Conferences  >  Informatics  >  Scientific Computing and Data Science

Institute for Computational and Experimental Research in Mathematics (ICERM), Brown University

Researchers working on graph algorithms use a broad range of different criteria for deciding what makes an algorithm efficient. While in theory the dominant benchmark is the asymptotic running time, in practice the story is more nuanced: an algorithm needs to be simple enough to be implementable, fast on graphs of bounded size, space efficient, cache-friendly, and easy to test. While many of these requirements motivate interesting algorithmic questions that are highly relevant in practice, they are often overlooked by the theory community. The goal of the workshop is to foster the exchange of ideas between researchers working on graph algorithms, which have high practical relevance. The workshop will include overview talks on the various perspectives, research talks, an open problem session, and structured time for collaboration.

ICERM Program Staff;     Phone: [+1 (401) 863-5030];     Email: info@icerm.brown.edu

graph algorithms, data science, networks

Algorithms and Data Structures,    Graph Theory and Combinatorics

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Simons Laufer Mathematical Sciences Institute (SLMath)

In a growing number of applications, one needs to analyze and interpret data coming from massive networks. The statistical problems arising from such applications lead to important mathematical challenges: building novel probabilistic models, understanding the possibilities and limitations for statistical detection and inference, designing efficient algorithms, and understanding the inherent limitations of fast algorithms. The workshop will bring together leading researchers in combinatorial statistics, machine learning, and random graphs in the hope of cross-fertilization of ideas.

combinatorial statistics, random graphs, network inference, network reconstruction, detection, estimation

Complex Networks,    Graph Theory and Combinatorics

The main topics of our congress are planned to be composed of new methods developed in the field of artificial intelligence and systems developed for the application of artificial intelligence in engineering and artificial intelligence in many different fields such as health, education, law, marketing and finance, textile, city and regional planning In our international congress, which we organized in order to increase interaction and communication, to cooperate, to act together, to share information and experiences by bringing together researchers, industrial organizations, public institutions and organizations working in the field of artificial intelligence and data science, national and international speakers will be included. Oral presentations will be made on subjects related to all areas of intelligence. We hope to see you among us at the 5th International Artificial Intelligence and Data Science Congress, and thank you in advance for your valuable contributions and participation.

ICADA 2025 meets the application requirements for ÜAK associate professorship.

Neural Networks and Artificial Intelligence, Machine Learning,    Implementation and Applications of Artificial Intelligence

NEXT BUSINESS MEDIA

The Data Science Conference (DSC Next 2025) is a premier event set to take place from May 07 - 09, 2025, in Amsterdam. This conference brings together industry experts, data scientists, researchers, and professionals to explore the latest advancements in data science, machine learning, and artificial intelligence. It offers a platform for participants to network, share insights, and discuss the future of data-driven technologies.

EVENT MANAGER;     Phone: [1 702 551 9568];     Email: contact@nextbusinessmedia.com

European Molecular Biology Organization (EMBO)

Molecular Biology,    Systems Biology and Computational Biology

On its 10th anniversary, ODSC East will feature 250+ speakers, instructors, and practitioners, 2,500 of your fellow data and AI practitioners, and hands-on instruction for world-class experts in: AI Agents | Generative AI | Large Language Models | AI Engineering | Machine Learning | Deep Learning | MLOps and LLMOps | AI for Biotech, Pharma, and Life Sciences | Data Engineering | Data Visualization and Analysis | and much more. You’ll also be able to build meaningful connections with speakers and peers in a relaxed setting during our networking events like the ODSC Networking Reception, Dinner with Data Scientists, Meet the Speaker session, Book Signing sessions, and more.

Email: iryna@odsc.com

Data Science, Machine Learning, AI, Artificial Intelligence

American Institute of Mathematics, Pasadena, California (AIM)

This workshop is designed for faculty, postdocs, and PhD students who are interested in teaching statistics and data science through an interdisciplinary approach that leverages the strengths of both applied mathematics and statistics. Participants will exchange pedagogical ideas, curricula, and research applications, fostering collaboration between those teaching data science. The workshop is especially relevant for statistics faculty looking to expand their data science toolbox and applied mathematicians aiming to equip their students with essential data science skills. The workshop is also open to individuals in engineering, epidemiology, computer science and other STEM or public health fields.

Applied Mathematics (in general),    Didactics of Scientific Disciplines

COLOURS is a 2-week event aimed at ensuing that early-career researchers (ECR) are prepared to make the most of Stage-IV cosmological survey data. The first week of the event (02/06/25-06/06/25) will be a 5-day summer school aimed at improving both technical (software development, machine learning, statistics) and soft skills (academic writing, transferable skills). Site visits and social activities will also be organised. The second week (10/06/25-13/06/25) will be a 4-day workshop with invited speakers. The aim will be to review key lessons learned in the analysis of Stage-III data and the scientific aspirations of on-going and upcoming Stage-IV surveys.

Organiser;     Email: samuel.farrens@cea.fr

Cosmology, machine learning, software development, academic writing, transferable skills

MIPRO Croatian Society

The DS-BE conference aims to showcase new research and advancements in computational methods, tools, and applications related to Data Science and Biomedical Engineering. We invite high-quality, original research papers highlighting theoretical and practical innovations in these areas, expecting interdisciplinary approaches promoting scalable solutions for real-world challenges. The conference focuses on hardware and software solutions designed to address specific domain-related challenges related to various domains in science and industry. Additionally, it encompasses broader research initiatives that provide generalizable approaches across data-driven disciplines.

Karolj Skala - conference chair;     Phone: [+38551423984];     Email: skala@irb.hr

Machine Learning and Deep Learning, Complex Networks: Structure, Behavior, and Dynamics, Knowledge Discovery and Interpretability, Data Science Methods, Tools and Platforms, Big Data Analysis and Visualization, Service Applications Based on Cloud, Fog, and/or Dew Computing, Interpretable and Explainable Machine Learning, Expert Systems and Knowledge-Based Systems, Knowledge Representation and Management, Natural Language Processing and Text Mining, Ethical AI, Data Science in Computational Biology and Medicine, Biological Network Analysis, Drug Target Identification and Validation, Medical and Biological Image Analysis, Analysis and Visualization of Biological and Clinical Data, Bioinformatics and Medical Applications, Advanced Bio-Signal Processing and Interpretation, Monitoring of Vital Functions with Sensor and ICT Systems, Wearable Sensors and Networks in Distributed Systems, Telehealth, Telecare, Telemonitoring, and Telediagnostics, Social Networking, Computing, and Education for Health, Internet of Things (IoT) for mHealth, Data Models and Representations for mHealth, Information Fusion of Biomedical Data, Biomedical Scientific Databases

Genomics and Bioinformatics,    Neural Networks and Artificial Intelligence, Machine Learning

Institute for Computational and Experimental Research in Mathematics, Brown University, Providence, RI (ICERM)

Summer@ICERM is a residential undergraduate research program hosted at the Institute for Computational and Experimental Research in Mathematics at Brown University. Led by experienced faculty and graduate student teaching assistants, participating undergrads will spend seven weeks learning how to collaborate, engage in data science, and conduct research as a team. The goal of Summer@ICERM 2025: Building Useful Insights from Local Data through Sustainable partnerships (BUILDS) is to introduce students with limited experience to the field of data science through projects related to issues such as global food systems, food production, and food security.

Courses and Events for Math Students and Early Career Researchers,    Public Lectures and Outreach

Data for Policy CIC & Leiden University

Data for Policy envisions a future where data-driven technologies shape a more equitable and informed world. At the forefront of this vision is the concept of twin transitions—digital and green transformations—that form the heart of the 2025 conference theme, “Twin Transitions in Data and Policy for a Sustainable and Inclusive Future”. This theme emphasizes how data-driven strategies can address complex issues like environmental impact and social equity.

Community Manager;     Email: communications@dataforpolicy.org

Twin Transitions, Data Policy, Data Science, Artificial Intelligence, Digital Transition, Digital Inovation, AI Governance

Political science,    Neural Networks and Artificial Intelligence, Machine Learning

European Molecular Biology Organization (EMBO)

Bayes Business School, University of London

The conference brings together academics and practitioners in areas including data science, analytics, machine learning, artificial intelligence and InsurTech, as applied in the insurance industry.

Email: https://insurancedatascience.org/

ICAS - University of Catania, Italy

IAISS 2025 is a full-immersion 5-day Summer School in Tuscany on cutting-edge advances in AI and Generative AI with lectures delivered by world-renowned experts. 

Event Secretariat;     Email: iaiss@icas.cc

Artificial Intelligence, Generative Artificial Intelligence, Large Language Models, Foundation Models, Deep Learning, Machine Learning

Neural Networks and Artificial Intelligence, Machine Learning,    Natural Language Processing, Computational Linguistics

South African AI Association

Back for its 8th edition, AI Expo Africa is the largest Enterprise AI trade event and conference in Africa. AI Expo Africa 2025 will run 29-31st Oct 2025 in Johannesburg South Africa at the prestigious Sandton Convention Centre, uniting 2500 decision makers, investors, buyers, suppliers, innovators, SMMEs and global brands. This year it will also be joined by the inaugural UN ITU AI4Good Impact Africa Summit focused on how AI can be used to solve the UN SDGs.

Event Manager;     Email: enquiries@aiexpoafrica.com

Machine / Deep Learning Business Solutions RPA / Intelligent Process Automation CX / UX / Chatbots / Conversational AI Avatars / Agents / Autonomous Enterprise Platform AI / NLP / LLMs / SLMs Creative Media / Generative AI Big Data / Data Ops / Analytics Cloud / Data Centre / Storage / Super Computing ML Ops / Frameworks AI in Security & DevSecOps IoT / Mobile / Edge AI Smart Devices / Hardware Autonomous Systems / Industrial Robots AR VR / Mixed Reality / Metaverse / Web3 Training / Education & Skills Women in AI Applied University R&D AI4Good / Ethics / Privacy / Standards Regulation / Policy / Responsible AI Smart Cities / Smart Society & Smart Citizen National AI Strategies / Community Building / Investing

Implementation and Applications of Artificial Intelligence,    Neural Networks and Artificial Intelligence, Machine Learning

This workshop, sponsored by AIM and the NSF, will bring together researchers from across the mathematical sciences to apply a broad range of mathematical, statistical, and data science tools to study the mathematical sciences community. The workshop will include both researchers currently working in this area, as well as researchers new to the field interested in applying their expertise to this area.

Developing MetaMath as an example of using mathematical, statistical, and computational methods to investigate the mathematical sciences community itself. Catalyzing research collaborations aimed at using data to answer questions about the mathematical sciences community. Exploring the variety of mathematical, statistical, and data science techniques that can be applied to gain insight into the systems and structure of the mathematical sciences community.

General Mathematical Research and Multidisciplinary Events,    Applied Mathematics (in general)