth explorations of minhashing and locality-sensitive hashing.
Practical applications in recommendation systems and anomaly detection.
Frequent Itemset Mining: Discovering the Rules of the Game
Deep dives into association rule mining and market-basket analysis.
How to apply these techniques to various domains like retail, healthcare, and cybersecurity.
Clustering: Grouping Together What Belongs Together
Explorations of various clustering algorithms, including k-means, hierarchical clustering, and DBSCAN.
Hands-on exercises in practical applications such as customer segmentation and image clustering.
Advanced Topics in Data Mining and Machine Learning
This track covers cutting-edge techniques and scalable approaches for complex data challenges. We welcome submissions on:
Graph Analytics: Unraveling Complex Relationships
Social network analysis and advanced graph mining techniques.
Real-world applications in fraud detection and knowledge graph construction.
Dimensionality Reduction: Simplifying the Complex
In-depth discussions of SVD and LSI.
Practical applications in text mining and feature engineering.
Machine Learning for Massive Datasets: Scalable Algorithms and Techniques
Explorations of scalable machine learning algorithms, including gradient descent and distributed deep learning.
Hands-on experiences and best practices with cloud-based machine learning platforms.
Submission Types
We invite various types of submissions to ensure a rich and diverse program:
Oral Presentations (20 minutes): Share your research findings, innovative applications, case studies, or best practices in a focused presentation.
Technical Papers (Full Length, 8-12 pages, IEEE format): Submit original, unpublished research that will undergo a rigorous peer-review process. Accepted papers will be published in the conference proceedings.
Experience & Insight Papers (4-6 pages, formatted for readability): This category is for practitioners, industry leaders, and innovators to share valuable lessons learned, practical case studies, real-world implementations, and insightful perspectives on the challenges and successes encountered in scalable data processing and data mining. These papers should focus on practical applications, best practices, and actionable insights. Submissions will be peer-reviewed for clarity, relevance, and practical value.
Poster Presentations: Visually showcase preliminary results, ongoing research, or innovative concepts. There will be a dedicated poster session for interactive discussions.
Panel Proposals (60 minutes): Suggest and moderate a discussion among 3-5 experts on a controversial, emerging, or complex topic within scalable data processing and data mining.
Workshop Proposals (60 minutes): Propose an interactive, hands-on session focused on practical skills, tools, or methodologies related to data processing, data mining, or machine learning for massive datasets.
Submission Guidelines
Abstract: All submissions (except workshop proposals) must include a concise abstract (maximum 300 words) summarizing the problem, approach, key findings/insights, and conclusions.
Author Information: Include full names, affiliations, and a brief professional biography (max 100 words per author).
Keywords: Provide 3-5 relevant keywords that best describe your submission.
Originality: Submissions must represent original work that has not been previously published or is not currently under review elsewhere.
Audience Consideration: Presenters should be prepared to convey complex technical or business concepts clearly to a diverse audience, including both technical and non-technical attendees.
Formatting: Specific formatting guidelines for full papers will be provided upon the submission portal opening.
Review Process
All submissions will undergo a rigorous peer-review process by the Program Committee, comprising leading experts in data science, distributed systems, machine learning, and related domains. Submissions will be evaluated based on:
Relevance to conference themes
Originality and novelty of contributions
Technical merit and soundness (for technical papers)
Clarity, organization, and presentation quality
Potential impact and practical applicability
We look forward to receiving your valuable contributions and seeing you at the conference!
We're looking for compelling presentations, papers, workshops, and lightning talks that offer original research, innovative solutions, real-world case studies, and insightful analyses.
Main Conference Subject Areas
Scaling Data Processing: Distributed Systems and Frameworks
This track focuses on the foundational and advanced aspects of processing large-scale datasets efficiently. We encourage submissions on:
Distributed File Systems: The Foundation of Big Data
Deep dives into HDFS, Cloud Storage, and their crucial role in storing massive datasets.
Explorations of the advantages and trade-offs of different storage solutions in various contexts.
Distributed Processing Frameworks: Unleashing the Power of Parallelism
Comparative analyses of Apache Spark and Apache Flink, including performance benchmarks and use cases.
Hands-on demonstrations of real-world data processing pipelines built with these frameworks.
Data Processing Paradigms: Batch vs. Stream
Discussions on the strengths and weaknesses of batch and stream processing.
Explorations of hybrid approaches and real-time analytics use cases across different industries.
Uncovering Hidden Patterns: Data Mining Techniques
This track delves into methodologies for extracting valuable insights and patterns from large datasets. We're particularly interested in:
Similarity Search: Finding Your Matches in the Haystack
In-depth explorations of minhashing and locality-sensitive hashing.
Practical applications in recommendation systems and anomaly detection.
Frequent Itemset Mining: Discovering the Rules of the Game
Deep dives into association rule mining and market-basket analysis.
How to apply these techniques to various domains like retail, healthcare, and cybersecurity.
Clustering: Grouping Together What Belongs Together
Explorations of various clustering algorithms, including k-means, hierarchical clustering, and DBSCAN.
Hands-on exercises in practical applications such as customer segmentation and image clustering.
Advanced Topics in Data Mining and Machine Learning
This track covers cutting-edge techniques and scalable approaches for complex data challenges. We welcome submissions on:
Graph Analytics: Unraveling Complex Relationships
Social network analysis and advanced graph mining techniques.
Real-world applications in fraud detection and knowledge graph construction.
Dimensionality Reduction: Simplifying the Complex
In-depth discussions of SVD and LSI.
Practical applications in text mining and feature engineering.
Machine Learning for Massive Datasets: Scalable Algorithms and Techniques
Explorations of scalable machine learning algorithms, including gradient descent and distributed deep learning.
Hands-on experiences and best practices with cloud-based machine learning platforms.
Submission Types
We invite various types of submissions to ensure a rich and diverse program:
Oral Presentations (20 minutes): Share your research findings, innovative applications, case studies, or best practices in a focused presentation.
Technical Papers (Full Length, 8-12 pages, IEEE format): Submit original, unpublished research that will undergo a rigorous peer-review process. Accepted papers will be published in the conference proceedings.
Experience & Insight Papers (4-6 pages, formatted for readability): This category is for practitioners, industry leaders, and innovators to share valuable lessons learned, practical case studies, real-world implementations, and insightful perspectives on the challenges and successes encountered in scalable data processing and data mining. These papers should focus on practical applications, best practices, and actionable insights. Submissions will be peer-reviewed for clarity, relevance, and practical value.
Poster Presentations: Visually showcase preliminary results, ongoing research, or innovative concepts. There will be a dedicated poster session for interactive discussions.
Panel Proposals (60 minutes): Suggest and moderate a discussion among 3-5 experts on a controversial, emerging, or complex topic within scalable data processing and data mining.
Workshop Proposals (60 minutes): Propose an interactive, hands-on session focused on practical skills, tools, or methodologies related to data processing, data mining, or machine learning for massive datasets.
Submission Guidelines
Abstract: All submissions (except workshop proposals) must include a concise abstract (maximum 300 words) summarizing the problem, approach, key findings/insights, and conclusions.
Author Information: Include full names, affiliations, and a brief professional biography (max 100 words per author).
Keywords: Provide 3-5 relevant keywords that best describe your submission.
Originality: Submissions must represent original work that has not been previously published or is not currently under review elsewhere.
Audience Consideration: Presenters should be prepared to convey complex technical or business concepts clearly to a diverse audience, including both technical and non-technical attendees.
Formatting: Specific formatting guidelines for full papers will be provided upon the submission portal opening.
Review Process
All submissions will undergo a rigorous peer-review process by the Program Committee, comprising leading experts in data science, distributed systems, machine learning, and related domains. Submissions will be evaluated based on:
Relevance to conference themes
Originality and novelty of contributions
Technical merit and soundness (for technical papers)
Clarity, organization, and presentation quality
Potential impact and practical applicability
We look forward to receiving your valuable contributions and seeing you at the conference!