Is your groundbreaking research trapped by sluggish, inefficient bioinformatics workflows?
What you’ll learn:
- Identify & avoid critical roadblocks: Learn to recognize common pitfalls in large-scale data projects to improve project success rates.
- Explore powerful acceleration technologies: Get insights into leading hardware acceleration options (FPGA, GPU) for demanding bioinformatics analyses.
- Streamline your path to production: Discover practical strategies for efficiently moving bioinformatics prototypes to robust, production-ready pipelines.
- See real-world performance gains: Understand how optimized approaches can lead to significant cost savings and faster turnaround times through concrete examples.
Who should attend
This webinar is ideal for:
- Bioinformatics Leaders & Computational Biology: Looking to boost team efficiency and scale omics workflows.
- Bioinformaticians & Computational Scientists: Seeking faster, high-performance solutions for complex analyses.
- Pipeline Developers: Focused on building scalable, cost-effective production systems.
Featured topics
Why traditional large-scale bioinformatics workflows often slow you down—and how to spot the hidden costs before they hit.
How NVIDIA Parabricks can help you run variant calling faster and more efficiently, with real numbers to show the difference.
What happens when you supercharge single-cell workflows with GPU acceleration—using NVIDIA RAPIDS to get real speed gains.
Practical tips on how to move your workflows from prototypes to scalable, production-ready systems that actually hold up.
Real stories and lessons learned: see how teams at Ardigen and NVIDIA tackled real-world challenges and built better, faster pipelines.
Meet our speakers:
Hassan Sirelkhatim
Hassan Sirelkhatim is a Senior Solutions Architect with a focus on the intersection of machine learning and biology. He has played a key role in advancing foundation models in areas such as nucleotides, proteins, and chemical structures. In his day-to-day work, he partners with customers to optimize their machine learning models for efficient performance on GPUs.
Kamil Malisz, Ardigen
Kamil is a life science software engineer with 7 years of experience, currently Lead Nextflow Developer and Bioinformatic Workflows Offering Manager at Ardigen. He develops pipelines across domains from phage display to whole-genome sequencing. A Jagiellonian University bioinformatics graduate, he combines strong biology knowledge with Nextflow expertise and project management skills, including two years as a Tribe Leader. He also supports strategic partnerships, driving innovation in bioinformatics workflows.
