Description

This one-day, hands-on workshop introduces participants to single-cell RNA-seq analysis on RCAC systems using a 10x Genomics dataset and the Seurat framework. The workshop focuses on practical, end-to-end analysis, including quality control, normalization, clustering, visualization, and basic cell type annotation.

Emphasis is placed on running scRNA-seq workflows efficiently on RCAC HPC resources and understanding key analysis decisions commonly encountered in real-world single-cell studies.

Who should attend

• Researchers and students working with single-cell RNA-seq data
• Users planning to analyze 10x Genomics datasets
• Bioinformaticians seeking hands-on experience with Seurat on HPC systems

What you’ll learn

• scRNA-seq quality control and filtering using Seurat
• Clustering and visualization of single-cell data
• Downstream analysis and basic cell type annotation
• Practical considerations for running scRNA-seq workflows on RCAC

Level

Intermediate. Basic familiarity with RNA-seq concepts and the command line is recommended.

Registration: Register here (opens 04/09/2026)

Who Should Attend

Researchers interested in building reproducible, automated genomics workflows using modern workflow managers.

What You’ll Learn

• Core concepts behind reproducible workflows
• Structure and components of a Nextflow pipeline
• When and why to use workflow systems in bioinformatics

By the End of the Session, You’ll

• Understand how Nextflow enables reproducible analyses
• Be able to read and reason about simple Nextflow workflows
• Know how workflows fit into HPC and collaborative research

Level

Intermediate. Prior exposure to command-line tools is helpful.

🔗 Register now: Click here to register

• Host: Purdue RCAC, Envision Center
• When: Monday, April 20 | 2:30 PM – 4:30 PM
• Where: WALC 2124
• Other information: No registration needed

Overview: The XR Forum will serve as a community discussion space for faculty and researchers to share and learn on topics of XR in academia. As a continuation from previous XR symposiums, this event is designed to bring researchers together to share their knowledge, best practices, lessons learned, and pain points to further improve the experience in leveraging immersive technologies. This forum is also intended to help connect researchers to existing resources and establish opportunities to connect researchers with common goals.

Topics:

• Hardware, support, sustainability and resources
• Consumer & enterprise equipment/resource landscape
• XR Research and IRB
• Collaborative opportunities and Grants
• Demos & Discussions

Agenda:

• 2:30-3:00 Arrival, Welcome, and Introductions
• 3:00-4:00 Forum discussion topics
• 4:00-4:30 Wrap up, break-out discussions and demos

• Host: Purdue RCAC, Center for Research Software Engineering (RSE)

• When: Friday, April 17 | 9:00 AM – 12:30 PM

• Where: STEW 202

• For more information, please visit: https://www.cyberfaces.org/learn/course/351-streamci-spring-workshop-

• Other information: Breakfast pastries, coffee, tea, and lunch will be provided

• Registration Link and Deadline: April 3rd, 2026 https://purdue.ca1.qualtrics.com/jfe/form/SV_4VDLOdrxDAlxaia

Workshop Overview: The StreamCI Spring Workshop will bring together researchers, research software engineers, and cyberinfrastructure partners to explore how StreamCI, a real-time sensor data management and processing infrastructure, can accelerate research, enable new analytical workflows, and support scalable, reproducible science. Funded by the NSF CSSI program, StreamCI is an AI-ready streaming data platform designed to support diverse scientific applications. It addresses the need to significantly lower the barrier for domain scientists to manage their sensor data and develop streaming data–driven ML/AI models, analyses, and applications. This workshop will highlight StreamCI’s capabilities and opportunities for collaboration. The team will also provide a live demonstration of the platform, and faculty researchers will present active science use cases that illustrate how StreamCI supports their data-driven research.

Intended Outcomes for participants:

• Gain clarity on how StreamCI can support their research
• Identify potential pilot projects or collaborative opportunities in the future
• Connect with RSE and cyberinfrastructure partners at Purdue

Agenda:

• 9:00-9:15 Arrival, Coffee & Informal Networking
• 9:15-9:30 Welcome, Workshop Framing, and Use Cases Overview
• 9:30-10:30 SteamCI Architecture and Capabilities. Live Demo
• 10:30-11:30 Faculty Research Highlights & Data Use Cases and use case demos

1. UC1 - Energy Sustainability
2. UC2 - Crop health and pesticide control
3. UC3 - Precision audiology
4. UC4 – Pavement Monitoring

• 11:30-12:30 QandA, Remarks, working session
• 12:00-12:30 Lunch and networking

Faculty, staff, and students are invited to present or attend!

First event: April 10, 2026 @ 10am EST To attend, please register here: REGISTRATION

Presentation Callout

If you would like to present at our April 10th launch event, or any future events, please fill out the interest form: Presenter Proposal Form

Information for Presenters:

• Presenter proposals due: April 5, 11:59 PM EST (Fast Approaching!)
• Presentation formats: Lightning Talk, Standard, or Extended
• Proposal: 2–5 sentence description of your talk

Choose between a:

• Lightening Talk (5-10mins)
• Standard Presentation (20-30mins)
• Extended Presentation (45mins)

Why present?

• Share your work with WHPC
• Practice presenting in a supportive space
• Shape the future of WHPC technical programming

This opportunity is open to all experience levels—first-time presenters encouraged! Please feel free to share this page with colleagues who may be interested in attending or presenting!

Who Should Attend

Researchers working with sequencing data who want to understand and apply quality control best practices.

What You’ll Learn

• Common QC metrics for genomics data
• Tools used for assessing sequencing quality
• How QC decisions affect downstream analyses

By the End of the Session, You’ll

• Be able to interpret common QC reports
• Understand when data quality is sufficient for analysis
• Make informed decisions about filtering and preprocessing

Level

Basic. Suitable for newcomers to genomics data analysis.

🔗 Register now: Click here to register

This seminar series brings Purdue faculty and researchers together to explore AI opportunities and build connections across campus and NSF-supported programs. Each session features two 20-minute faculty talks followed by 20 minutes of Q&A and networking. In each session, you will:

• Hear short talks showcasing AI work across diverse disciplines
• Meet and network with faculty interested in AI research and teaching
• Share your challenges and expectations with Purdue AI Hubs admins.
• Participate in open discussion and Q&A
• Learn about Purdue and NSF AI, computing, and data services
• Join the conversation and help shape the future of AI at Purdue.

The series is open to anyone at the university and registration is not required. Please join us in helping to advance AI at Purdue!

Schedule:

All sessions take place from 3-4 p.m. in DSAI 1069

• Februray 10: Professor Nikhilesh Chawla (Materials Engineering), Professor Alexandra Boltasseva (Electrical and Computer Engineering)
• March 3: Professor Yan Gu (Mechanical Engineering), Professor Jinha Jung (Civil and Construction Engineering)
• March 10: Professor D. Marshall Porterfield (Agricultural and Biological Engineering), Professor Yaguang Zhang (Agricultural and Biological Engineering)
• March 24: Professor Vanesa Cañete Jurado (College of Liberal Arts), Professor Maurice Tetne (College of Liberal Arts)
• April 7: Professor Edwin Garcia (Materials Engineering), Professor Romit Maulik (Mechanical Engineering)
• April 21: Professor Prianka Baloni (Health Sciences), Professor Mia Liu (Physics and Astronomy)
• April 28: Professor Mustafa Abdallah (Computer and Information Technology), Professor Rua M. Williams (Applied and Creative Computing)

Details of talks will be published the week before each event through RCAC and IPAI mailing list. Please subscribe to our RCAC newsletter and our IPAI newsletter for more information.

Who Should Attend Researchers and students who want to learn more about Large Language Model (LLM) fine-tuning and compression techniques such as Low-Rank Adaptation (LoRA) and QLoRA, and learn the step-by-step process for creating production-ready fine-tuned LLMs.

What You’ll Learn The motivation behind LLM fine-tuning and the differences between full fine-tuning and parameter-efficient fine-tuning (PEFT) How Low-Rank Adaptation (LoRA), Quantized LoRA (QLoRA), and other popular PEFT methods work Key LoRA hyperparameters, their roles, and recommended starting values The fundamentals of LLM compression and quantization How to create GGUF files for production-ready deployment A step-by-step walkthrough of a typical LoRA fine-tuning process using Mistral 7B with Unsloth

By the End of the Session, You’ll Learn how to fine-tune your own LLM using LoRA and run it locally with Ollama Understand the architectural differences and tradeoffs between LoRA and other PEFT methods in terms of accuracy and efficiency

Level Intermediate. Familiarity with basic machine learning concepts such as model training and evaluation, neural networks, and Python-based ML workflows is recommended. Prior exposure to LLMs and Ollama is helpful but not required. 🔗 Register now: LINK

⏰ Time: 1:00-2:30

💻 Location: Online ( Teams)

🏫 Instructor: Jacob Verburgt

This is a 4-week workshop that will happen on Fridays in April from 1:00 PM - 2:30 PM Eastern time.

Who Should Attend

People who are starting to use High Performance Computing systems and want to learn how to use them. There is no prior knowledge/experience requirement to attend these workshops.

What You’ll Learn

By the end of the four 90 minute sessions, you’ll feel confident in your ability to navigate HPC systems and use them to run your workflow. You will learn basic Unix commands as well as HPC-specific ones. By the end, you should be equipped to create scripts and run applications on Purdue's supercomputing clusters.

Week 1 - Friday, April 3rd, 2026 - Unix basics

Week 2 - Friday, April 10th, 2026 - HPC basics

Week 3 - Friday, April 17th, 2026 - Advanced Unix

Week 4 - Friday, April 24th, 2026 - Advanced HPC

Level

Beginner - No experience needed

🔗 Register now: LINK

Fundamentals of Distributed Memory Parallelism is a 1-hour introductory training session covering the basic concepts of parallel computing across multiple processes and nodes. Participants will learn how distributed memory systems work, why message passing is needed, and the core ideas behind MPI, including ranks, communication, and data distribution. The session also introduces common challenges such as communication overhead and load balancing in HPC applications. 🔗 Register now: LINK

Operational practices for machine learning are evolving to support large language models and other generative AI systems. The session will cover the lifecycle of building, deploying, and maintaining generative AI applications, including topics such as model and prompt management, evaluation challenges, monitoring, and scalable deployment architectures. 🔗 Register now: LINK

Who Should Attend

Researchers and students who want to run bioinformatics software efficiently on RCAC clusters.

What You’ll Learn

• How software is deployed and accessed on RCAC systems
• Using modules, containers, and command-line tools
• Best practices for running analyses on shared HPC resources

By the End of the Session, You’ll

• Understand how to find and run bioinformatics software on RCAC
• Know when to use modules versus containers
• Avoid common execution and environment pitfalls

Level

Intermediate. Basic command-line familiarity recommended.

🔗 Register now: Click here to register

Description

This one-day, hands-on workshop introduces participants to genome annotation on RCAC HPC systems, covering both structural and functional annotation workflows. The workshop focuses on practical annotation strategies using modern tools such as BRAKER3, Helixer, Easel, and EnTAP, with an emphasis on reproducible execution on shared compute resources.

Participants will learn how to generate and evaluate gene models using transcriptomic and homology-based evidence, interpret annotation outputs, and assess annotation quality using standard metrics. The workshop emphasizes real-world considerations, common pitfalls, and troubleshooting strategies encountered in genome annotation projects.

Who should attend

• Researchers and students working with newly assembled genomes
• Bioinformaticians interested in gene prediction and annotation workflows
• Users planning to annotate genomes using RNA-seq or protein evidence
• Anyone seeking hands-on experience with annotation pipelines on RCAC

What you’ll learn

• Core concepts of structural and functional genome annotation
• How to run gene prediction workflows using BRAKER3 and Helixer on RCAC clusters
• Interpreting and refining gene model predictions
• Functional annotation using EnTAP
• Basics of annotation quality assessment and troubleshooting

Level

Intermediate. Participants should have basic familiarity with genomics concepts, command-line tools, and bioinformatics workflows.

Registration: Register here (opens 02/26/2026)

Who Should Attend

Researchers preparing figures for publications, presentations, or grant proposals using genomics data.

What You’ll Learn

• Principles of clear and effective data visualization
• Common pitfalls in genomics plots
• Tools and approaches for generating publication-quality figures

By the End of the Session, You’ll

• Be able to design clearer, more interpretable plots
• Understand how to tailor figures for different audiences
• Improve the visual quality of your genomics results

Level

Intermediate. Familiarity with basic plotting tools is helpful.

🔗 Register now: Click here to register

🔗 Register now: Click here to register

This workshop explores the evolving landscape of Geospatial Artificial Intelligence (GeoAI) on High-Performance Computing (HPC) environments.

We'll begin with the foundational concepts of GeoAI, introducing what typical GeoAI tasks are and how AI are applied to geospatial data like satellite imagery.

Next, we'll dive into the practical tools that enable this work, and set up working environment on HPC Clusters. We'll examine the TorchGeo library, which provides a comprehensive toolkit for training models on geospatial datasets within PyTorch. We'll also cover TerraTorch, a fine-tuning and benchmarking toolkit that extends capabilities for Geospatial Foundation Models.

Finally, we'll present several case studies to illustrate the transition from traditional, single-task GeoAI models—like a model trained to identify specific land cover types—to the latest advancements in Geoscience Foundation Models. These larger, more versatile models are capable of performing specific geoscience tasks with much less new data than would be required for a traditional model. We will also introduce three ways to perform these tasks with HPC, and mainly focus on two of them with online experiments: interactive job via OoD and batch job.

⏰ Time: 1:00 PM - 2:30 PM

💻 Location: Virtual (Teams)

🏫 Instructor: Jacob Verburgt

Who Should Attend

People who are starting to use High Performance Computing systems and want to learn how to use them. There is no prior knowledge/experience requirement to attend these workshops.

What You’ll Learn

By the end of the four 90 minute sessions, you’ll feel confident in your ability to navigate HPC systems and use them to run your workflow. You will learn basic Unix commands as well as HPC-specific ones. By the end, you should be equipped to create scripts and run applications on Purdue's supercomputing clusters.

Week 1 - Friday, March  6th, 2026 - Unix basics

Week 2 - Friday, March 13th, 2026 - HPC basics

Week 3 - Friday, March 20th, 2026 - Advanced Unix

Week 4 - Friday, March 27th, 2026 - Advanced HPC   Level

Beginner - No experience needed

🔗 Register now: LINK

The Rosen Center for Advanced Computing (RCAC) invites all students, faculty, staff, industry professionals, and beyond to register for this event, Women in HPC Presents: Intersectional Voices on Double Standards and Belonging, organized by the Purdue Women in High-Performance Computing (WHPC) chapter.

This will be a 90-minute workshop and panel exploring how double standards and bias shape belonging in computing and HPC. The event is co-designed with the Black Cultural Center (BCC), the Native American Educational and Cultural Center (NAECC), and the LGBTQ Center, centering intersectional perspectives across gender, race, indigeneity, and sexuality.

What to expect

Intersectional Panel (60 minutes): Panelists affiliated with BCC, NAECC, and the LGBTQ Center will share their lived experiences and observations of double standards in classrooms, labs, research groups, and campus life, followed by a guided discussion.

Audience: Students, postdocs, staff, and faculty in computing, data, and HPC, as well as campus community members interested in inclusive technical education.

We’re grateful to Aztlan Combat Sports for generously sponsoring this event.

Please complete the short registration form to help us plan. Feel free to share this invitation with your network; we look forward to seeing you there.

Description - Advanced RAG & Vector Databases As AI systems become more widely used in research and enterprise settings, one of the biggest challenges is helping large language models work effectively with an organization’s own data. Retrieval-Augmented Generation (RAG) provides a practical solution by combining LLMs with fast, accurate retrieval from internal knowledge sources. This is supported by vector databases, which store and search information in a way that aligns with modern embedding models. This session introduces the core concepts behind RAG workflows and explains how vector databases support reliable, relevant, and grounded AI outputs. We will discuss the practical design decisions, how to structure data, choose embeddings, build retrieval pipelines, and evaluate whether the system is working as expected.

Who Should Attend - AI/ML engineers, data scientists, research software engineers, platform engineers, and technical leads who want a practical, up-to-date understanding of how RAG systems work in real environments. This session is ideal for practitioners responsible for building LLM-powered applications, selecting retrieval or vector database tooling, or supporting researchers who need trustworthy, data-grounded AI systems.

Topics - What RAG does and why it matters for modern AI applicationsHow embeddings represent text and why vector databases are used to store themThe basic building blocks of a RAG pipeline: chunking, indexing, retrieval, reranking, and generationArchitectural patterns for building effective retrieval systemsWhat impacts the retrieval quality (better chunking, metadata, hybrid search)How to evaluate the RAG system

Level - Intermediate. Attendees should understand the basics of LLMs, but no prior experience with vector databases or RAG systems is required.

🔗 Register now: LINK

Who Should Attend

Life science researchers and students who want to use R more effectively for data manipulation, analysis, and visualization.

What You’ll Learn

• Core R data structures and workflows for biological data
• Importing, cleaning, and summarizing datasets
• Practical tips for writing clearer, reusable R code

By the End of the Session, You’ll

• Be comfortable working with common biological datasets in R
• Understand how to structure R scripts for analysis
• Have a foundation for further statistical or visualization work

Level

Basic. No prior R experience required.

🔗 Register now: Click here to register

Description

This one-day, hands-on workshop introduces participants to long-read genome assembly on RCAC HPC systems using modern assemblers such as HiFiasm and Flye. The workshop emphasizes practical considerations for running assembly workflows on shared compute resources, including parameter selection, workflow organization, and common troubleshooting scenarios.

Participants will also be introduced to hybrid assembly concepts, scaffolding approaches, and assembly quality assessment, with a focus on reproducible and scalable practices suitable for real-world genome assembly projects.

Who should attend

• Researchers and students working with long-read sequencing data
• Bioinformaticians interested in genome assembly on HPC systems
• Users planning to assemble genomes using PacBio HiFi or Oxford Nanopore data
• Anyone seeking hands-on experience with genome assembly workflows on RCAC

What you’ll learn

• How to run genome assembly workflows using HiFiasm and Flye on RCAC clusters
• Key considerations for long-read and hybrid genome assembly
• Basics of assembly evaluation, polishing, and visualization
• Practical strategies for organizing and troubleshooting assembly jobs on HPC systems

Level

Intermediate.

Registration: Register here (opens 02/05/2026)