Join us for a 3-day immersive conference exploring the cutting-edge applications of random forests in various industries.

What to Expect:

In-depth Technical Sessions: Delve into the core concepts of random forests, including ensemble learning, decision trees, and feature importance.
Real-World Case Studies: Learn from industry experts as they share practical examples of how random forests have been applied to solve real-world problems.
Hands-on Workshops: Gain practical experience by working on real-world datasets and building your own random forest models.
Networking Opportunities: Connect with like-minded professionals and build valuable relationships with industry leaders.

Key Topics:

Financial Industry:

Fraud Detection
Customer Churn Prediction
Risk Assessment

Healthcare:

Disease Diagnosis
Patient Risk Stratification
Drug Discovery

Marketing and Sales:

Customer Segmentation
Market Basket Analysis
Customer Lifetime Value Prediction

Environmental Science:

Species Distribution Modeling
Climate Change Impact Assessment
Forest Fire Prediction

Cybersecurity:

Network Intrusion Detection
Malware Detection
Phishing Email Detection

Recommender Systems:

Product Recommendations
Content Recommendations

Why Attend?

Gain Expertise: Learn from top experts in the field of machine learning and data science.
Stay Ahead of the Curve: Discover the latest trends and advancements in random forest applications.
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.

Primary Audience for Conference Attendees

AI and Data Science Professionals:

Data Scientists
AI/Machine Learning Engineers
AI Researchers
Software Engineers
Product Managers
UX Designers

Business and Finance Professionals:

Financial Institutions: Banks, investment firms, and tech companies.
E-commerce Businesses: Online retailers and payment processors.
Telecommunications Companies: Providers of communication services.
Healthcare Providers: Hospitals, clinics, and health insurance companies.
Entrepreneurs and investors in the Tech space.
Academic and Research Community.

Technology Professionals:

IT Managers and CIOs: IT leaders responsible for securing organizational systems.
Network Engineers: Network administrators and security engineers.
Cybersecurity Experts: Security analysts, penetration testers, and security architects.
Cryptographers: Cryptography researchers and engineers.

Government Officials and Regulators:

Policymakers and regulators shaping the regulatory landscape.
Regulators: Policymakers responsible for overseeing AI/ML.

Main Conference Subject Areas

I. Random Forest Fundamentals and Applications

A. Core Concepts

B. Hyperparameter Tuning

C. Feature Importance and Interpretation

II. Industry Applications of Random Forests

A. Finance

• Fraud Detection
• Customer Churn Prediction
• Risk Assessment

B. Healthcare

• Disease Diagnosis
• Patient Risk Stratification
• Drug Discovery

C. Marketing and Sales

• Customer Segmentation
• Market Basket Analysis
• Customer Lifetime Value Prediction

D. Environmental Science

• Species Distribution Modeling
• Climate Change Impact Assessment
• Forest Fire Prediction

E. Cybersecurity

• Network Intrusion Detection
• Malware Detection
• Phishing Email Detection

F. Recommender Systems

• Product Recommendations
• Content Recommendations
• Collaborative Filtering and Content-Based Filtering Techniques

III. Building a Random Forest Model (Hands-on Workshop)

A. Data Preparation and Feature Engineering

B. Model Training and Evaluation

C. Model Deployment and Monitoring

Experiencing Niseko United Ski Resort in Hokkaido, Japan

Niseko United, a world-renowned ski resort in Hokkaido, Japan, is famous for its exceptional powder snow. This winter wonderland comprises four interconnected ski areas—Grand Hirafu, Niseko Village, Hanazono, and Annupuri—offering a vast expanse of skiable terrain for all levels.

Niseko United's allure extends beyond its slopes. The resort boasts abundant snowfall, creating consistently deep and fluffy powder conditions. Its diverse terrain caters to everyone, from gentle slopes for beginners to challenging off-piste runs for experts. Moreover, Niseko offers a unique blend of Japanese culture and international influences, with a variety of dining and accommodation options. After a day on the slopes, visitors can relax in traditional Japanese hot springs, known as onsen.

Hokkaido offers a diverse range of adventures for all interests. Whether you're seeking adrenaline-pumping thrills or peaceful relaxation, you'll find it in this beautiful region of Japan. Here are some cool things to experience:

Hot Spring Soaking (Onsen) in Noboribetsu:

Relax in therapeutic mineral-rich waters.
Experience traditional Japanese culture and hospitality.
Rejuvenate your body and mind in a serene onsen setting.

Skiing or Snowboarding in Niseko:

Experience world-class powder snow in this renowned ski resort.
Enjoy a variety of slopes for all skill levels.
Immerse yourself in the stunning winter wonderland.

Rafting on the Shiretoko River:

Embark on a thrilling white-water rafting adventure.
Admire the breathtaking scenery of Shiretoko National Park.
Challenge yourself with exciting rapids and serene river stretches.

Hiking in Daisetsuzan National Park:

Explore diverse landscapes, from volcanic peaks to alpine meadows.
Encounter unique wildlife, including brown bears and red foxes.
Enjoy stunning views and fresh mountain air.

Whale Watching in Otaru:

Witness majestic whales in their natural habitat.
Learn about marine conservation and ecology.
Create unforgettable memories of these gentle giants.

Heli-Skiing Adventure (Optional)

Experience the ultimate powder skiing adventure with a helicopter tour to remote, pristine snowfields.

Join us for a thrilling day of heli-skiing in the Niseko Mountain Range. We will fly you to remote, pristine snowfields where you will experience the ultimate powder skiing adventure. Our experienced guides will lead you to the best terrain, ensuring a safe and unforgettable experience.

Call for Presentations & Papers

This event aims to bridge the gap between theoretical understanding and practical implementation, fostering a deeper knowledge of this powerful machine learning technique across diverse fields. We seek to unite researchers, practitioners, and industry leaders to share insights, discuss advancements, and explore the vast applications of Random Forests.

We welcome submissions for presentations, technical papers, and workshop proposals that delve into the cutting-edge advancements, practical applications, and developmental challenges of Random Forests. Our audience is broad, encompassing data scientists, machine learning engineers, software developers, researchers, and professionals across various industries. Submissions should offer valuable insights for both technical and non-technical attendees, covering aspects from foundational concepts to real-world deployment strategies.

Topics of Interest

We encourage submissions that align with, but are not limited to, the following themes:

I. Random Forest Fundamentals and Applications

• Core Concepts: Delving into decision trees, ensemble learning, and bagging.
• Hyperparameter Tuning: Optimizing model performance through effective tuning strategies.
• Feature Importance and Interpretation: Understanding and explaining model decisions.

II. Industry Applications of Random Forests

• Finance: Fraud detection, customer churn prediction, and risk assessment.
• Healthcare: Disease diagnosis, patient risk stratification, and drug discovery.
• Marketing and Sales: Customer segmentation, market basket analysis, and customer lifetime value prediction.
• Environmental Science: Species distribution modeling, climate change impact assessment, and forest fire prediction.
• Cybersecurity: Network intrusion detection, malware detection, and phishing email detection.
• Recommender Systems: Product and content recommendations, including collaborative and content-based filtering techniques.

III. Building a Random Forest Model (Hands-on Workshop)

• Data Preparation and Feature Engineering: Techniques for preparing data for Random Forest models.
• Model Training and Evaluation: Methodologies for training and evaluating Random Forest models.
• Model Deployment and Monitoring: Best practices for deploying and monitoring Random Forest models in production.

Submission Types

• Oral Presentations (20 minutes): Share your research findings, innovative applications, case studies, or best practices.

• Technical Papers (Full Length, 8-12 pages, specified 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 on the challenges and successes encountered in the development, deployment, or strategic adoption of Random Forest models. These papers should focus on practical applications, best practices, and actionable insights that can benefit the broader community, even if they don't 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. This includes a dedicated poster session for discussion.

• Workshop Proposals (60 minutes): Propose an interactive, hands-on session focused on practical skills, tools, or methodologies related to Random Forest development or deployment.

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 data science and machine learning. 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

Ready to share your expertise in Random Forests? We look forward to your valuable contributions!