Computer Science Colloquium
Upcoming:
April 8 @ 4:30 pm in Jepson Hall 118
Speaker: Ramkumar Selvarathinam, Senior Manager in Data Engineering at CapitalOne with extensive experience leading large-scale data platform initiatives and integrating AI/ML solutions into enterprise systems.
Title: Building Enterprise-Scale Data Pipelines in AWS
Abstract: This presentation introduces students to the world of data engineering and demonstrates how modern enterprises build scalable, reliable, and cost-effective data pipelines in the cloud. Using AWS services such as Lambda, Glue, and EMR, we will explore how raw data is ingested, transformed, stored, and made available for analytics. Students will learn the roles of different AWS services, compare their strengths, costs, and use cases, and see how they work together in a real-world pipeline architecture.
Other Talks That May Interest Computer Science Majors:
April 1 @ 4:30 pm in Gottwald Science Center D-209
Speaker: Robert Kent, PhD, a senior quantum success engineer at QBLOX
Abstract: Robert is currently a Senior Quantum Success Engineer at Qblox, where he teaches customers how to use Qblox's fully integrated quantum control stack and ensures their success in experiments. He holds a Ph.D. in Physics from The Ohio State University, where he studied machine learning, FPGA programming, nonlinear control, and the readout of superconducting and neutral atom qubits. Robert received his Bachelor's degree in Physics from the University of Richmond in 2020. As an undergraduate researcher, he worked with Mariama Rebello Sousa Dias to measure surface plasmon resonance in Al-Au thin films.
Past Events:
March 24 @ 4:30 pm in Jepson Hall 118
Speaker: Rebecca M. M. Hicke, PhD Candidate in Computer Science, Cornell University
Title: How to Read Books with AI: AI and Narrative Analysis
Abstract: Join us as Rebecca M. M. Hicke, PhD candidate at Cornell, presents a talk, How to Read Books with AI: AI and Narrative Analysis. Rebecca's research interests lie in computational humanities, natural language processing, and cultural analytics. Specifically, I explore how large language models (LLMs) can be use for complex textual, particularly literary, analysis tasks.