Neha Kardam

Student at University of Washington

Research Expertise

Natural language processing applications in Engineering Education

Education

About

<br> | Interdisciplinary researcher with experience in using statistics, predictive analytics, mixed methods research and applying machine learning techniques in data driven research. Research interests include understanding and applying natural language processing techniques in real world problems | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | |

Publications

Communication and load balancing using SCADA model based integrated substation

2013 International Conference on Energy Efficient Technologies for Sustainability

2013

Implementation of particle swarm optimization for dynamic economic load dispatch problem

2013 International Conference on Energy Efficient Technologies for Sustainability

2013

An Insight into Students’ Feedback on Synchronous Distance Learning During COVID-19 Lockdown

2021 ASEE Virtual Annual Conference Content Access Proceedings

“Examining the Changing Perceptions of Graduate Students’ Role as Teaching Assistant with Online and Hybrid Labs during COVID-19” (Instruction)

2021 ASEE Virtual Annual Conference Content Access Proceedings

Applying Natural Language Processing Techniques to an Assessment of Student Conceptual Understanding

2016 ASEE Annual Conference & Exposition Proceedings

How did the landscape of student belonging shift during COVID‐19?

Journal of Engineering Education

2023

Augmenting Traditional ME Curriculum with Digital Badge Microcredentials

2021 ASEE Virtual Annual Conference Content Access Proceedings

Neural network approach to improving fault location in local telephone networks

9th International Conference on Artificial Neural Networks: ICANN '99

1999

Education

Ph.D., Data Science / August, 2024 (anticipated)

Seattle, Washington, United States of America

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