The Rutgers Artificial Intelligence and Data Science (RAD) Collaboratory
The Rutgers Artificial Intelligence and Data Science (RAD) Collaboratory
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The Rutgers Artificial Intelligence and Data Science (RAD) Collaboratory
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Past Event Resources

(listed in reverse chronological order)
April 29, 2025: Hands-on Training in Artificial Intelligence and Deep Learning
April 15, 2025: Hands-on Training in Artificial Intelligence and Deep Learning

 

April 8, 2025: RAD Collaboratory AI/Machine Learning Networking Event
  1. Single-Cell Transcriptomic Cell Type Annotation Using AI for Spinal Cord Injury Study, presented by Li Cai, Professor, Biomedical Engineering, School of Engineering
  2. New Jersey AI Hub and Rethinking Computer Science, presented by Ananda “Andy” Gunawardena, Teaching Professor, Computer Science, School of Arts and Sciences
  3. Pay Attention – Classical Statistical Models Got Interesting, presented by Sijian Wang, Professor, Statistics, School of Arts and Sciences
  4. The Last Mile in Remote Sensing Poverty Prediction, presented by Woojin Jung, Assistant Professor, School of Social Work  
  5. Robot Learning, Perception and Planning @ Rutgers CS, presented by Kostas Bekris, Professor, Computer Science, School of Arts and Sciences
  6. Evolution of Human – Chatbot Interactions, presented by Jim Samuel, Associate Professor of Practice, Informatics, E. J. Bloustein School of Planning and Public Policy
  7. Applying AI/ML methods to identify controls on the occurrence and organization of precipitating deep convection and extreme rainfall in the tropics, presented by Benjamin Lintner, Professor, Environmental Sciences, School of Environmental and Biological Sciences
  8. Machine Learning Approaches to Climate Data Bias Correction and Downscaling, presented by Lili Xia, Assistant Research Professor, Environmental Sciences, School of Environmental and Biological Sciences and Zhao Zhang, Assistant Professor, Electrical and Computer Engineering, School of Engineering
  9. Responsible AI for Health and Wellness, presented by Vivek Singh, Associate Professor, Library and Information Science, School of Communication and Information
  10. A Machine Learning Approach to Predicting In-Hospital Mortality Following Traumatic Injury: Model Development and Validation, presented by Hajer Ali, Graduate student, Biomedical Engineering, School of Engineering
  11. Deep learning from deep mutagenesis: data-driven computational design of protein binding and catalytic selectivity, presented by Sagar Khare, Professor, Institute for Quantitative Biomedicine, School of Arts and Sciences
  12. The Role of AI and ML in Precision Medicine: A Case Study of Brittle Bone Disease, presented by Emma Larson, Graduate student, Chemistry and Health Informatics, School of Health Professions
  13. IntelliGenes: AI/ML pipeline for biomarker discovery and predictive analysis, presented by Zeeshan Ahmed, Assistant Professor, Institute for Health, Health Care Policy and Aging Research, Robert Wood Johnson Medical School
  14. Interactive, personalized summarization of cancer diagnostics data using large language models, presented by Subhajyoti De, Associate Professor, Systems Biology, Rutgers Cancer Institute
  15. Intersection of the RCSB Protein Data Bank with Artificial Intelligence/Machine Learning, presented by Stephen Burley, Director, RCSB Protein Data Bank, Institute for Quantitative Biomedicine
  16. Advancing AI tools for drug discovery and enzyme design, presented by Darrin York, Distinguished Professor, Chemistry and Chemical Biology, Institute for Quantitative Biomedicine, School of Arts and Sciences
  17. Objective Metrics for AI Assurance, presented by Lazaros Gallos, Research Professor, Center for Discrete Mathematics and Theoretical Computer Science (DIMACS), School of Arts and Sciences
  18. Deep Learning for Automated Classification of Corrosion Failures in Potable Water Infrastructure, presented by Siddhartha Roy, Assistant Professor, Environmental Sciences, School of Environmental and Biological Sciences
  19. AI/ML-driven Annotation for Cellular Imaging, presented by Wei Dai, Associate Professor, Cell Biology and Neuroscience, Institute for Quantitative Biomedicine, School of Arts and Sciences
  20. Fundamental Physics: An Unparalleled Sandbox for AI and Modern Machine Learning, presented by David Shih, Professor, Physics and Astronomy, School of Arts and Sciences
  21. From the bottom up: Predicting 2D quantum materials to twist and stack, presented by Jed Pixley, Associate Professor, Physics and Astronomy, School of Arts and Sciences
  22. Improved Explainability and Robustness of Foundation Models: Principled Methodology to Incorporate Domain Knowledge, presented by Dimitris Metaxas, Board of Governors Professor, Computer Science, School of Arts and Sciences
  23. OSC/RAD summer course: Basic Statistical Analysis Methods for Biomedical Researchers, presented by Minge Xie, Distinguished Professor, Statistics, School of Arts and Sciences
  24. OARC Resources for Researchers in Today’s Digital Age, presented by Travis Williams, Senior Scientist, Office of Advanced Research Computing (OARC)
  25. New Jersey Big Data Alliance (NJBDA) & Journal of Big Data and Artificial Intelligence (JBDAI), presented by Jim Samuel, Associate Professor of Practice, Informatics, E. J. Bloustein School of Planning and Public Policy
March 14, 2025: New Jersey Big Data Alliance’s Research Collaboration Forum

 

March 5, 2025: RAD Collaboratory Data Science Networking Event
  1. CASS: Cyberinfrastructure and AI for Science and Society, presented by Alyson Brooks, Associate Professor, Physics and Astronomy, School of Arts and Sciences   
  2. Ensuring security and privacy of large-scale datasets: a synthetic data perspective, presented by Jaideep Vaidya, Distinguished Professor, Management Science and Information Systems, Rutgers Business School and Director, Rutgers Institute for Data Science, Learning, and Applications
  3. Solar Climate Intervention, presented by Lili Xia, Assistant Research Professor, Environmental Sciences, School of Environmental and Biological Sciences
  4. Remote Sensing of Turfgrass, presented by Juan Gonzalez, Postdoctoral Research Associate, Plant Biology, School of Environmental and Biological Sciences
  5. Rutgers University Center for Ocean Observing Leadership (RU-COOL) 30 Years of Coastal Ocean Data, presented by Hugh Roarty, Director of CODAR, Marine and Coastal Sciences, School of Environmental and Biological Sciences
  6. RU-COOL Autonomous Underwater Gliders, presented by Joe Gradone, Postdoctoral Research Associate, Marine and Coastal Sciences, School of Environmental and Biological Sciences
  7. Sign Language Data Science Applications, presented by Dimitris Metaxas, Board of Governors Professor, Computer Science, School of Arts and Sciences
  8. Socially Cognizant Robotics for a Technology Enhanced Society (SOCRATES), presented by Kristin Dana, Professor, Electrical and Computer Engineering and Director, SOCRATES, School of Engineering
  9. RCSB Protein Data Bank, presented by Stephen K. Burley, University Professor and Henry Rutgers Chair, Chemistry and Chemical Biology, School of Arts and Sciences
  10. Medical Imaging Data Science Applications, presented by Dimitris Metaxas, Board of Governors Professor, Computer Science, School of Arts and Sciences
  11. Peptide Screening Using in vivo Phage Display for the Development of Targeted Therapies, presented by Alex Ille, Postdoctoral Research Associate, Joint Laboratory of Renata Pasqualini and Wadih Arap, Rutgers Cancer Institute – Newark
  12. Closing the Gap in the Precision Medicine Model: Digital Behavioral Data Under a New Unifying Statistical Platform, presented by Elizabeth B. Torres, Professor, Psychology, School of Arts and Sciences
  13. Advancing patient-centered research using meta-analysis of individual patient data to study comparative effectiveness in comorbid PTSD and substance use disorder treatment outcomes, presented by Denise Hien, Senior Vice Provost for Research and Helen E. Chaney Endowed Chair in Alcohol Studies and Distinguished Professor, Graduate School of Applied and Professional Psychology
  14. Best Practices for Archiving Large Video Datasets, presented by Dimitris Metaxas, Board of Governors Professor, Computer Science, School of Arts and Sciences
  15. PDBx/mmCIF Data Standard: Foundation for FAIR Data Access in the Protein Data Bank, presented by Brinda Vallat, Associate Research Professor, Institute for Quantitative Biomedicine, School of Arts and Sciences
  16. Rutgers Cyberinfrastructure Resources at the Office of Advanced Research Computing, presented by Udi Zelzion, Senior Scientist, Office of Advanced Research Computing
  17. Rutgers Cyberinfrastructure Resources at the Office of Information Technology, presented by Andy Page, Infrastructure Architect, Office of Information Technology
  18. Rutgers University Libraries Support for Data Science, presented by Ryan Womack, Data Librarian, Rutgers University Libraries
  19. Data Science Education: Undergraduate Major, SEED2S, and MS Program, presented by Thu Nguyen, Dean of Mathematical and Physical Sciences, Professor of Computer Science, School of Arts and Sciences
  20. Designing and Scaling a Senior-Level Data Science Course CS 439 for Computer Science Majors: Managing High Enrollment and Demand, presented by Ananda “Andy” Gunawardena, Teaching Professor, Computer Science, School of Arts and Sciences

 

February 18, 2025: Hands-on Training in Artificial Intelligence and Deep Learning

 

February 9, 2025: Rutgers American Medical Student Association’s (AMSA) 17th Annual Pre-Health Conference on “The Future of Medicine”

 

January 22, 2025: RAD Collaboratory Inaugural Networking Event
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