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Research and Teaching Assistant

University of Illinois at Urbana-Champaign

Conducting research in the field of machine learning and teaching undergraduate and graduate students in the field of mechanical engineering and machine learning.

• Engineered a robust multi-modal ML framework for real-world application, significantly enhancing system deployment readiness.
• Implemented denoising algorithms & generated data to boost detection accuracy and model reliability in diverse environments.
• Advanced sensor fusion methodologies to optimize data quality for ML processing, markedly improving detection performance.
• Created data pipelines and engineered features robust to environmental disturbances, yielding improved model performance.
• Managed participant recruitment, coordination, & collection of clinical experiments, ensuring well-labeled & accurate datasets.
• Led a team of 30 graduate and undergraduate students, mentoring, coordinating, and evaluating.

Research Associate

Joint Center of Excellence at KACST and Stanford University

Experimental research on flight dynamics to aid in stall and spin detection and recovery.

• Spearheaded the design and optimization of bespoke subscale aircraft test beds, significantly advancing stall-spin (SS) research through the integration of advanced signal processing, sensor fusion, and machine learning flight classification algorithms.
• Enhanced stall and spin prediction models with innovative sensor fusion, denoising, and machine learning classification algorithms.
• Optimized Data Acquisition system, & data management to increase operational flight-testing efficiency.
• Engineered a novel fail-safe SS detection controller using predictive analytics, setting new standards in SS prediction and recovery systems, contributing to advancing aerospace safety protocols.
• Created novel methodologies to evaluate airflow conditions and characteristics through hardware and software design.

Machinery Diagnostics Engineer

SABIC

• Pioneered the use of data mining to provide insights, significantly improving productivity and reliability metrics.
• Provided critical engineering support globally, enhancing productivity across 90 affiliates.
• Led the revamp of engineering SOPs, streamlining procedures across SABIC's global operations.
• Spearheaded lean manufacturing initiatives, improving production records by 15% and operational efficiency by 12%.

PhD

University of Illinois at Urbana-Champaign

Mechanical Engineering, Applied Machine Learning

• Deep Learning
• Reinforcement Learning
• Generative AI
• Abstract Linear Algebra
• Artificial intelligence
• Probability and Statistics

Master of Science

University of Illinois at Urbana-Champaign

Aerospace Engineering

Master of Engineering

Lehigh University

Mechanical Engineering, Manufacturing

Bachelor of Science

Lehigh University

Mechanical Engineering

Review of Machine Learning Methods for Anxiety Detection

IEEE Transactions on Affective Computing

Feasibility of VR in Eliciting Anxiety in Older Women.

2021 IEEE EMBC

In-flight measurement of wing surface pressures on UAV during stall/spin maneuvers

2016 AIAA flight testing

Advancing Anxiety Detection: Efficacy of Machine Learning Models in Real-World

under submission

Assessing Impact of Environmental noise on Anxiety Detection

IEEE Transactions on Affective Computing