CARTA IAB Meeting Spring 2022 – Agenda

Agenda:

 

12:00 – 12:20 pm – Welcome & Meeting Overview

  • Welcome – Prof. Dimitris Metaxas, Center Director

  • State of CARTA – Prof. Dimitris Metaxas, Center Director

12:20 – 12:30 pm – NSF Overview-Ann Chrstine Von Lehmen

12:30 – 12:40 pm – New CARTA Site – Arizona State University

12:40 – 1:45 pm – New Proposals 

        At the of each presentation the CARTA Industry Members insert their comments

  • Collaborative Projects (6 minutes each):

    • Project 1: Ethical and Secure Medical Analytics, PIs: Drs. Karuna Joshi (UMBC), David Chapman (UMiami), Dimitris Metaxas (Rutgers)

    • Project 2: A Data Driven Deep learning OSSE,  PIs Dr. Milt Halem (UMBC), Dr. Ben Kirtman (UMiami)

    • Project 3: Histopathology Analytics, PIs: Mitsunori Ogihara, Dimitris Mexatas, Yelena Yesha (UMiami)

  • UMBC – Status by UMBC Site Director, Prof. Karuna Joshi (5 minutes each)

    • Searchable Malware Tensors, (PI) Dr. Charles Nicholas

    • Veracity Measure to Manage Disinformation Propagation, (PI) Dr. Karuna Joshi

    • Trusted data model in edge computing environment using permissioned blockchain, (PI) Dr. Yaacov Yesha

    • Using dynamic neural networks for an effective dynamic firewall, (PI) Dr. Yaacov Yesha

  • NC State – Status by NCSU Site Director, Prof. Rada Chirkova (5 minutes each)

    • Learning from Mistakes: Real-time On-board CNN Training for Autonomous Driving, Prof. Frank Mueller

    • Privacy-preserving Behavioral Analysis of IoT devices on Network Edge, Dr. Anupam Das

    • Performance Analysis from Edges to Cloud, Prof. Xu Liu

    • Forecasting Anomalous Atlantic Hurricane Seasons Using Explainable AI, Dr. Lian Xie

    • Realtime Position, Navigation and Timing with AI Support, Prof. Khaled Harfoush

  • University of Miami – Status by Miami Site Director, Prof. Mitsunori Ogihara (5 minutes each)

    • Comprehensive Testbed for Clinical Flow – PI: Dr. Yelena Yesha, Dr. Mitsunori Ogihara

1:45 – 1:50 pm – Break

1:50 – 2:30 pm – Ongoing Projects: Lightning Updates (40min) 

Each project will have 2 minutes for a student researcher to present key highlights of their existing project, specifically 1) the most important methodological problem the project seeks to address; and 2) the most important thing that has been learned about that problem. 

  • UMBC 

    • (Ongoing) Automatic Legal Document Analytics and Blockchain Smart Contracts, Dr. Karuna Joshi (PI), Dae-young Leroy Kim (Student)

    • (Ongoing) Blockchain for Supply Chain Asset Management and Data Security, Prof. Yaacov Yesha (PI), Yusen Wu, Lawrence Sebald (Students)

    • (Ongoing) Towards The Classification PA Chest Radiographs as Normal or Abnormal, Prof. David Chapman (PI), Sumeet Menon (Student)

  • Rutgers

    • (Ongoing Project) Cardiac Analytics: Dyssynchrony and CRT Outcomes – Meng Ye, Qi Chang

    • (Ongoing Project) Prediction of Liver Fibrosis Score, Progression and Clinical Deterioration using Multi-Modality Data – Anaya

    • (Ongoing Project) Predicting Prognostic Factors and Outcomes of COVID-19 Patients using Machine Learning Methods – Anaya

    • Exploiting Unlabeled Data with Vision and Language Models for Object Detection – Shiyu Zhao

  • NC State

    • (Active project) Fingerprinting IoT Devices at Real Time using Encrypted Traffic, Dr. Anupam Das

    • (Active project) Resource Protection in Cloud Data Centers Through Multi-Point Traffic Shaping, Dr. Muhammad Shahzad

  • University of Miami

    • Music-induced Brain Activities – Combining Naturalistic Music Listening, Neuroelectric Recordings, and Machine Learning for Conscious – PIs: Dr. Andrew Dykstra, Dr. Mitsunori Ogihara

    • Trends and patterns of Benzodiazepines: an overdose risk prediction model – PIs: Dr. Yelena Yesha, Dr. Smriti Prathapan

    • Genotype-aware Consumer Product Recommendation – PI: Dr. Vanessa Aguiar-Pulido

    • Cyber-Physical Security Analytics – PI: Steve Dinnis

2:30 – 2:35 pm – Break

2:35 – 3:10 pm – Research to Application: Final Reports – Take Home Points (5 minutes)

  • (Ending) Taking the Thunder Out of Zeus, Dr. Charles Nicholas (PI), Maksim Eren (Student)

  • (Ending) Multi-Domain Attack Detection for Cybersecurity, Prof. Yaacov Yesha (PI), Sarang Patil (Student)

  • (Ending) Evaluating and Eliminating Bias in AI for Medical Imaging, Prof. David Chapman (PI), Sourajit Saha, Nishanjan Ravin (Students) 

  • (Ending) Progressive Neural Nets for Emulator Training of Climate Model Sub-grid Scale Physics Parametrization, Prof. Milt Halem (PI), Qingyuan Zheng (Student)

  • (Completed Project) Real-time Monitoring the Evolution of the Web, Dr. Alexandros Kapravelos

3:10 – 3:15 pm – Break

3:15 – 4:00 pm – Wicked Problems Panel – Industry Members 

4:00 – 4:10 pm – NSF Survey Completion: IAB Reps, Faculty, and Students

4:10 – 4:40 pm – Guest Speaker: Mu Zhou

Title: Towards AI-driven Pathological Integration: Feature extraction, Outcome Prediction, and Annotation Efficiency


Abstract:

The rapid development of deep learning has made remarkable progress in healthcare applications. Yet we continue to face a plethora of medical data challenges from data scale, annotation cost, and outcome predictions. To advance clinical decision making, in this talk, I will highlight the recent surge of pathology-based AI analytics for predicting multiple cancer molecular outcomes. First, I will share our research progress on graph-based deep learning classifiers to predict genetic mutations in cancer. Second, I will present recent deep-learning works on linking whole slide images and important mutational outcomes in cancer and its validations across cancer types. We provide an image-to-genomics pipeline to allow a head-to-head comparison between mutations and biological pathway signals by leveraging public cohorts. Finally, ongoing data annotation challenges, limitations, and emerging industrial opportunities will be discussed in related areas. 


Brief bio:

Dr. Mu Zhou is broadly interested in machine learning, medical image analysis, and bioinformatics. Dr. Zhou serves as head for AI drug discovery at SenseBrain. He also holds a visiting professor position at Rutgers University, New Jersey. His research focuses on data-centered approaches to analyze and process quantitative information from multi-scale biomedical data across radiology, histopathology, and omics profiles in oncology. He was a research scientist and a postdoctoral fellow at medical school, Stanford University. In collaboration with his colleagues, he led the research for linking cancer imaging and high-throughput RNA expression in lung cancer. He received his Ph.D. degree in computer science and engineering from University of South Florida, Tampa, where he pioneered image-based analysis for non-invasive outcome prediction of cancer patients.


4:40 – 5:10 pm – Closed IAB meeting

5:10 – 5:20 pm – Closing Remarks & Adjournment


1 thought on “CARTA IAB Meeting Spring 2022 – Agenda

  1. Pingback: CARTA Spring 2022 IAB Meeting – CARTA

Comments are closed.