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Ekta Mulkalwar
Junior Machine Learning & Full-Stack Engineer specializing in applied AI systems
Los Angeles, CATeaching Associate2 years experienceJuniorEducationTechnologyWeb Development
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About
Master’s thesis focused on building and deploying a gait-based biometric authentication system using mobile accelerometer time-series data as an alternative to passwords/2FA. Emphasized real-world robustness by addressing sensor noise and variability (phone placement, walking speed, footwear) and improving safety using biometric metrics like FAR/FRR and EER, while collaborating closely with a non-ML thesis advisor.
Experience
Teaching AssociateCalifornia State University, Los Angeles
Graduate Research AssistantCalifornia State University, Los Angeles
Software EngineerCling MultiSolution Pvt. Ltd
Education
California State University, Los Angelesmaster, Computer Science (2025)
Vishwakarma Institute of Information Technologybachelor, Information Technology (2023)
Key Strengths
- Built and deployed an AI-powered gait authentication system (master’s thesis) using accelerometer time-series data
- Handled noisy/variable real-world sensor data via preprocessing (filtering, stride segmentation) and salience-based logic
- Applied biometric-specific evaluation metrics (FAR/FRR, EER) to reduce false acceptance and improve decision safety
- Structured AI workflow design with staged pipeline approach and edge-case testing
- Strong research-driven approach (reviewed 12–15 papers per step) to select methods and validate decisions
- Able to communicate ML/biometrics concepts to non-technical stakeholders (explaining why EER matters vs accuracy)
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