
ZEISS Launch Event at Lab Central
Integrated Software Solutions
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ZEISS Event Agenda
Harness powerful AI analysis using ZEISS software with the Acquifer HIVE Server at Lab Central.
ZEISS is working with Lab Central to increase throughput and image analysis capabilities for all Lab Central residents. This event will showcase the power of the ZEISS digital ecosystem with Acquifer HIVE server processing and data routing. We want to help you uncover new ways to visualize and analyze your imaging data, and peer deeper into your science with cutting-edge technologies.
The ZEISS Digital Ecosystem – which includes our software suite of ZEN, APEER, and arivis – integrates automated image capture with software for data analysis, routing, and processing within the Lab Central network. Paired with the Acquifer HIVE server, this allows several users to process complex, multi-dimensional analysis of large image sets simultaneously. Let us help you automate your imaging workflows from image to results – take your research to the next level and scale your throughput!
Sign-up below and we will follow up with a demo worksheet to outline your experiments and the analysis you want to perform!
NOTE: We invite all participants to provide experimental imaging data prior to and part of the software trainings. By doing so, you will be able to take advantage of pre-built analysis pipelines and capabilities. This will allow the training to be more relevant and meaningful to your applications, while giving you customized analysis from day one.
If you don’t have an application or data to share for the launch event, we can work with you moving forward to build analysis capabilities OR demo one of our pre-trained workflows.
Kick-off Presentation
Join us for our event kick-off presentation on Tuesday, February 28th at 11:00 AM EST.
We will have our presentation and software overview in the atrium with a ZEISS sponsored luncheon. Software trainings and demos will begin thereafter.
Kick-off Presentation

Kevin O'Keefe
Senior Software Sales Biotech Pharma
Prior to joining ZEISS Kevin O’Keefe completed his Ph.D. at the University at Albany, SUNY, where he gained extensive experience in widefield, confocal microscopy and image analysis with a focus on tissue multiplexing following injury in the mouse submandibular salivary gland. After graduating Kevin started his career at ZEISS as a Product Application Sales Specialist and covered NY, NJ and PA working with ZEISS hardware including advanced 3D imaging systems. Recently, Kevin has joined the software sales team as the Senior Software Sales Representative with a concentration in biotech and pharma. He focuses on using the ZEISS toolkit for image analysis including ZEN, APEER and Arivis to help translate images into actionable data.

Chris Zugates
Head of Customer Success at ZEISS Microscopy
Prior to joining ZEISS, Chris was the VP of US Operations at arivis. He now is the Head of Customer Success for ZEISS Microscopy. He has a PhD in Cell and Developmental Biology from the University of Illinois Urbana-Champaign.
Register Today
Register to attend the event and select if you would like a demo.
Visualization & Analysis of Big Image Data
arivis Vision4D is your modular software for working with multi-channel 2D, 3D and 4D images of almost unlimited size, highly scalable and independent of local system resources. Many modern microscope systems such as high-speed confocal, light sheet / SPIM, super-resolution, electron microscopy or X-ray instruments can produce huge amounts of imaging data.
Accelerate your R&D with Automated Image Analysis
APEER by ZEISS provides AI-driven, automated image analysis solutions that enable researchers to push the boundaries of traditional methods. With APEER you can easily train your AI model for image segmentation. Create and customize your image analysis application with a few clicks. Integrate your trained model with end-to-end automated pipelines. Save time by reducing repetitive manual steps and avoid human errors by using advanced automated solutions for image analysis. Improve your throughput without compromise on the quality and reproducibility of your results.