Invite Science Day 2026

Innovations, Visions & Technologies

Application of Artificial Intelligence in Drug Delivery, Robotics and Digitalization

On July 8, 2026, INVITE opens its doors for a one-day hybrid event where world-class experts and young INVITE scientists & engineers share insights into the latest applications of artificial intelligence as well as current research in the chemical and pharmaceutical industry.

Our cooperation partners and friends are cordially invited to join us for a day of knowledge exchange, networking and inspiration – including guided tours through smart automation and laboratory environments. Discover how AI is shaping current and future applications across our key research domains.

Program Highlights

Participants can join individual sessions on-site or virtually. Online access links to each session will be provided directly on this page on the event day.

Confirmed Speakers

Keynotes

Title: tbc Prof. Dr. Thomas Villmann (University of Applied Sciences Mittweida, Saxon Institute for Computational Intelligence and Machine Learning (SICIM)) 

Trusworthy AI in Scientific Discovery and Medical Therapy -

 

Drug Delivery

Digitalization of Pharmaceutical Development and Manufacturing: Status Quo and Future Perspectives – Dr. Adrian Funke (Bayer AG)

AI use cases in Life Science R&D – Dr. Georg Mogk, Dr. Oliver Staudt (Bayer AG)

 

Robotics

KI im Engineering industrieller Robotik - Thomas Hohenwarter Gluth Systemtechnik GmbH

Flexible Robotics enabled by AI and Industrial Ecosystems - tbc

Opportunities for Physical AI in Multipurpose Lab Robotics – tbc

 

Digitalization Enabling Sustainability

CogniFlow - Ontology-driven standardization for FAIR data processing – Dr. Gerrit Renner (University Duisburg-Essen), Dr. Ricardo Cunha (IUTA)

On the Feasibility of LLM-Based Operator Support in Industrial Control Rooms under Brownfield Constraints – Dr. Heiko Brandt (Bayer AG), Patryk Bakalarz (INVITE)

Identification of Low-Intensity Peaks and Single-Event Signals in Mass Spectrometry Data Using Machine Learning – a feasibility study – Dr. Kevin Eckey (Merck KGaA), Aaron Rüthing (TU Dortmund)

Registration

Please register in advance via our online registration. Online Registration