Podcast
Build Data Science Programs, Democratize HPC & Scale Graph Analytics with Arkouda
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Build Data Science Programs, Democratize HPC & Scale Graph Analytics with Arkouda
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Episode Overview
How do you build effective data science programs, democratize high-performance computing, and scale graph analytics so researchers and practitioners can solve real-world problems? In this episode, David Bader — Director of the Institute for Data Science at NJIT, founder of NJIT’s Department of Data Science, and a distinguished professor with deep expertise in HPC, big data, and analytics — walks through his career, leadership in launching academic units, and practical lessons for curriculum design and regional.
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Chapter Summary
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- 0:00 - Podcast Introduction
- 1:47 - Guest Intro: David Bader — NJIT Institute for Data Science, research focus
- 3:20 - Career Journey & Academic Appointments
- 4:53 - Daily Responsibilities: Research, Teaching, and Institute Leadership
- 6:11 - Active Projects & Industry Partnerships (NSF, Accenture, NVIDIA)
- 8:30 - Launching Academic Units: Starting Departments and Degree Programs
- 9:01 - Designing Data Science Curricula & Regional Workforce Alignment
- 13:55 - Academic Ranks: Assistant, Associate, Full, and Distinguished Professor
- 17:41 - Career Pathways: PhD, Postdoc, and Faculty Entry
- 19:03 - Academic CV vs. Industry Resume: Documentation and Expectations
- 24:10 - Arkouda & ARACHNE: Interactive, Massive-scale Python Analytics and Graph
- 27:35 - Backend Performance: Chapel, Supercomputing, and Democratizing HPC
- 29:32 - Research Lab as Startup: Open Source, Code Release, and Student Output
- 30:30 - Finding Datasets: Synthetic Data, SNAP, and Industry Collaboration
- 32:38 - Lab Composition & Mentorship Model (PhD, MS, undergrads, high school)
- 35:39 - Time Allocation: Balancing Teaching Load, Research, and Service
- 37:06 - Most Rewarding Work: Linear-time Algorithm & Pancake-flipping Variant
- 40:29 - Underappreciated Impact: STINGER and Streaming Graph Analytics
- 45:45 - Virtual Seminar Series & NJIT Data Science YouTube Channel
- 46:52 - Teaching-focused Careers: Universities Prioritizing Instruction over Research
- 49:01 - Staying Current: Journals, Conferences, and Information Triage
- 53:52 - Favorite Conferences: Supercomputing, IPDPS, HPEC
- 54:58 - Selecting Research Topics: Domain-driven, Impact-first Approach
- 56:40 - Building Usable Systems: From Research to Real-world Adoption (NASA example)
- 58:11 - Recruiting Students: PhD vs. Industry and Collaborative Opportunities
- 1:03:31 - Contact & Resources: davidbader.net, Arkouda, NJIT Data Science links