• Developed and implemented advanced mathematical programming models (MILP and MINLP) to enhance the resilience of power distribution systems against disruptions.• Utilized YALMIP and OpenDSS for detailed simulation and analysis, optimizing fault isolation and rapid service restoration processes.• Engineered strategies integrating proactive islanding and remote-controlled switches (RCS) to minimize outage durations and improve system recovery times.

• Assist both the instructor and students in the Power System Operation and Control course.• Prepare and evaluate assignments for students, ensuring thorough understanding and application of course material.• Document various aspects of the course to facilitate a comprehensive learning environment.• Invigilate different components of the course examinations to maintain academic integrity.• Manage specialized assignments such as the "Power Optimization," which includes:o Manually solving economic dispatch and unit commitment problems.o Formulating these problems for clear comprehension and analysis.o Utilizing GAMS-based optimization to find efficient solutions.• Solve and verify DCOPF (Direct Current Optimal Power Flow) problems using Lagrange Relaxation and GAMS, with validations executed through the PowerWorld Simulator.• Apply and integrate complex theories into practical, real-world scenarios within the course framework.

𝐔𝐌𝐓𝐏 𝐎𝐟𝐟𝐢𝐜𝐞𝐫• Attended a 3-month Traineeship under the State of the Art University Management Trainee Program (UMTP)• Following were the salient features of this programOrientation week session with VC and Department Heads, Orientation of office work and ISO 9001 2015 documentation, Routine correspondence, Interpersonal Skills, Policy Drafting, Critical thinking, Archive Management & Checklisting, People Management, Legal matters in universities, Inoculating gratitude and forgiveness, Resolving irrational beliefs, Strategies for implementation & employee engagement, Introduction to Economics, SPSS Software, Microsoft Office and Tools, Strategic Management𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠 & 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐃𝐢𝐫𝐞𝐜𝐭𝐨𝐫𝐚𝐭𝐞• Engaged in the planning of multibillion rupee projects for NUMS Institute of Advanced Studies and Research (NIASR) and NUMS Medical City• Performed in resolving NUMS development issues arising due to operations and coordination with other departments/ directorates of the university• Organized, planned and managed activities of the P&D office• Performed other duties as assigned𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐫 𝐃𝐢𝐫𝐞𝐜𝐭𝐨𝐫𝐚𝐭𝐞• Performed all duties (i.e. graduation and transcripts, enrollment reporting and student relations, petitions and appeals)• Exercised independent judgment in addressing the daily concerns of staff, students, and faculty• Interpreted and effectively communicated regarding the gathering and maintenance of student records in compliance with federal and state regulations, as well as internal policies and practices• Assisted Deputy Registrar and Registrar in maintaining the integrity of student records that include, but are not limited to, registration, grade processing, graduation, and transcript processing• Keeps informed of all changes in policies and by-laws that affect student records.• Performed related duties as required

• Designed and characterized enhancement-mode (normally-off) Gallium Nitride (GaN) High Electron Mobility Transistors (HEMTs) for high-power and high-frequency applications.• Investigated the impact of gate length, aluminium mole concentration, and barrier variations on the performance of normally-off GaN HEMTs.• Conducted numerical analyses using methods such as Newton-Raphson to solve for electrostatic potential and carrier densities within the device models.• Evaluated the effects of aluminium concentrations in the AlGaN barrier and buffer on the performance of GaN HEMTs, achieving optimal configurations for enhanced device performance.• Conducted extensive data analysis and developed machine learning algorithms to tackle high misclassification and low detection rates in electricity theft detection and utilized adaptive synthetic minority oversampling techniques to address class imbalance problems, enhancing the performance of supervised learning methods.• Trained and evaluated various machine learning and deep learning models, including LightGBM and XGBoost, on realistic datasets provided by electric utilities and achieved significant performance improvements with XGBoost and LSTM models, attaining high detection rates and low misclassification rates.• Performed literature reviews to support ongoing research projects. Conducted research, summarized findings, and interpreted data analysis results to draw inferences and conclusions.• Responded to emails related to research inquiries and collaboration opportunities. Attended project meetings, prepared project reports, and presented research results to the committee.• Collected, recorded, and analyzed data meticulously, ensuring accuracy and reliability in research outcomes.