TechConnect World 2020
Co-Located with Nanotech 2020Co-Located with Nanotech 2020 SBIR/STTRSBIR/STTR AI TechConnectAI TechConnect
Nanotech 2020
 
 

AI for Biomaterials and Drug Design

AI Biomaterials and Drug Design

Call for Abstract - due April 10 »

Symposium Co-Chairs

Payel DasPayel Das
IBM Thomas J Watson Research Center

Sarah TaoSarah Tao
Technology Lead
Sanofi

Key Speakers

Philip M. KimMachine learning methods for the de-novo design of proteins and antibodies
Philip M. Kim
Professor, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto

Debora S. MarksDebora S. Marks
Associate Professor
Harvard Medical School

Connor ColeyChemical Discovery and AI-Assisted Chemical Synthesis
Connor Coley
Assistant Professor of Chemical Engineering, Massachusetts Institute of Technology

Glenn ButterfossCombining machine learning with other computational methods for drug design
Glenn Butterfoss
Senior Computational Biologist, ProteinQure

Advances in computational power coupled with big data analysis and innovations in machine learning, modeling and simulation approaches are enabling artificial intelligence to revolutionize the biomaterials and drug discovery and development process.

Submit your abstract and join researchers from around the world as we highlight the latest developments in this area.

 
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Symposium Sessions

Tuesday June 30

8:30AI and Machine Learning Fireside Chat
1:30AI for Biomaterials and Drug Design

Wednesday July 1

10:30Innovations for Next-gen AI
1:30Machine Learning for Medical Diagnostics
4:00Biomaterials - Posters
4:00Innovations in AI - Posters
4:00AI for Advanced Manufacturing - Posters

Symposium Program

Tuesday June 30

8:30AI and Machine Learning Fireside Chat
Session chair: Brent M. Segal, Lockheed Martin, US
1:30AI for Biomaterials and Drug Design
Session chair: Payel Das, IBM. Thomas J. Watson Research Center, US, Sarah Tao, Sanofi, US
Chemical Discovery and AI-Assisted Chemical Synthesis
C. Coley, Massachusetts Institute of Technology, US
Combining machine learning with other computational methods for drug design
G. Butterfoss, ProteinQure, CA
TBA
D. Marks, Harvard University Medical School, US
Machine learning methods for the de-novo design of proteins and antibodies
P. Kim, University of Toronto, CA
Accelerating Drug Discovery With Outcome-based Data Science and AI Application
L. Subramanian, S. Schweizer, 3DS, US
Explainable Deep Models for Compound-Protein Binding Affinity Prediction and Deep Generative Models for Protein Design
Y. Shen, Texas A&M University, US

Wednesday July 1

10:30Innovations for Next-gen AI
TBA
C. Milroy, NVIDIA, US
TBA
P. Das, IBM Thomas J Watson Research Center, US
How Can the DoD Leverage Big Data, AI and Machine Learning to Accelerate UxS Integration and Decision Making
G. Galdorisi, Naval Information Warfare Center Pacific, US
In-Storage Distributed Machine Learning for the Edge
V. Alves, NGD Systems, Inc., US
Graph-Centric Machine Learning: Algorithms, Systems, and Cybersecurity Applications
H. Huang, George Washington University, US
A Study of Famous CNN Architectures to Have Descent Base Models
M. Bari, T-Mobile, US
Concept for a Natural Language Processing (NLP) Application: Artificial Intelligence (AI) Technology for Text and Language Search (ATTLS)
M. Niv, N. Kumar, E. Henry, T&T Consulting Services, Inc, US
1:30Machine Learning for Medical Diagnostics
Session chair: Prakash D. Nallathamby, Notre Dame University, Eric Gale, Harvard Medical School
Point-of-care serodiagnostic test using a multiplexed paper-based immunoassay and machine learning
Z. Ballard, University of California, Los Angeles, US
Machine Learning for Automated Hepatic Fat Quantification
H. Sagreiya, A. Akhbardeh, University of Pennsylvania, US
An Unsupervised Approach for Treatment Effectiveness Monitoring Using Curvature Learning
A. Akhbardeh, H. Sagreiya, Stanford University, US
Novel respiratory monitoring using ultrasound signaling
G. Bilen-Rosas, I. Ong, H. Rosas, University of Wisconsin School of Medicine and Public Health Madison, US
Microbubbling Digital Assay
P. Wang, University of Pennsylvania, US
AI Platform for DNA Diagnostics, Therapeutics & Ancestry
R. Peterson, J. Kahn, DNA Analtytics, US
Kidney Cancer Staging using Deep Learning Neural Network
N. Hadjiyski, Ann Arbor Pioneer High School, US
4:00Biomaterials - Posters
Bioinpired virus nanofiber for soft tissue engineering
S.Y. Yoo, Pusan National University, KR
Nanoparticles of hydroxide and magnesium oxide: formation of PLGA nanocomposite and possible biomedical application
G.J. Colmenares Roldán, M. Londoño, S. Mesa, F. Jaramillo, I.C. Ortiz, L.M. Hoyos Palacio, Funadación Universirtaria CEIPA/Universidad Pontificia Bolivariana, CO
Microwave-assisted synthesis of hydroxyapatite nanoparticles (HA) for production of bioabsorbable nanocomposites of PLGA-HA
G.J. Colmenares Roldán, I.C. Ortiz, L.M. Hoyos Palacio, Funadación Universirtaria CEIPA/Universidad Pontificia Bolivariana, CO
Physicochemical characterization of collagen films integrating PLGA nanocapsules, fabricated via electrospinning
L.M. Agudelo Gómez, J.A. Carlos Cornelio, L.M. Hoyos Palacio, G.J. Colmenares Roldán, Funadación Universirtaria CEIPA/Universidad Pontificia Bolivariana, CO
Electrode Modifications Using Surfactant/Myoglobin Films for Electrocatalysis of Bisulfite Reduction
A. Mohamed, Beni-Suef University, EG
Potentiometric Investigation on Complexation Equiibria and Stabilities of Divalent Metal Ion Complexes of L-Cysteine and Glycine in Aqueous Solutions
A.M. Radalla, Beni-Suef University, EG
Ternary Complex Systems of The Divalent Metal Ions, Ca(II) and Zn(II), with L-Cysteine and Diphenylamine as Ligands in Aqueous Media
A. Mohamed, Beni-Suef University, EG
4:00Innovations in AI - Posters
An EHR using AI technology as a Clinical Decision Support Tool
J.M. Penn, Guidance Founation Inc., US
Autonomous Conceptualization and Design by DABUS
S. Thaler, Imagination Engines, Inc., US
IoT + DDoS = Disruptive (Business + Cyber) Risk!
A. Pabrai, ecfirst, US
Improve Health Outcomes and Maximize Quality Improvement: Using Artificial Intelligence Models
S. Kapoor, HealthEC, US
A Review of AI Influence in Intellectual Property Law
D. Mottley, Howard University, School of Law, US
ABSCA - Boost Converter Switching Controller using Machine Learning Algorithms
B. Abegaz, Loyola University of Chicago, US
AROSV - An ROS based Self-Driving Vehicle Controller using Unsupervised Machine Learning Methods
B. Abegaz, Loyola University of Chicago, US
Dropping 500 Feet in 20 Seconds: Simulating the Cockpit Experience of an Airliner with a Trim Control Failure
A. Redei, Central Michigan University, US
Artificial Intelligence Trends Based on the Patents Granted by the United States Patent and Trademark Office
H.H.N. Abadi, M. Pecht, University of Maryland - Center for Advanced Life Cycle Engineering (CALCE), US
A Survey of Artificial Intelligence Funding in China
Z. He, W. Diao, M.G. Pecht, University of Maryland, US
Next Generation PCIe Network Fabric for High Performance AI Computing
C. Reynolds, Technical Systems Integrators, US
AI - Lack of data characterization significantly reduces accuracy of AI results
M. Gilger, Modus Operandi, US
4:00AI for Advanced Manufacturing - Posters
Residual Distortion Prediction through an Artificial Intelligence Approach in Additive Manufactured Components
A. Imanian, TDA, US
Bayesian Networks Connecting Processing and Product Features in Additive Manufacturing
A. Malmberg, K. Chandra, A. Peterson, J. Mead, University of Massachusetts Lowell, US
Using Robotics to Assemble Graphene Supercapacitor
C. Wu, J. Kim, D. Magluyan, D.K. Kindred, Y. Zhou, N. Cao, H. Zhao, Z. Kuang, T. Kidd, S. Dobbs, Z. Yu, California State Polytechnic University, Pomona, US

Call for Abstract - due April 10 »

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