NCWIT Selects 2023 Collegiate Award Recipients

The National Center for Women & Information Technology (NCWIT) Aspirations in Computing Program (AiC) is pleased to announce the recipients of the 2023 NCWIT Collegiate Award, celebrating 47 undergraduate and graduate women, genderqueer, and non-binary students from 38 academic institutions nationwide. Conferred annually, the award recognizes technical contributions to projects that demonstrate a high level of innovation and potential impact.
The entire NCWIT AiC program platform is supported generously by Apple. AiC also receives support for specific national program elements; the NCWIT Collegiate Award is sponsored by Qualcomm and Amazon.
Winners
- Serena Ivery, Birmingham-Southern College;
▶️ Clearing the Cobwebs: Benefits of Identifying Online Human Trafficking
- Anika Puri, Massachusetts Institute of Technology (MIT);
▶️ ElSa: A Novel Real-time Wildlife Poacher Detection Solution Leveraging Machine Learning Driven Spatio-temporal Analysis of Nighttime UAV Thermal Infrared Videos - Swapna Throve, University of Virginia;
▶️ Data-Driven Scalable AI for Addressing Problems in the Study of Smart Grids
Honorable Mentions
- Noor Boukari, Dartmouth College;
▶️ Developing a Mobile App for Accessible Malaria Diagnosis Using Deep Learning Semantic Segmentation
- Taylor Bradley, Johns Hopkins University;
▶️ Novelty Detection in Network Traffic: Using Survival Analysis for Feature Identification
- Angela Busheska, Lafayette College;
▶️ EnRoute
- Dominique Calder, George Mason University;
▶️ Building and Decaying a Document Corpus For Sub-Block Forensic Analysis
- Portia Cooper, University of Arizona;
▶️ Training Transformer Models to Recognize Hate Speech Masked by Homoglyphs
- Katelyn France, University of Minnesota - Duluth;
▶️ "Anaphylactic Shocker!" Creating Novel Medtech Devices and Supporting the Next Generation of Women in STEAM
- Maliha Haider, Kean University;
▶️ Comparison of Yelp's Star Rating and Text Reviews
- Dana Joseph, Dartmouth College;
▶️ Catalace: Using Artificial Intelligence and Precision Medicine to Accurately Predict Cancer
- Victoria Li, Harvard University;
▶️ CROTON: An Automated and Variant-Aware Deep Learning Framework for Predicting CRISPR/Cas9 Genome Editing Outcomes
- Rachel Masters, Colorado State University;
▶️ Virtual Reality Forest Bathing: Importance of Biomass for Stress Reduction in VR Nature
- Eesha Nayak, University of Texas - Austin;
▶️ Nutri: Clinical Decision Support System (CDSS) to help primary care providers (PCPs) set personalized nutrition goals with patients
- Katherine Skocelas, Michigan State University;
▶️ Understanding the Evolution of Multicellular Organisms
Finalists
Hena Ahmed Scripps College Towards Reproducible Machine Learning: A Sensitivity Analysis of Pseudo-Randomness in ML Models | Drshika Asher University of Illinois - Urbana Champaign Horizon Worlds: Features and Moderation-specific Affordances |
Kary Cabrera University of Southern California Computer Vision for Business Impact: Identifying Objects and Sorting by Color | Lily Chen Massachusetts Institute of Technology (MIT) Automated Detection of Diabetic Retinopathy with Deep Learning |
Alexandra Chin Wellesley College Efficacy of a Misconceiving Robot to Improve Computational Thinking in Collaborative Problem Solving | Shide Dehghani University of California - Berkeley Extract Flora |
Diya Dinesh Carnegie Mellon University A Novel Multi-Model Approach to Real-Time Road Accident Prediction and Driving Behavior Analysis using a Fully-Connected Feed-Forward Deep Neural Network and an Object Detection CoreML Model | Ye-un Christina Go University of Texas - Austin Post-Facto Calibration of the HETE-2 (High Energy Transient Explorer) Satellite Proportional Counter |
Joanna Huang University of Illinois - Urbana Champaign Improving Robot-Aided Care of Physically Impaired Individuals | Rrezarta Krasniqi University of North Texas A Three-Pronged Approach for Detecting Highly Impactful Quality Concerns in Source Code |
Aparna Kumar Columbia University Improving SEACells | Paridhi Latawa Massachusetts Institute of Technology (MIT) EasyComm |
Amanda Liu University of Maryland - College Park Debugging Techniques in Professional Programming | Bryn Loftness University of Vermont The ChAMP System: An Open-Access Tool for Enhancing Knowledge Discovery and Detecting Digital Phenotypes of Early Childhood Mental Health |
Sana Madhavan University of Illinois - Urbana Champaign Processing Mindfulness Meditation: An Exploratory Analysis | Christine Mbagwu University of Maryland Global Campus High Performance Computing in the Cloud |
Lauren McGuirk Grand Valley State University Virtual Motion Therapy (VMT) | Sarah Motteler Rice University Garden Planner |
Jalynn Nicoly Colorado State University Virtual Reality Restorativeness | Marian Obuseh Purdue University Sensor-based Surgical Data Science and Human Factors in Robotic-Assisted Surgeries |
Kim Anh Phung University of Dayton Co-AID: Collaboration of Artificial Intelligent Doctors for X-Ray Image Analysis | Lori Porter University of Louisville Galaxy Evolution with Simulations and Citizen Science |
Tanisha Rajgor Northeastern University Deepfake Detection With Haar-Cascades & GANs | Yarianis Rivera Boston University The Covid Run Game |
Jocelyn Shen Massachusetts Institute of Technology (MIT) Modeling Empathic Similarity In Personal Narratives | Priyanka Shrestha Stanford University Developing a Mechanistic Tensor Decomposition (MTD) for Systems Serology Data |
Saumya Suvarna University of Pennsylvania Social Media as an Indicator of Declining Mental Health | Quincy Taylor Brigham Young University - Provo Understanding Hacktivist Groups through Online Media Posts |
Akshaya Venkatesh University of Illinois - Chicago Changing Consumer Behavior - A Mobile App to Minimize Food Waste and Maximize Harvest | Keke Wu University of North Carolina - Chapel Hill Designing Accessible Visualizations for People with Intellectual and Developmental Disabilities (IDD) |
Maya Zeng California State University - Northridge Sustainable Origami | Victoria Zhang Harvard University Characterizing Quantum Processors Using Discrete Time Crystals |