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2021 Ken Kennedy AI and Data Science Conference
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2021 Ken Kennedy AI and Data Science Conference
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#1
Scalable Deep Learning for Large Scale Scientific Machine Learning: Challenges and Opportunities
#2
Integrated Data - Driving the Future of NASA Missions and Technology
#3
How Do We Know if Data Science is "For Good"?
#4
Discovery and Action Through Geospatial Visualization and Urban Analytics
#5
Opening: Intro to Morning
#6
What Do We Mean by “AI Ethics”?: Conceptual Tools and Examples for a Common Future
#7
Deep Learning-Based Blood Glucose Predictors In Type 1 Diabetes
#8
Automatic Machine Learning with AutoGluon - Algorithms, Domains, Applications - Auditorium
#9
How to Teach AI Multiple Languages?
#10
Welcome: Intro to Afternoon
#11
Random-Walk Based Graph Representation Learning Revisited
#12
Explainable Deep Learning Approaches to Predict Development of Brain Metastases in Patients with Lung Cancer Using Electronic Health Records
#13
Scalable and Sustainable AI Acceleration for Everyone: Hashing Algorithms Train Billion-parameter AI Models on a Commodity CPU faster than Hardware Accelerators - Auditorium
#14
Multi-Task Deep Learning Framework for Sales Forecasting and Product Recommendation
#15
Multi-Task Learning for Demand Prediction Through a Hyper-Network
#16
ML for Energy Transition
#17
ShiftAddNet: A Hardware-Inspired Deep Network
#18
Neural Architecture Search for Inversion
#19
Democratizing Deep Learning with Commodity Hardware: How to Train Large Deep Learning Models on CPU Efficiently with Sparsity - Auditorium
#20
How to Deal with Volume and Velocity Associated with Hundreds of Terabytes (and Beyond) of Genomics Data? - Room 280
#21
Break
#22
Lunch + Virtual Booths
#23
Break
#24
Closing Remarks
#25
Emu: Species-Level Microbial Community Profiling for Full-Length Nanopore 16S Reads
#26
Co-Manifold Learning
#27
Using Visual Feature Space as a Pivot Across Languages
#28
Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints
#29
Generalized Zero-Shot Learning via Normalizing Flows
#30
Parallel RRT Algorithm for Robotic Motion Planning
#31
Posters and Networking - Exhibit Hall
#32
Data4Good & Responsible AI-Automated Data Collection: How Do You Ensure Data4good?
#33
Opening: Pre-Recorded Poster Presentations
#34
Opening: Pre-Recorded Sponsor Presentations
#35
Break
#36
Break
#37
MLPrE – A Tool for Preprocessing Data and Conducting Exploratory Data Analysis Prior to Machine Learning Model Construction
#38
Diabetes Management in Underserved Communities: Data-Driven Insights from Continuous Glucose Monitoring
#39
Closing Remarks
#40
Outdoor Networking Reception with Sponsors
#41
Conference Registration, Breakfast, Networking
#42
Welcome
#43
Lunch + Networking
#44
Afternoon Break and Networking
#45
SeqScreen: Accurate and Sensitive Functional Screening of Pathogenic Sequences via Ensemble Learning - Auditorium
#46
MaGNET: Uniform Sampling from Deep Generative Network Manifolds without Retraining - Auditorium
#47
Magnified Convolutional Enrichment Representation Model - Auditorium
#48
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication - Auditorium
#49
Quantification of Myxococcus Xanthus Aggregation and Rippling Behaviors: Deep-Learning Transformation of Phase-Contrast into Fluorescence Microscopy Images - Auditorium
#50
Opening: Pre-Recorded Poster Presentations
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Recently Active Attendees
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Zhenzhen Zhong
NS
Nishant Satpathy