Workshops & Events | Raghuwansh Raj

🏛️ Hausdorff Trimester Program - Geometric Statistics 2026

Sat, 12 Dec 2026 00:00:00 +0000

I am honored to be invited to participate in the Dual Trimester Program on Geometric Statistics: theory, application, and computation at the Hausdorff Research Institute for Mathematics (HIM) in Bonn, Germany from September 14 to December 12, 2026.

This is an exceptional opportunity to engage with leading mathematicians and researchers working at the forefront of geometric and statistical methods in mathematics.

Program Overview

The trimester program spans three months and includes multiple schools, workshops, and conferences:

School on Geometric Statistics

September 14-18, 2026

Foundational lectures on geometric statistics
Theory and applications of statistics on manifolds
Computational methods for geometric data analysis

Workshop: Stochastic Analysis, Statistics, and Computation on Manifolds and Singular Spaces

October 12-16, 2026

Advanced topics in stochastic analysis
Statistical methods on curved and singular spaces
Computational algorithms and implementations

Workshop: Geometry, Topology, and Learning on Smooth and Singular Spaces

November 9-13, 2026

Learning theory perspectives on geometric problems
Topological data analysis methods
Applications to machine learning on manifolds

Conference: Interactions of Statistics and Geometry III (ISAG III)

December 7-11, 2026

Presentation of cutting-edge research
Dialogue between statisticians and geometers
Exploring new directions in geometric statistics

About Hausdorff Research Institute for Mathematics

The Hausdorff Research Institute for Mathematics (HIM) is an international center devoted to advancing research in mathematics and mathematical economics. HIM brings together:

A critical mass of expertise and scientists at one location
An inspiring mathematical atmosphere
Opportunity for mathematicians to work on challenging projects undisturbed
Direct discussion with leading experts in their field

This unique environment has consistently led to substantial output of research results of the highest quality, with many projects initiated, pursued, and sometimes completed during HIM programs.

Program Goals

By participating in this trimester program, I aim to:

Deepen knowledge in geometric statistics and their applications
Explore connections between geometry, topology, and machine learning
Engage with world-leading experts in the field
Collaborate on research projects addressing fundamental problems
Build connections with the international mathematics community

Research Interests Alignment

The program aligns perfectly with my research interests in:

Geometric and topological deep learning
Mathematical foundations of GNNs and topological methods
Applications of geometry to machine learning
Algebraic and differential geometric approaches

Learn More

For more information about HIM and the Geometric Statistics program:

Geometric Statistics Trimester Program

About HIM

Hausdorff Research Institute

📐 London Geometry and Machine Learning (LOGML) Summer School 2026

Fri, 17 Jul 2026 00:00:00 +0000

I had the privilege to attend the London Geometry and Machine Learning (LOGML) Summer School 2026 held at Imperial College London from July 13-17, 2026.

This was my first summer school during my PhD journey, and it was an incredible opportunity to engage with the vibrant community of doctoral students, researchers, and experts working at the intersection of mathematics, geometry, and machine learning.

Program Overview

The summer school featured intensive lectures and tutorials covering:

Graph Representation Learning - Understanding and learning from graph-structured data
Learning Graphs from Data - Discovering graph structures from raw data
Equivariant Machine Learning - Building models that respect symmetries and invariances
Algebraic Geometry in Deep Learning - Mathematical foundations for neural network design
Discrete Structures for 3D Geometric Learning - Geometric approaches to 3D data
Graph Foundation Models - Pre-trained models for graph-based tasks
Physics-Informed Graph Neural Networks - Incorporating physical priors into GNNs

Key Learnings

I was particularly inspired by lectures from world-leading experts including:

Xiaowen Dong - Graph signal processing and learning
Dorina Thanou - Geometric methods in machine learning
Stefanie Jegelka - Graph neural networks and expressiveness
Olga Fink - Physics-informed machine learning

Their discussions on mathematical and physical priors in building graphical models, and the integration of AI in physical and health sciences, were enlightening.

Collaborative Project

During the summer school, I had the opportunity to work on a group project exploring:

Canonicalization of 3D Molecular Point Clouds - Collaborating with mentor Snir Hordan, we investigated how symmetry-aware preprocessing can help conventional neural architectures learn from molecular geometry more efficiently.

This work bridges the gap between geometric deep learning theory and practical molecular applications.

Key Takeaways

Deepened understanding of geometric and topological approaches in deep learning
Networked with talented researchers from institutions worldwide
Gained hands-on experience with cutting-edge techniques in equivariant learning
Explored applications in molecular geometry and 3D learning
Built connections with mentors and peers in the GDL community

Gratitude

I’m grateful to the LOGML Organizers, especially Dr. Lennart Bastian, the speakers, mentors, and fellow participants for creating such an intellectually stimulating and collaborative environment.

Learn More

For more information about LOGML:

Visit LOGML Official Website

Imperial College London

🌐 Attending AWS Summit Paris 2024

Wed, 10 Apr 2024 00:00:00 +0000

Recently, I had the opportunity to attend AWS Summit Paris on behalf of my team at Stellantis France.

It was my first time participating in an event of this scale, and it was an incredible experience to be immersed in the tech ecosystem of France and Europe.

The summit was a full-day event with more than 50 companies showcasing their technologies and solutions through talks, presentations, and booths.

I had the chance to meet and listen to professionals working across many domains including:

Cloud infrastructure
Encryption and cybersecurity
Automotive technologies
SaaS and PaaS platforms
Supply chain systems
Artificial intelligence and machine learning

A major theme of this year’s summit was Large Language Models (LLMs) and the Retrieval Augmented Generation (RAG) approach used to address some of their practical challenges.

It was fascinating to see how organizations are integrating AI-driven solutions with AWS cloud infrastructure to build scalable and intelligent systems.

The event provided a great opportunity to learn about new developments in cloud computing, AI, and industry applications, while also connecting with professionals from across the European tech community.

Event Highlights

50+ companies presenting cutting-edge technologies
Focus on LLMs and RAG architectures
Discussions on cloud-native AI systems
Insights into automotive and industrial AI applications
Networking with professionals from across Europe

Learn More

You can find more details about the summit here:

Visit AWS Summit Paris

🌐 AWS Summit Paris 2024

Wed, 10 Apr 2024 00:00:00 +0000

Recently, I had the opportunity to attend AWS Summit Paris on behalf of my team at Stellantis France.

It was my first time participating in an event of this scale, and it was an incredible experience to be immersed in the tech ecosystem of France and Europe.

The summit was a full-day event with more than 50 companies showcasing their technologies and solutions through talks, presentations, and booths.

I had the chance to meet and listen to professionals working across many domains including:

Cloud infrastructure
Encryption and cybersecurity
Automotive technologies
SaaS and PaaS platforms
Supply chain systems
Artificial intelligence and machine learning

A major theme of this year’s summit was Large Language Models (LLMs) and the Retrieval Augmented Generation (RAG) approach used to address some of their practical challenges.

It was fascinating to see how organizations are integrating AI-driven solutions with AWS cloud infrastructure to build scalable and intelligent systems.

Event Highlights

50+ companies presenting cutting-edge technologies
Focus on LLMs and RAG architectures
Discussions on cloud-native AI systems
Insights into automotive and industrial AI applications
Networking with professionals across Europe

Learn More

Visit AWS Summit Paris