Event

November 18 2025

AI MSE (Artificial Intelligence in Material Science) – Bochum 2025

Redefining Materials Science through Artificial Intelligence.
Accelerating discovery, enhancing innovation, and transforming engineering processes.

The 2nd Conference on Artificial Intelligence in Materials Science and Engineering (AI MSE 2025) successfully brought together an inspiring community of researchers, industry leaders, and innovators to explore the rapidly evolving intersection of artificial intelligence and materials science. Organized by the Deutsche Gesellschaft für Materialkunde (DGM) and hosted at Ruhr-University Bochum—with a global online audience joining in—this year’s event showcased just how quickly the field is advancing.

SciSpot is proud to have been part of this exciting event and to contribute to the growing dialogue around the future of AI-driven materials research.

Event Highlights

Cutting-Edge Research
Participants presented groundbreaking work demonstrating how AI, deep learning, and machine learning are reshaping materials design, characterization, and prediction.

Engaging Expert Panels
Thought leaders from academia and industry shared insights into current challenges, emerging opportunities, and the future direction of AI-enabled materials science.

Vibrant Networking
The conference fostered new connections and collaborations, both in person and online, strengthening the global community working at the forefront of this transformative field.

Key Themes

Microstructure Characterization and Reconstruction:
AI-driven, image-based techniques for analyzing and reconstructing complex microstructures.
Property and Microstructure Prediction:
Machine-learning approaches applied across atomistic and continuum simulations.
Materials Discovery:
Accelerating the search for novel materials through data science and AI-guided optimization.
NLP and Large Language Models:
Leveraging text mining and AI tools to extract, structure, and utilize materials knowledge.
Emerging Data Science Technologies:
New computational methods with strong potential for future impact in materials research.

Emerging Technologies Track

This year introduced a dedicated track highlighting innovative data-science approaches not yet widely used in materials science but poised to become influential in the years ahead.

AI MSE 2025 once again demonstrated the power of interdisciplinary collaboration. SciSpot is grateful to have taken part in a conference that continues to push the boundaries of what is possible when AI and materials science meet. We look forward to supporting and engaging with this community in future events.

October 3 2024

MSE (Material Science and Engineering) – Darmstadt 2024

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The leading international Materials Science and Engineering Congress in Germany.

With over 1,200 participants, SciSpot had the pleasure of presenting the Next-Gen AI image analysis techniques.

Materials characterization using deep learning image analysis

Sammy Nordqvist1* (S. Nordqvist), John Sosa2 (J. Sosa), Michael Kudlinski2 (M. Kudlinski), Alisa Stratulat2
(A. Stratulat), Dr. Simone Langner3 (S. Langner)
1 SciSpot, Aspvägen 13, Stenungsund, Sweden, 2 MIPAR Image Analysis Software, 8050 N High St, Ste 170,
Columbus, OH 43235, United States, 3ADDITIVE Soft- und Hardware für Technik und Wissenschaft GmbH, MaxPlanck-Str. 22b, D-61381 Friedrichsdorf, Germany *sammy@scispot.se

Background

For scientists and engineers across various disciplines, image analysis serves as a vital tool for gaining
deeper insights into complex phenomena. Whether studying biological structures, geological
formations, engineering components, or materials microstructures, the ability to extract quantitative
data from images is invaluable. Image analysis enables engineers and researchers to replace manual
analysis and increase productivity, gain additional data insights improve statistics, and advance
their work by solving complex problems. By harnessing the power of image analysis, scientists and
engineers can accelerate research, optimize manufacturing processes, and improve the performance of
products across a wide range of fields, ultimately advancing our understanding of the natural world and
improving technology.
Figure 1. Next-generation detection using real-time processing leads to improved detection visualization (right side).

Method and results

Using deep learning and powerful image analysis engines, MIPAR (www.mipar.us) allows users to
perform fast, accurate, and automated analysis of images. Through a user-friendly interface, engineers
and researchers can personalize analysis to their samples as well as visualize and extract measurements
– all without programming. Through five integrated applications, MIPAR offers flexibility and efficiency
for 2D and 3D analysis applications. The key ingredients are in the Recipes, which include a series of
analysis steps that are tailored to each application. As a result, researchers and engineers can now easily
solve problems such as grain size analysis excluding twins, particle analysis of clusters, defect
identification, and many more.
Seamlessly integrated within the MIPAR ecosystem, the Snap tool, powered by Spotlight, offers
accelerated creation of training datasets for an efficient and streamlined model training workflow. The
accurate segmentations provided by Spotlight allow for less time spent creating models and algorithms,
leading to faster data collection. MIPAR Spotlight simplifies image analysis further by limiting the
need for custom model configurations and amplifying a model’s ability.

Conclusion

This presentation will overview the advantages of using MIPAR Spotlight, the new cutting-edge of
detection, to analyze grains, particles, droplets, and defects with real industrial applications

: Materials Science and Engeneering Congress in Darmstadt 2024

: Lecture in AI-image analysis

: Technical University in Darmstadt

September 5 2024

EMC (European Microscopy Congress) – Copenhagen 2024

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Spotlight: Shedding Light on Next-Generation Detection for Microscopists.

EMC is the 17th of its kind and will bring the world of scientific imaging together in one of Europe’s most beautiful cities.

Copenhagen, Denmark. 25th – 30th September 2024

MIPAR Spotlight: Shedding Light on Next-Generation Detection for Microscopists

Background
For scientists and engineers across various disciplines, image analysis is a vital tool for gaining
deeper insights into complex phenomena. Whether studying biological structures, geological
formations, engineering components, or materials microstructures, the ability to extract quantitative
data from images is invaluable. Image analysis enables engineers and researchers to replace manual
analysis and increase productivity, gain additional data insights, improve statistics, and
advance their work by solving complex problems. By harnessing the power of image analysis,
scientists and engineers can accelerate research, optimize manufacturing processes, and improve
the performance of products across a wide range of fields, ultimately advancing our understanding of the
natural world and improving technology.

Method and results
Using deep learning and powerful image analysis engines, MIPAR (www.mipar.us) allows users to
perform fast, accurate, and automated analysis of images. Through a user-friendly interface,
engineers and researchers can personalize analysis to their samples and visualize and extract
measurements – all without programming. Through five integrated applications, MIPAR offers
flexibility and efficiency for 2D and 3D analysis applications. The key ingredients are in the Recipes,
which include a series of analysis steps tailored to each application. As a result, researchers
and engineers can now easily solve problems such as grain size analysis excluding twins, particle
analysis of clusters, defect identification, and many more.
Seamlessly integrated within the MIPAR ecosystem, the Snap tool, powered by Spotlight, offers
accelerated creation of training datasets for an efficient and streamlined model training workflow.
The accurate segmentations provided by Spotlight allow for less time spent creating models and
algorithms, leading to faster data collection. MIPAR Spotlight simplifies image analysis even further
by limiting the need for custom model configurations and amplifying a model’s ability.

Conclusion
This presentation will overview the advantages of using MIPAR Spotlight, the new cutting-edge of
detection, to analyze grains, particles, droplets, and defects with real industrial applications.

“Unleashing the Power of SigmaPlot: Transforming Data into Insight”

October 3 2023

Life Science Baltics – Congress in Vilnius

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We are proud to be sponsoring the Life Sciences Baltics event in Vilnius and demoing the new exciting SigmaPlot NG release – Unleashing the Power of SigmaPlot: Transforming Data into Insight.

Life Science Baltic – Vilnius 2023

We are proud to be sponsoring the Life Sciences Baltics event in Vilnius and demoing the new exciting SigmaPlot NG release – Unleashing the Power of SigmaPlot: Transforming Data into Insight.

This event is a brilliant platform that brings together top decision-makers and the next generation of founders and talents from the Baltics, all in one place.

They will be joined by CEOs of companies and startups, tech scouts, and researchers from all around the world, to create a potential for deep cooperation across traditional boundaries and take up a lasting learning journey.

: “Unleashing the Power of SigmaPlot: Transforming Data into Insight”

September 14 2023

FEMS EUROMAT23 Wraps up in Frankfurt

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Showcasing Cutting-Edge Advances in Material Science!

Leading Experts Converge to Explore the Future of Materials Research, Frankfurt, Germany, 3-7 September 2023

The highly anticipated FEMS Euromat23 conference concluded last week in Frankfurt, bringing together a diverse array of professionals, thought leaders, and innovators from the field of material science. The event provided a platform for engaging discussions, insightful presentations, and invaluable networking opportunities.

Exploring Pioneering Breakthroughs

FEMS Euromat23 showcased the latest advancements in material science, encompassing a wide spectrum of disciplines from biomaterials to nanotechnology. Attendees were treated to a series of expert-led sessions that delved into topics ranging from the development of novel materials to their applications in various industries.
In addition to the conference sessions, the exhibition hall featured a diverse range of exhibitors, each showcasing their latest research findings, technologies, and solutions. From groundbreaking composite materials to state-of-the-art analytical techniques, attendees had the opportunity to explore a wide spectrum of offerings.

Fostering Collaboration and Networking

FEMS Euromat23 provided an invaluable platform for professionals to connect, share insights, and forge meaningful collaborations. Attendees praised the event’s ability to create an atmosphere conducive to meaningful interactions, ultimately advancing the field of material science.

Looking Ahead

As the curtains close on FEMS Euromat23, researchers, academics, and industry professionals leave with a deeper understanding of the cutting-edge breakthroughs and innovations that are shaping the future of material science. The event’s success sets a promising tone for continued advancements in this critical field.

For more information about FEMS and future events, please visit https://euromat2023.com/ or visit SciSpot at www.scispot.eu

June 12 2023

SCANDEM 2023 – Sweden Uppsala

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Nordic Microscopy Society, SCANDEM2023, will be organized at Uppsala, Sweden, 12-15 June 2023.

We present materials characterization using deep learning image analysis.

The quick development of materials relies on the understanding of material microstructure
(size, porosity, morphology, etc.), a reliable manufacturing process, and a thorough analysis of
the performance for different applications. To solve some of the research challenges, automated,
reliable, and intelligent analysis techniques are needed.

Using deep learning and a powerful image analysis engine, MIPAR [1] (www.mipar.us) allows
users to perform fast, accurate, and automated analysis of images. In three simple steps: trace,
train and apply, researchers can create a model that identifies the features of interest and run
personalized recipes on new images to detect complex features.

This presentation will overview the advantages of using modern analysis techniques to analyze
particles, fibers and pores, droplets, defects, contaminants, and phases with real research
applications.

Figures/Tables

Figure 1 Detecting grains while ignoring twins using MIPAR. Model was trained on 25 images
in 40 minutes and applied to new images in 2 seconds

Figure 2 Overlapping nanofiber network analysis performed using MIPAR. Model was trained
on 36 images in 40 minutes and applied to new images in 1.5 seconds.

References
[1] Sosa, J. M., et al. “MIPAR™: 2D and 3D Image Analysis Software Designed by
Materials Scientists, for All Scientists.” Microscopy and Microanalysis 23.S1 (2017):
230-231.

November 20 2022

BioTechX – Switzerland

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We’re excited to be at BioTechX in Basel!
Let´s discuss how image analysis and data analytic technologies can support you in solving complex design and manufacturing challenges.

Join SciSpot – Scientific Solutions to exchange ideas and experience how image analysis and data analytic technologies can support you in solving complex design and manufacturing challenges Register using our promo code: SNOBALL20 and save an additional 20% on top of base discounts! For Pharma, Academic/Health System, you can apply for a free pass. We are looking forward to discussing your challenges and seeing you soon!