Exhibitors & Event Agenda
Browse the research fair floor plan, list of exhibitors, and event agenda.
Undergraduate Computer and Data Science Research Fair
Event Date: Thursday, November 2, 2023 (5:00 PM - 8:00 PM)
Location: Carleton Commons - Mudd Building - 4th Floor
2023 Agenda
To give our undergraduate exhibitors time to meet and network, the fair will be split into two exhibitor groups. Projects will switch out in the middle of the fair.
This is a grazing style event, in which students will be posted by their projects. Attendees should feel free to engage with the work, ask questions, and provide helpful feedback.
Food and beverages will be available throughout the event - head across the hall to the DSI Suite for catering!
5:00 PM - 6:20 PM: GROUP A
6:20 PM - 6:30 PM: Intermission & Remarks
Susan McGregor, Data Science Institute
Undergraduate Organizing Committee
6:30 PM - 7:50 PM: GROUP B
7:50 PM - 8:00 PM: Awards!
Clifford Stein, Interim Director of the Data Science Institute, will issue the awards for Best in Each Track, and Best Overall
Joyce Robbins, Lecturer in Discipline in the Statistics Department at Columbia, will issue a special sponsored price “Best Use of Statistical Innovations”
Floor Plan
List of Exhibitors
GROUP A
5:00 PM - 6:20 PM
D01: Digital Twin of NYC as a Platform to Study Naturalistic Driver-Pedestrian Interaction
Submitted by: Ellie Yan, Barnard College, Junior, Computer Science
Track: Create
D02: Effective English Language Learner Tutoring with Language Models
Submitted by: Daniel Ben-Levi, Columbia College, Freshman, Computer Science + Cognitive Science
Track: Create
D03: Open Source Economics
Submitted by: Ramya Subramanian, Barnard College, Sophomore, Computer Science
Track: Converge
P01: TensorShop: A Visualization Suite to Facilitate Fast Matrix Multiplication
Submitted by: Jonah Stockwell, Columbia College, Freshman, intended Computer Science
Track: Change
P02: Enhancing Time Series Forecasting through a Hybrid LSTM-Transformer Model
Submitted by: Spencer Austin, SEAS, Junior, Operations Research: Analytics
Track: Change
P03: Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysis
Submitted by: Caden Lin, Columbia College, Sophomore, Mathematics, Computer Science
Track: Change
P04: Space Microbiology: Mitochondrial Transfer in Spaceflight Environments
Submitted by: Theodore Nelson, Columbia College, Senior, Computer Science
Track: Converge
P05: Designing Interactive Music Devices
Submitted by: Aditi Haiman, Barnard College, Senior, Computer Science
Track: Converge
P06: Identity Crisis? Self-identification versus Group Selection in the 2024 Taiwanese Presidential Elections
Submitted by: Sunny Fang, Barnard College, Junior, Data Science
Track: Converge
P07: MultiModal Hierarchical Classification (MMoCHi) for CITE-Seq
Submitted by: Will Specht, SEAS, Junior, Biomedical Engineering
Track: Converge
P08: ML Scan-Number Imputation
Submitted by: Youssf Hegazy, Columbia College, Junior
Track: Converge
P09: OpenDataVal: a Unified Benchmark for Data Valuation
Submitted by: Kevin Jiang, Columbia College, Senior, Mathematics + Statistics
Track: Create
P10: Telematics for Risk Scoring Cyber Attacks
Submitted by: Heeyun Kim, SEAS, Junior, Computer Science
Track: Create
GROUP B
6:30 PM - 7:50 PM
D01: Digital Twin of NYC as a Platform to Study Naturalistic Driver-Pedestrian Interaction
Submitted by: Ellie Yan, Barnard College, Junior, Computer Science
Track: Create
D02: Safe and Reliable Medical Records: Assessing the Robustness of openEMR
Submitted by: Angel Cui, Barnard College, Senior, Computer Science
Track: Create
P01: Prediction of Tumor RNA-Seq Expression from Whole-Slide Images using Deep Learning
Submitted by: Nolan Tremelling, SEAS, Senior, Electrical Engineering
Track: Converge
P02: Development of an Automated Pre-Processing Method for Feature Identification in Carotid Arterial Wall Motion Waveforms: A Feasibility Study In Vivo
Submitted by: Rahi Mitra, SEAS, Sophomore, Computer Science
Track: Change
P03: A Systematic Benchmarking and Optimization of Single-Nucleus RNA Sequencing for Biological Analysis
Submitted by: Manan Vij, Columbia College, Sophomore, Computer Science + Biology
Track: Converge
P04: A Custom-Designed App for Comprehensive Proteomics Analysis Reveals Exosomal Biomarker Candidates for Non-invasive Diagnostics in Non-Small Cell Lung Cancer
Submitted by: Manan Vij, Columbia College, Sophomore, Computer Science + Biology
Track: Converge
P05: Examining the Drivers of Irregular Migration out of Central America and West Africa
Submitted by: Eva Das, Barnard College, Junior, Computer Science
Track: Converge
P06: Investigating the Impact of Early Life Stress on Spontaneous Alternation Tasks in Mice: A Quantitative Approach
Submitted by: Lucy King, Columbia College, Sophomore, Computer Science
Track: Converge
P07: Reinforcement Learning in Dual-Sourcing Problem: A Focus on Real and Simulated Demand Shocks
Submitted by: Yihan Shen, SEAS, Junior, Computer Science
Track: Create
P08: An Efficient Algorithm to Build Atomic-Structure Datasets for Machine Learning Potential Training
Submitted by: Aleksandra Pawlowska, SEAS, Sophomore, Chemical Engineering
Track: Create