AI Application Highlight from NVIDIA GTC 2020

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AI Application Highlight from NVIDIA GTC 2020
Alex G. Lee1
Healthcare
Therapeutics
1. AI in Medical Diagnosis by Vignesh Krishnaraja, Data Scientist, Blue Eye Soft Corp
AI powered clinical decision support tool that uses deep learning algorithms to diagnose COVID-19 on chest x-
rays with limited COVID-19 data and a high degree of accuracy.

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Alex G. Lee, Ph.D Esq., is a principal consultant at TechIPm, LLC.

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2. An AI-Augmented Platform for Diagnosing High-Risk Vascular Diseases by Ajith Kumar , CEO, VasoGnosis
AI-augmented platform that uses deep learning algorithms to diagnose high-risk vascular diseases (i.e. brain
aneurysms). Class Activation Map technique with Global Average Pooling CNN layer is used to utilize image level
labels for discriminative learning.
3. AI-Based Prediction in Bone Diseases by Ranjan Challa Shridhara, Marketing Specialist, ImageBiopsy Lab

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AI powered clinical decision support tool for bone diseases diagnoses that uses AI to better predict osteoarthritis
(OA), the most common joint disease worldwide, by measuring the joint space width in a more standardized way.
The software also assesses the severity of OA and the overall health of the bone in a standardized and objective
manner. This enables more precisely targeted therapies, cost reduction, and better quality of life for patients.
4. AI for Precision Radiotherapy by Jen-Tang LU, CEO, Vysioneer
A clinician-centered deep learning-based system for automated tumor segmentation and further deploys the system
into clinical workflow to facilitate tumor contouring of radiotherapy.

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Drug Discovery
1. AI and Simulation to Predict Treatment Efficacy for Parkinson’s Disease by Andy Lee, Co-founder & CTO,
NeuroInitiative

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AI based simulation engine and system for loading biological models to simulate human cells for the validation of
targets for Parkinson's disease. Drug discovery tool for predicting effective therapeutics for neurodegenerative
diseases.
2. Accelerating Rare Disease Treatments with AI by Daniel O'Donovan, Machine Learning - Technical Lead, healx
The world’s most efficient AI platform that makes drug discovery faster, smarter and safer, and supports in
discovering and translating new treatments towards the clinic our team for rare disease treatments. Machine
Learning applied to Knowledge Extraction and Reasoning gives super powers to our expert pharmacologists.

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3. Utilizing AI and Physics for SARS-CoV2 Drug Design and Discovery by Rick Stevens, Associate Laboratory
Director - Computing, Environment and Life Sciences, Argonne National Laboratory
An open source deep learning tools and conventional physics-based simulations that can accelerate timely response
for treating pandemics. The outputs from its physics-based models are used iteratively to improve the prediction
capabilities of deep learning approaches to improve the overall yield of drug candidates that can be refined further

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using biochemical and biological assays.
4. AI-Driven Generation of Molecular Structures Optimized for Drug Discovery by Stratos Davlos, CTO ,
Innoplexus
A deep learning generative model and pipeline to leverage the existing molecular and biological data for training,
generation, and cross-validated using scientific literature to accelerate molecule discovery for developing a new
drug.

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Precision Medicine/Genomics
Accelerating Whole Genome Analysis, Tim Harkins, Product Manager, NVIDIA
Genomic data is foundational in making precision medicine a reality. As next generation sequencing becomes more
routine, large genomic datasets are becoming more prevalent. Being able to transform the sequencing data into

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genetic information is just the first step in a complicated, data intensive workflow. By accelerating multiple variant
callers for both germline and somatic mutations, the strengths of one caller can be used to address the weakness of
another. Using the combination of outputs from multiple callers, the multiple consensus callers can be created from
simple parliament voting to more sophisticated machine learning-based approaches. By generating a high
confidence and comprehensive variant catalog, annotation filters and tertiary analysis can be applied to help
identify important variants in downstream applications.

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Public Health
Automated AI-Powered Social Distancing and Mask Detection, by Rakshit Agrawal, Applied Scientist, Camio
Real-time alert system for wearing face mask and keeping social distancing that uses security cameras to track and
monitor people moving on a 3D floor-plane grid that defines the areas inside and outside of each entrance.

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Mobility/Autonomous Vehicle
1. 5G-enabled Vision-based Autonomous Navigation by Mohamed Elhabiby, Executive Vice President, Micro
Engineering Tech, Inc.
A 5G-ready, vision-based navigation solution for the improvement of autonomous vehicles that uses multi-sensor
integration for a submeter level positioning accuracy.
2. Building Blocks of a Modern Vision Pipeline Enabling Optimized Traffic Management by Daniel Zelyanski,
Computer Vision & Imaging Team Leader, NoTraffic

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A real-time vision system that uses multiple CNNs and a radar to obtain robust vehicle detection and tracking.

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Cybersecurity
1. Accelerating Cybersecurity Log Pipelines and Analytics for Rapid Correlation by Bartley Richardson, Senior
Cybersecurity Data Scientist, NVIDIA
GPU-based ML techniques for rapid correlation and enrichment using raw data that can be quickly parsed and
enhanced with threat intelligence feeds for end-to-end infrastructure cybersecurity workflows.

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2. Trojan Detection Evaluation by Michael Majurski, Computer Scientist, NIST
Neural networks are trained on data, learn relationships in that data, and deployed to operate on new data. A
potential problem is that an adversary can disrupt the training pipeline to insert Trojan behaviors. To combat such
Trojan attacks reference datasets and operating a challenge where detection methods can be evaluated against
sequestered data are developed. Submissions, packaged into Singularity containers, are run against the sequestered
data and results are posted to a public leaderboard.

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Finance
1. AI for Quantitative Multi-Asset Research and Investment by Suresh Bavisetti, Founder, AsknBid Tech
Accessible and affordable enterprise grade deep learning-based algorithmic trading system.
2. Anomaly and Outlier Detection for Fraud Prevention Based on Customer Profiles Using GPU Acceleration by
Bharath Shasthri, Head of Data Science, HDFC bank
Fraud Prevention solution that is based on customer profiles and uses GPU acceleration exploiting the anomaly and
outlier detection algorithm. The system builds feature engineering workflows to detect outliers in features like age,

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income, and credit history using the binning and bucketing technique, which was implemented using NVIDIA
RAPIDS and the NVIDIA DGX platform.

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Telecommunications
1. Machine Learning in Beyond-5G Mobile Communications by Charles Clancy, Senior Vice President, MITRE
The Open Radio Access Network (O-RAN) Alliance is standardizing radio resource automation subsystems that
specifically leverage ML as part of the system design. ML can revolutionize both waveform design and
implementation, and can be used for orchestrating real-time core network resources to satisfy the quality-of-service
demands of new use cases.

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2. Leveraging Deep Learning on the Edge to Enhance 5G Radio Access Network L1 Performance
SESSION ENDED by Tim O'Shea, CTO, DeepSig
A deep learning-enhanced 5G physical layer technologies to reduce cost and power consumption while improving
quality of experience and multi-user capacity, as well as enhancing interoperability and fault detection in shared
and unlicensed spectrum deployments.

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3. Edge AI meets 5G by Kuntal Chowdhury, Senior Vice President, Product Management & Systems Engineering,
Mavenir & Ash Bhalgat, Senior Director, Cloud & Telco Market Development, NVIDIA
The nexus of 5G, IoT, and MEC is expanding the horizons of digital transformation. NVIDIA EGX platform
captures the video streams coming from 5G connected cameras and the accelerated and efficient Edge AI solution
processes the video data for analysis (e.g., detect cars).

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Conversational AI/Chatbot
1. A Chatbot Platform That Everyone Can Use by Wenxi Chen, AI Software Engineer, Juji, Inc.
Chatbot Q&A solution leveraging state-of-the-art hardware and software to create a chatbot platform that everyone
can use. Powerful GPUs enable them to quickly train deep learning models for different customer service settings
and iteratively update them.

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2. Automated Interviews Using Realistic AI Face Generation, Karthik Balu, CEO/Founder, Clofus Innovations
Private Limited
Automated Interviewer solution that uses multiple deep learning models and realistic AI face generation.

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Supply Chain/Logistics
Augmented Supply Chain Logistics Using Deep Learning by Francois Noel, AI product manager, Nuvoola inc.
AI platform that are integrated for the supply chain, logistics, and transportation industries.

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Agriculture
Building Farming Robots to Feed the World by Marie Schiltz, Lead Computer Vision Engineer, FarmWise
AI robot that can distinguishes vegetable crops from harmful weeds, using computer vision, and removes weeds
with mechanical tools down to one centimeter of precision.

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AI Application Highlight from NVIDIA GTC 2020

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AI Application Highlight from NVIDIA GTC 2020