Electrical Engineering

Biswash Basnet Email: *******@***.***.***

LinkedIn/biswash-basnet Mobile: +1-945-***-****

Google Scholar/biswash-basnet Morgantown, WV 26505, USA Research Experience

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Cybersecurity and Fault Detection in Power Systems WVU Jan 2025 – Present

Designed FDIA detection and classification using ANN and BiLSTM with physics-informed loss.

Benchmarked models against Random Forest, SVM, and XGBoost.

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Battery Modeling and Parameter Estimation WVU

Jan 2025 – Present

Helped in developing EKF, UKF, AUKF calibration models(ECM) for 2RC/3RC.

Performed battery modelling

Performed perturbation and noise-based studies for robustness analysis.

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Utility-Scale Non–Lithium-Ion Batteries Review WVU July 2025–Present

Studied NaS, ZEBRA/Na–NiCl2, VRFB, Zn–Br chemistries and techno-economics.

Evaluated integration aspects of non-Li BESS in grid applications.

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Dynamic–Static Var Compensation Project IOE Pashchimanchal Campus(WRC) 2019 – 2022

Designed and validated a power factor improvement scheme using dynamic–static VAR compensation.

Published results in Journal of Engineering and Sciences. Education

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West Virginia University Morgantown, WV

Ph.D. in Electrical Engineering [Power Systems], GPA: 4.00/4.00 Jan 2025 – Present

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Tribhuvan University, IOE Pashchimanchal Campus (WRC) Pokhara, Nepal B.E. in Electrical Engineering, GPA: 3.75/4.00 (Aggregate 79.54%) 2018 – 2022 Publications

• B. Basnet, V. Sen: Networking for Power Grid and Smart Grid Communications: Structures, Security Issues, and Features. Recent Research Reviews Journal, 4(1):120–140, 2025.

• B. Basnet, K. Sapkota, R. Poudel, S. Kshetri, R. P. Pandey: Dynamic-Static Var Compensation for Improving Power Factor. Journal of Engineering and Sciences, 1(1):46–49, 2022.

• V. Sen, B. Basnet: Neural Network-Based Detection and Multi-Class Classification of FDI Attacks in Smart Grid Home Energy Systems. arXiv preprint, arXiv:2508.10035, 2025.

• B. Basnet: Robust Fault Detection and Classification in Power Systems via Physics-Informed and Data-Driven Learning (in preparation), 2025.

• B. Basnet: Utility-Scale Non–Lithium-Ion Batteries: Chemistries, Performance, and Grid Integration

(review, in preparation), 2025.

Skills/Expertise

• Python:

Proficient in Python programming with strong foundation in data manipulation, analysis, and visualization.

Developed neural network models using TensorFlow and scikit-learn.

Skilled in pandas, NumPy, Matplotlib for data analysis and visualization.

Familiar with database management and real-time ML model development in Jupyter Notebook.

• MATLAB:

Simulated optimization algorithms for economic load dispatch and OPF in power systems.

Developed a dynamic–static VAR compensator for power factor control.

• OpenDSS:

Simulated unbalanced IEEE distribution systems with DERs (PV, wind).

Integrated batteries and PVs into AEP feeder models, tested performance under varying conditions.

• Microsoft Office Suite:

Proficient in Word, PowerPoint, Excel, Outlook for documentation and presentations.

• Other Skills:

Proficient with Microsoft Teams and Google Workspace.

Teaching experience with LTSpice for circuit simulation. Honors & Scholarly Activities

• Academic Excellence Award: First position, Electrical Batch 2074, IOE WRC, 2022.

• Government Scholarship, IOE Pashchimanchal Campus, Merit-based (2017–2022).

• National Education Board Scholarship, Nepal, 2015. Research Interests

• Power systems and microgrids Optimization

• Cyber-physical security: FDI detection, fault detection/classification

• Battery modeling and parameter estimation and calibration

• Apllication of Physics-informed Neural Network and data-driven learning References

• Sarika Khushalani Solanki

Email: ******************@****.***.***

• Anurag Srivastava

Email: ******.**********@****.***.***

Contact this candidate