In this free webinar, Dave DeMarle will provide an overview of Kitware’s Visualization Toolkit. Learn about the origin of VTK, its diverse developer pool and understand its core capability – analyzing 3-dimensional scientific data sets. Don’t miss this opportunity to learn about this state-of-the-art open source software toolkit and ask Dave, one of our Kitware experts, your questions about VTK. Please register here.

Date: October 7, 2019

Time: 11:00 a.m. EDT

Length: 20 mins

Join Dr. Rachel Clipp, Technical Leader, and Aaron Bray, Staff R&D Engineer, from Kitware’s Medical Computing Team on October 9 at the Defense TechConnect Summit.

Poster Session
Wednesday, October 9, from 3:00 to 4:00 p.m. ET

Overview of the Pulse Physiology Engine and its use in Medical Training and Simulation

Kitware’s Director of Medical Computing Andinet Enquobahrie and Senior Director of Strategic Initiatives Stephen Aylward will present at the International Conference on Medical Image Computing and Computer Assisted Intervention.

Development and Face Validation of Ultrasound-Guided Renal Biopsy Virtual Trainer

To be presented at a joint workshop MIAR, AE-CAI and CARE

The 7th International Conference on Medical Imaging and Augmented Reality (MIAR)
The 13th Augmented Reality, Augmented Environments for Computer Assisted Interventions (AE-CAI),
and 6th Computer Assisted and Robotic Endoscopy (CARE)

https://workshops.ap-lab.ca/aecai-care-miar-2019/

Abstract: The overall prevalence of chronic kidney disease (CKD) in the general population is approximately 14 percent with more than 661,000 Americans having a kidney failure. Ultrasound-guided renal biopsy is a critically important tool in the evaluation and management of renal pathologies and it requires competent biopsy technique and skill to consistently obtain high yield biopsy samples. This paper presents KBVTrainer, a virtual simulator that we developed to train clinicians to improve procedural skill competence in ultrasound-guided renal biopsy. The simulator was built using low-cost hardware components and open source software libraries. We conducted a face validation study with five experts who were either adult/pediatric nephrologists or interventional/diagnostic radiologists. All the experts had considerable experience performing US guided needle biopsies within their specialty with experience ranging from 3-23 years. The trainer was rated very highly (>4.4) for the usefulness of the real US images (highest at 4.8), potential usefulness of the trainer in training for needle visualization, tracking, steadiness and hand-eye coordination, and overall promise of the trainer to be useful for training US guided needle biopsies. The lowest score of 2.4 was received for the look and feel of the US probe and needle compared to clinical practice. The force feedback received a moderate score of 3.0. The clinical experts provided abundant verbal and written subjective feedback and were highly enthusiastic about using the trainer as a valuable tool for future trainees. As part of the future work, we will improve the technology based on clinical and user feedback, develop automated skill assessment and tracking modules deployable in a web-based application, and conduct a clinical validation study.

Active Learning Technique for Multimodal Brain Tumor Segmentation using Limited

To be presented at Medical Image Learning with Less Labels and Imperfect Data

https://www.hvnguyen.com/lesslabelsimperfectdataml

Abstract: Image segmentation is an essential step in biomedical image analysis. In recent years, deep learning models have achieved significant success in segmentation. However, deep learning requires the availability of large annotated data to train these models, which can be challenging in biomedical imaging domain. In this paper, we aim to accomplish biomedical image segmentation with limited labeled data using active learning. We present a deep active learning framework that selects additional data points to be annotated by combining U-Net with an efficient and effective query strategy to capture the most uncertain and representative points. This algorithm decouples the representative part by first finding the core points in the unlabeled pool and then selecting the most uncertain points from the reduced pool, which are different from the labeled pool. In our experiment, only 13% of the dataset was required with active learning to outperform the model trained on the entire 2018 MICCAI Brain Tumor Segmentation (BraTS) dataset. Thus, active learning reduced the amount of labeled data required for image segmentation without a significant loss in the accuracy.

Intramodality Domain Adaptation using Self Ensembling and Adversarial Training

To be presented at Domain Adaptation and Representation Transfer (DART) workshop

https://sites.google.com/view/dart2019/

Abstract. Advances in deep learning techniques have led to compelling achievements in medical image analysis. However, performance of neural network models degrades drastically if the test data is from a domain different from training data. In this paper, we present and evaluate a novel unsupervised domain adaptation(DA) framework for semantic segmentation which uses self ensembling and adversarial training methods to effectively tackle domain shift between MR images. We evaluate our method on two publicly available MRI dataset to address two different types of domain shifts: On the BraTS dataset to mitigate domain shift between high grade and low grade gliomas and on the SCGM dataset[13] to tackle cross institutional domain shift. Through extensive evaluation, we show that our method achieved favorable results on both datasets.

“Proposal Writing 101” at the MICCAI “Tutorial On Publishing, GRant writing And career Development” (TOPGRAD) workshop

Presented by Kitware’s Senior Director of Strategic Initiatives Stephen Aylward on October 13th

Abstract: The TOPGRAD tutorial provides advice on publishing, grant writing and career trajectories in the MICCAI field. The tutorial will consist of a number of talks and discussion on the review process, publishing strategies (including open access) and grant writing requirements. Moreover, we hold an extensive Q&A session between early career researchers and experts in the relevant fields.

Dr. Ken Martin and Cory Quammen will speak about ParaView, Kitware’s open-source, multi-platform data analysis and visualization application that runs on everything from laptops to supercomputers.

Kitware will be presenting 7 courses over four days in July (22-25) at our new Albany NY Headquarters.

Monday July 22

Morning: Introduction to 3D Web visualization

Modern development is pushing applications to run inside Web environments. This course will introduce vtk.js and ParaViewWeb, and explain how these tools enable 3D Visualization inside your web browser.

Afternoon: Managing your data with Girder

Girder is a free and open source web-based data management platform. This course will provide an overview of Girder, including various use cases and extensibility for end-to-end data management, analytics, and visualization.

Tuesday July 23

All Day: CMake and Friends

CMake is open-source software for managing the build and test process of software using compiler-independent methods. This course will teach users the fundamentals of CMake and CTest through a mix of lectures and hands on tutorials.

Wednesday July 24

Morning: Introductory and applied VTK

At this introductory course, attendees learn the fundamental concepts that all users and developers need to know to work with The Visualization Toolkit. A curated selection of hands on exercises, in either C++ or Python, give students first hand experience with VTK’s fundamentals: data structures, data processing and rendering, and user interaction. The course material is annotated with recommended resources for further learning.

Afternoon: Tomviz: Tomography Data from Acquisition to Analysis and Visualization

The course will introduce you to the Tomviz desktop application (Windows, macOS, and Linux binaries available) with a focus on materials tomography data. We will cover the complete pipeline from data acquisition on a TEM microscope to projection image alignment and reconstruction. The more general analysis and visualization of reconstructed tomography data will be covered, along with exporting movies, web scenes, and data. Some advanced topics to be covered include running the pipeline in Docker and adding custom Python-based operators.

Thursday July 25

Morning: A hands on introduction to ParaView

Paraview is an open-source, parallel visualization and analysis application. In this course we provide a hands-on introduction to the ParaView interface, learn how to query the data, work on examples that use common visualization and data analysis filters, describe how to create animations, and how to save a visualization pipeline as a Python script that can be modified and run in batch mode.

Afternoon: Introduction to Computational Model Builder (CMB)

This course will introduce you to the fundamental concepts of Simulation Model ToolKit (SMTK) with examples in both C++ and Python as well as hands on experience with using the Computational Model Builder (CMB) ModelBuilder Application. These combine to manage the core resources and associated operations which are required to define a simulation. Resources include geometric models, simulation information, and meshes.
This course cover use cases from a large range of problem domains, a discussion on how CMB can be applied to your workflow and problem domains, and future enhancements to both SMTK and CMB.

To reserve a seat for the courses, please fill out this google form and we’ll get back to you to confirm you reservation.

https://forms.gle/4Lze8vXrZSyvxWVm6

Kitware at CVPR 2017

Kitware will continue their active participation and support to the computer vision community within this year’s IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). The computer vision team has had a long-term commitment to CVPR and this year will be no different. We will discuss our extensive experience in utilizing deep learning and computer vision to develop tools for image and video scene recognition, object detection and tracking, and image enhancement in talks at multiple workshops.  Domains will include aerial video, ground-level video, underwater video and satellite imagery.  Throughout CVPR 2019, the vision team will continue their high-level of participation as silver sponsors, area chair, reviewers, workshop organizers, speakers, and more. Come by our booth (#1118) to share and discuss Kitware’s computer vision and deep learning techniques supporting the open source software community. Be sure to check out the full details below so you don’t miss this great opportunity to meet with our team.

Event Details:

Kitware is a silver sponsor at this year’s CVPR.  Each year, Kitware sponsors this conference to support this community, recruit computer vision professionals, and to continue collaboration and engagement.  Anthony Hoogs, Ph.D., the Senior Director of Computer Vision, is an Area Chair providing his extensive expertise in computer vision and deep learning to ensure selection of the highest quality papers.

Learning to Explain Artificial Intelligence (AI)

Sunday, June 16 will kick-off the beginning of Kitware’s participation starting with the CVPR-19 Workshop on Explainable Artificial Intelligence (AI).  This workshop “aims to bring together researchers, engineers and industrial practitioners” to discuss relevant topics and concerns related to “interpretability, safety, and reliability of AI”.  Dr. Anthony Hoogs will present detailed information on our accepted paper “Explainability for Content-Based Image Retrieval”. This will be based on our experience performing research and development (R&D) for funded research programs focused on explaining AI. It will be a half-day event located at the Hyatt, Beacon, A; however please check the agenda to ensure no locations have changed at the start of the conference.

Monday June 17, Dr. Anthony Hoogs, the General Co-Chair and organizer of the CVPR 2019 Workshop and Challenge on Automated Analysis of Marine Video for Environmental Monitoring will begin.  This full-day workshop includes“experts and researchers interested in learning about the challenges, current work, and opportunities in marine video analytics, including video captured from both under and above water”. Monitoring fish, shellfish, marine mammals, coral reefs, bottom habitats, and other wildlife continues to be of great interest to oceanographers, biologists, and others.  Maritime video collection is expanding exponentially as professionals work to determine new ways to use this data for marine science and oceanography. The challenges in this environment are vast and many experts and researchers are diligently working to overcome these challenges to enable increased automated video processing. Currently, marine video is annotated manually, resulting in a tremendous bottleneck to studying marine biological problems such as fish population estimates. Under NOAA funding, Kitware has developed an open-source framework and toolkit, Video and Imagery Analytics for the Marine Environment (VIAME), to integrate analytics algorithms from the community into an operational capability for NOAA.

Video and Imagery Analytics for the Marine Environment (VIAME) Toolkit

This Workshop will feature a data challenge within this domain, in addition to the invited talks and selected papers.  Large amounts of image data from a variety of underwater cameras and environments has been provided and annotated by the National Oceanic and Atmospheric Administration (NOAA). Challenge entries must work towards achieving the highest detection and classification accuracy of organisms in the provided videos. Results will be scored and ranked by Kitware, and the top three entries will present their solutions at the workshop.  Check out the Challenge website for more information.

Textured 3D Mesh of Jacksonville

Kitware will also be presenting and participating in the EARTHVISION 2019 IEEE/ISPRS Workshop June 17.  The need for automated interpretation of remotely sensed data is always present to positively support human society, economy, industry, and the planet.  It is evolving and highly challenging, therefore awareness within the computer vision community needs to be raised to support and develop tools to improve data mining, multi-sensor, multi-modality, multi-temporal, and multi-resolution fusion and more. This workshop focuses on large scale computer vision for remote sensing in imagery and is a full-day event with invited talks, poster spotlights and presentations.  This year, Kitware was awarded the “Best Paper Presentation” for this workshop titled “Urban Semantic 3D Reconstruction from Multiview Satellite Imagery”.  Matt Leotta, Ph.D., a Technical Lead within Kitware’s Computer Vision team, will be presenting this research to the community; with additional Kitware attendees and authors, such as Chengjiang Long, Ph.D., a Computer Vision Researcher with Kitware.

The Workshop on Media Forensics will also be held on Monday, June 17.  This workshop will discuss topics such as media forensics, reconstruction of media genealogy, analysis and detection of imagery and videos created by new synthesis methods such as Generative Adversarial Networks (GANs) and more. Kitware’s, Dr. Chengjiang Long will  present a spotlight presentation starting at 9:30 am PST on the paper titled “A Coarse-to-fine Deep Convolutional Neural Network Framework for Frame Duplication Detection and Localization in Forged Videos”. It proposes a novel coarse-to-fine framework based on deep Convolutional Neural Networks to automatically detect and localize frame duplication.  In addition to this, keynote speakers for universities and government organizations will discuss research, challenges and real-world needs based on media forensics now. Make sure to come check out this workshop in room 102A and the others at CVPR 2019!

Finally, during the main conference and exhibition, Kitware’s computer vision team members including Anthony Hoogs, Ph.D.,  Keith Fieldhouse, Matt Leotta, Ph.D., Brian Clipp, Ph.D., Matt Dawkins, Chengjiang Long, Ph.D., Heather James, and John Westbrook will be available at booth #1118 to discuss and demonstrate Kitware’s computer vision expertise.  You will have the opportunity to see the KitWare Image and Video Exploitation and Retrieval (KWIVER) toolkit, Kitware’s open source software toolkit that contains advanced computer vision tools to perform object detection and tracking; activity, event, and threat detection; scene understanding; and social multimedia analysis.  In addition, our work on the Video and Image Analytics for a Marine Environment (VIAME) toolkit will be demonstrated as we are continuously working with NOAA to develop open source software for fish monitoring and extending that to other capabilities and needs.

About Kitware’s Computer Vision Team:

Kitware’s Computer Vision team recognizes how valuable advancing computer vision and deep learning is in order to greatly improve and push capabilities beyond their limits supporting Academia, Industry, and the DoD and Intelligence Communities.  Our main focus areas include deep learning, object detection and tracking, image and video scene understand, image and video forensics, social multimedia analysis, complex activity, event, and threat detection, 3D vision, and super resolution; however we are not limited and continuously explore and participate in other research and development for our customers and our partners.  We partner with many academic institutions such as Harvard, Massachusetts Institute of Technology, Cornell University, University of California, Berkeley, and Texas A&M University. We have worked with various agencies, such as the Defense Advanced Research Project Agency (DARPA), Air Force Research Laboratory (AFRL), the Office of Naval Research (ONR), Intelligence Advanced Research Projects Activity (IARPA) and the U.S. Air Force.  Kitware has developed and deployed an operational Wide Area Motion Imagery (WAMI) tracking systems for Intelligence, Surveillance, and Reconnaissance (ISR) in theatre, providing analysts with exploitation capabilities that fuse sensors, platforms, and people. Our work with DARPA on Squad-X has led to extensive research, development, and deployment of robust methods to more accurately identify and track objects and people, delivered straight to the soldier on the ground.  Our work on the Visual Global Intelligence and Analytics Toolkit (VIGILANT), funded by the Air Force Research Laboratory (AFRL) via the Small Business Innovation Research (SBIR) program is a collaborative effort with Rochester Institute of Technology’s (RIT’s) Digital Imaging and Remote Sensing (DIRS) and Real Time Vision and Image Processing (RTVIP) Labs and the Middlebury Institute of International Studies at Monterey, James Martin Center for Nonproliferation Studies to develop object and object-based change detection and unstructured change detection in satellite imagery. In addition, Kitware is continually improving their KitWare Image and Video Exploitation and Retrieval (KWIVER) toolkit, which is an open source framework for video and image analytics built from Kitware’s years of experience developing analytic systems for various customers in multiple domains.  Please visit our computer vision and KWIVER webpages for more information into our key focus areas and experience.

Contact:

Please reach out to computervision@kitware.com to schedule meetings throughout this event.  We are looking forward to engaging with this community and sharing information on Kitware’s ongoing research and capability development in computer vision and deep learning as well as our cutting-edge open source vision software, KWIVER and VIAME.

The United States Geospatial Intelligence Foundation (USGIF) GEOINT 2019 Symposium is just around the corner!  This is Kitware’s first year to have a booth at GEOINT and we are very excited.  Come visit us at booth #1430 to learn more about our advanced computer vision capabilities and how they translate to geospatial intelligence.

Are you interested in machine learning in satellite and marine imagery?  We are holding a training session titled “Interactive Machine Learning in Satellite and Marine Imagery”.  This training session will demonstrate interactive and machine learning (ML) by analysts based on the open-source Visual Global Intelligence and Analytics Toolkit (VIGILANT) and Video and Image Analytics for Marine Environments (VIAME) systems.  These systems allow analysts to develop ML-based object detectors without the need for any programming, all within minutes.  Check out our teaser video below and we look forward to seeing you on Monday June 3 in room 302A from 2-4 pm.

Over the years, Kitware has continuously developed exciting and forward thinking technologies that support the GEOINT community.  This is all through the use of our specialized team and computer vision and deep learning techniques.  These techniques help Kitware build advanced tools and capabilities to support intelligence operations through threat detection and more.  By adopting and harnessing deep learning techniques tied with computer vision, Kitware has demonstrated dramatic improvements in technologies.  Our focus is on hard problems such as extracting meaningful information from low resolution images and video and/or small training sets.  In addition, we scale these technologies to handle large data volumes associated with object detection and tracking, event and activity recognition, scene understanding, 3D vision, threat detection, and more.

Contact:

This year we will have members of the computer vision team attending sessions and at the booth.  Please reach out at computervision@kitware.com or 202-725-9389 to schedule meetings throughout GEOINT 2019.  We look forward to speaking with you about Kitware’s technologies, solutions, and your challenges!

NVIDIA and Kitware have teamed up to provide a free one-hour webinar on using GPU-accelerated ray tracing in ParaView and VTK to improve understanding of your scientific visualizations.

Highlights include:

• How to use OptiX Ray Tracer inside ParaView
• Leverage simulations with ParaView
• How ray tracing can provide more insights into data

Click here to register

Beatriz Paniagua, Ph.D., a technical leader on the medical team at Kitware, will join a roundtable forum to determine cross-discipline interests between the biomedical and radio astronomical imaging research communities.

More information can be found at the forum’s website.

We invite clinical researchers or technologists in biomedical imaging to attend our training course and learn from our team members about open source software platforms for medical computing:

• The Visualization Toolkit and ParaView,
• The Insight Toolkit, and
• 3D Slicer.

Come for a day, two days or all three!

For more information, including a breakdown of course topics, please see the registration form.

Register Now

Principal Engineer Matthew McCormick and Technical Leader Beatriz Paniagua will be guests on the podcast.

Kitware’s work will be featured in the following.

Monday Poster Session
February 18th, from 5:30 to 7 p.m. PST

Content based retrieval of video segments from minimally invasive surgery videos using deep convolutional video descriptors and iterative query refinement

Towards an advanced virtual ultrasound-guided renal biopsy trainer

Session 4, Brain: Shapes and Biomarkers
Tuesday, February 19th, from 3:30 to 4:50 p.m. PST

Model selection for spatiotemporal modeling of early childhood sub-cortical development

Session 9, Bone
Thursday, February 21st, from 8 a.m. to 9:40 a.m. PST

Methods for quantitative characterization of bone injury from computed-tomography images

Advanced statistical analysis to classify high dimensionality textural probability-distribution matrices

The original web page for this workshop (actev.nist.gov/workshop/hadcv19) was hosted by the National Institute for Standards and Technology (NIST), which has been closed because of the partial shutdown of the US Government. This webpage is a temporary surrogate and does not contain all of the content of the original. The workshop will happen as originally planned on Jan. 7, 2019 with the schedule as published in the hardcopy conference booklet, and also listed below.

This workshop is part of the 2019 IEEE Winter Conference on Applications of Computer Vision (WACV) at the Hilton Waikoloa Village in Hawaii, Jan. 7-11, 2019.

This workshop has an associated data challenge, the Activities in Extended Videos (ACTEV) Prize Challenge sponsored by IARPA. See details at https://actevchallenge.avidannotations.com. In a preliminary phase of the challenge, the top three submissions as of October 2018 were invited to give presentations at this workshop. The challenge continues through February 2019 with substantial prize money and the winners presenting at the ActivityNet workshop at CVPR 2019.

Workshop Program

Workshop Organizers

Terry Adams, Former IARPA PM for DIVA

Jonathan Fiscus, NIST

Afzal Godil, NIST

Anthony Hoogs, Kitware, Inc.

Reuven Meth, Engility

Contact

For information about the workshop please email hadcv@actev.live.

Staff R&D Engineer Rachel Clipp will discuss modeling and simulation work on the medical computing team to illustrate a potential career for math and applied math majors.

Technical Leader Matthew McCormick will present “itk-jupyter-widgets: Interactive 3D and 2D Image Visualization for Jupyter” from 11 to 11:25 a.m. EST.

Booth      •      Team Members      •      Hiring      •      Activities

Booth 3735

Kitware will host a booth at the exhibition from Monday, November 12th, to Thursday, November 15th. Meet ParaView, VTK and CMake developers; grab giveaways; and hear booth talks.

Booth Talks

Monday, November 12th
What’s New with Kitware & HPC: High-performance Visualization and Analysis with ParaView
7 p.m. EST • Patrick O’Leary

Tuesday, November 13th
What’s New with Kitware & HPC: High-performance Visualization and Analysis with ParaView
11 a.m. EST • Patrick O’Leary

Girder: A New Extensible System for Large Data and Analytics Management
1 p.m. • Jeff Baumes

CMake: Building Improvements, followed by an ask the experts session with CMake developers
2 p.m. • Robert Maynard

Visualization on the Web with ParaView and VTK
3 p.m. • Sébastien Jordain

Ray Tracing Comes to ParaView
4 p.m. • Dave DeMarle

Wednesday, November 14th
In Situ Analysis and Visualization (ParaView Catalyst)
11 a.m. EST • Patrick O’Leary and David Thompson

What’s New in ParaView, followed by an ask the experts session with ParaView developers
1 p.m. • Utkarsh Ayachit

Virtual Reality with VTK and ParaView
2 p.m. • Ken Martin

Creating a Web-based Simulation Environment
3 p.m. • Sébastien Jordain

Computational Model Builder (CMB)
4 p.m. • David Thompson

Booth Demos

VTK and ParaView in Virtual Reality

Team Members

• Ken Martin, distinguished engineer and co-founder
• Jeff Baumes, director of data and analytics
• Patrick O’Leary, assistant director of scientific computing
• Brad Davis, director of business development
• Utkarsh Ayachit, distinguished engineer
• Dave DeMarle, principal engineer
• Robert Maynard, principal engineer
• Sébastien Jordain, principal engineer
• David Thompson, staff R&D engineer
• Aron Helser, staff R&D engineer
• Scott Wittenburg, staff R&D engineer
• Omar Padron, senior R&D engineer
• John Westbrook, human resources generalist
• Libby Rose, business development representative

Hiring

If you are interested in working on VTK and/or ParaView as a member of our team, please let us know when you stop by our booth or see us at one of the activities in which we are involved. For more information on our jobs or work environment, please visit https://jobs.kitware.com.

Activities

Sunday, November 11th
David Thompson will present at the tutorial SENSEI Cross-Platform View of In Situ Analytics.

Monday, November 12th
Patrick O’Leary and David Thompson will attend the workshop In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (ISAV 2018). Patrick is the at-large chair and a member of the organizing committee. David is a member of the programming committee.

Tuesday, November 13th
Dave DeMarle and Utkarsh Ayachit will be part of Meet & greet ParaView developers and experts at the Department of Energy’s booth (2433) from 1 to 2 p.m. CST.

Dave DeMarle will talk about ParaView and OSPRay at Intel’s booth (3223) at 3 p.m.

Wednesday, November 14th
Dave DeMarle and Utkarsh Ayachit will be part of Meet & greet ParaView developers and experts at the Department of Energy’s booth (2433) from 5 to 6 p.m. CST.

John Westbrook will recruit at the Student/Postdoc Job Fair, which will take place from 10 a.m. to 3 p.m. Open positions include scientific visualization developer in Santa Fe, NM, and Clifton Park, NY.

Technical Leader Marcus Hanwell is involved in multiple activities.

On Thursday, November 1st, he will present “Open Chemistry and Jupyter: Platform for Data Mining and Machine Learning.” The presentation will take place from 8 to 8:15 a.m. EDT in the Data Mining and Machine Learning in Molecular Sciences II session. The session will be held in room 308 of the convention center.

Later on Thursday, from 4:55 to 5:10 p.m. EDT, he will present “Open Chemistry, Avogadro and Jupyter: User Friendly Frontends.” The presentation is part of the session Making Molecular Simulation a Mainstream Chemical Engineering Tool. It will also take place in room 308.

Technical Leader Marcus Hanwell is involved in multiple activities.

On Thursday, November 1st, he will present “Open Chemistry and Jupyter: Platform for Data Mining and Machine Learning.” The presentation will take place from 8 to 8:15 a.m. EDT in the Data Mining and Machine Learning in Molecular Sciences II session. The session will be held in room 308 of the convention center.

Later on Thursday, from 4:55 to 5:10 p.m. EDT, he will present “Open Chemistry, Avogadro and Jupyter: User Friendly Frontends.” The presentation is part of the session Making Molecular Simulation a Mainstream Chemical Engineering Tool. It will also take place in room 308.

On Thursday, October 25th, from 9 to 9:20 a.m. CDT, Technical Leader Marcus Hanwell will provide a plenary talk. He is on the conference’s organizing committee.

Technical Leader Marcus Hanwell will present “Tomviz: Open Source 3D Graphical Tool for Reproducible Tomography” from 1 to 1:25 p.m. EDT Wednesday, October 24th.