Machine Learning Engineer / Research Scientist / Cyber Security Engineer / Software Engineer
Developing and implementing Python-based algorithms for analyzing election data, extracting insights, and detecting misinformation to ensure the integrity of datasets and enhance research accuracy.
Engineering a proprietary approximate string-matching algorithm tailored for election data analysis, facilitating data wrangling and anomaly detection using techniques such as isolation forest, one-class SVM, and XGBoost to improve analytical robustness.
Utilizing synthetic data generation techniques to boost research productivity, enabling broader hypothesis exploration and enhancing the scalability of data-driven approaches in election analysis.
Presenting research findings to academic and professional audiences, supported by comprehensive technical documentation, fostering transparency, and contributing to the advancement of election data analysis methodologies.
Offered valuable mentorship and guidance to students undertaking thesis and project work across a diverse spectrum of computer science disciplines, thereby fostering their academic and professional development.
Orchestrated academic events such as conferences and programming contests, providing valuable opportunities for students to showcase their skills and network with industry professionals.
Took proactive leadership in spearheading efforts to refine and moderate curriculum content for courses taught, ensuring alignment with industry standards and incorporating emerging trends in computer science education.
Engaged in ongoing professional development through pedagogy-focused training sessions, refining teaching methodologies to better meet the diverse needs of students and enhance the overall learning experience.
Developed and administered assessments aligned with course and program objectives, ensuring that evaluation methods accurately measured student comprehension and mastery of concepts in Structured Programming Language, Data Structures, Theory of Computing & Automata, Data Communication, and Digital Logic Design.
Instructed courses spanning a broad spectrum of computer science topics, including Programming Language, Data Structures, Theory of Computing & Automata, Data Communication, and Digital Logic Design, providing students with a comprehensive understanding of fundamental concepts and practical applications within the field.
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