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2020 – today
- 2024
[c20]Rakeshkumar V. Mahto
, Kanika Sood:
Advancing Occupancy Detection through Deep Learning and Sensor Integration. CCWC 2024: 173-177- [c19]Rakeshkumar V. Mahto, Kanika Sood:
HIV Progression and Outcome Prediction to Enhance Patient Matching for Clinical Trials. CCWC 2024: 278-284 - [c18]Brennon Hahs, Kanika Sood, Desiree Gomez:
A Data-Driven Model for Wildfire Prediction in California. SmartNets 2024: 1-6 - 2023
- [c17]Kanika Sood, Sijie Shang, Nima Nijad:
Predictive Analytics for Real Estate During COVID-19 Pandemic. AIIoT 2023: 338-344 - [c16]Kanika Sood, Aneesh Reddy Sannapu:
Risk Estimate of Complications in Type 2 Diabetes Using Ensemble Learning and Deep Learning. AIIoT 2023: 359-368 - [c15]Nidhi Shah, Kanika Sood, Jayraj Arora:
Speech emotion recognition for psychotherapy: an analysis of traditional machine learning and deep learning techniques. CCWC 2023: 718-723 - [c14]Anna Chiu, Kanika Sood, Ariadne Rincon, Davina Doran:
Detecting Hate Speech on Social Media with Respect to Adolescent Vulnerability. CCWC 2023: 724-728 - [c13]Rakeshkumar V. Mahto, Kanika Sood:
Harnessing the Power of Neural Networks for Predicting Shading. GHTC 2023: 327-333 - [c12]Kunal Chhatrapati, Kanika Sood, Purva Surve:
Human Activity Recognition Using Ambient Sensors. ISNCC 2023: 1-8 - [c11]Bharti Moryani, Kanika Sood, Kirti Chaudhary:
A Deep Learning Approach for the Classification of Tuberculosis and Pneumonia Using NIH Dataset. ISNCC 2023: 1-8 - [c10]Steven Rico, Kanika Sood, Kevin Hsu, Ethan Trinh:
Interpreting Live Video Sign Language and Translate into Text. ISNCC 2023: 1-6 - [c9]Nurhaliza Hassan, Kanika Sood, Gabriel Suzuki:
Machine Learning with Bitcoin Heist Ransomware. SmartNets 2023: 1-6 - [c8]Victor Tran, Kanika Sood, Kayhan Bakian, Aneesh Reddy Sannapu:
Indoor Navigation Assistance System for Visually Impaired with Semantic Segmentation using EdgeTPU. SmartNets 2023: 1-8 - [c7]Rakeshkumar V. Mahto, Kanika Sood, Nathaniel Ruppert:
Random Forest Empowered Shade and Fault Detection in Photovoltaic Panel. UEMCON 2023: 812-820 - [c6]Kanika Sood, Azucena Lizbeth Jimenez Martinez:
Supervised Learning for Non-Invasive Pre-Diabetes, Type 1 and Type 2 Diabetes Screening. UEMCON 2023: 821-829 - 2022
- [c5]Kanika Sood, Prathyusha Gundlapally:
Risk-Based Breast Cancer Prognosis Using Minimal Patient Characteristics. ICHI 2022: 170-181 - [c4]Merin Joseph, Kanika Sood, Tianhao Shen:
COVID-19 Epidemic Forecast using Machine Learning Regression Techniques. SmartNets 2022: 1-6 - [d1]Kanika Sood, Nate Ruppert, Rakeshkumar V. Mahto:
Partial Shading and Fault Simulation Dataset of Photovoltaics Module. IEEE DataPort, 2022
- 2020
- [j2]A. Grannan, Kanika Sood, Boyana Norris, Anshu Dubey:
Understanding the landscape of scientific software used on high-performance computing platforms. Int. J. High Perform. Comput. Appl. 34(4) (2020)
2010 – 2019
- 2017
- [c3]Kanika Sood, Boyana Norris, Elizabeth R. Jessup:
Comparative Performance Modeling of Parallel Preconditioned Krylov Methods. HPCC/SmartCity/DSS 2017: 26-33 - 2016
- [j1]Elizabeth R. Jessup, Pate Motter, Boyana Norris, Kanika Sood:
Performance-Based Numerical Solver Selection in the Lighthouse Framework. SIAM J. Sci. Comput. 38(5) (2016) - 2015
- [c2]Kanika Sood, Boyana Norris, Elizabeth R. Jessup:
Lighthouse: a taxonomy-based solver selection tool. SEPS@SPLASH 2015: 66-70 - [c1]Pate Motter, Kanika Sood, Elizabeth R. Jessup, Boyana Norris:
Lighthouse: an automated solver selection tool. SE-HPCCSE@SC 2015: 16-24
Coauthor Index
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