Aaditya Raval, Ph.D.

• Working as a doctoral researcher at Human-Centered AI Lab, I developed an Android application called ’Sensor Recorder’ that captures sensor data in a structured format.
• Analyzed and utilized sensor data to generate ML-based and DL-based models to test the feasibility of passive user identification and authentication. As a result, papers were published at IEEE TransAI 2020 and 2021.

Key achievements: Research training, smartphone software development, documentation, participant recruitment-management, publication.

• Working as a graduate teaching assistant in the computer science department at NCAT, I performed teaching, grading, creating quizzes, managing the course, and communicating with students.
• Mentored 30+ students each semester for two years and organized plans for effective communication between multiple TA’s.

Key achievements: Teaching, grading, creating quizzes, course management, and interpersonal communication.

• Managed and assisted in mobile application development phases such as requirement gathering, planning, design, development, testing, deployment, and maintenance. Additionally performed database optimization and improvement of multiple existing Android apps.

• Application, Software, and Website Development Center is known as ASWDC. I developed an Android application called ”Doctor’s Keep” that manages patient records such as contact details and treatment history. This app has a user-friendly custom interface that generates prescription documents

Coursework: Machine Learning and Data Mining; Advanced Network Science; Software Security Testing; Deep Learning; Security for Emerging Networks; Doctoral Research Methods.

Coursework: Network Security; Big Data Analytics; Master’s Thesis; Web Security; Software Specification, Analysis & Design; Advanced Design & Analysis of Algorithms; System Testing and Evaluation; Information Privacy & Security; Advanced Operating Systems.

Coursework: Software Engineering; Computer Architecture; Operating Systems; Data Structures; Analysis and Design of Algorithms; Database Management Systems; Data Mining; Programming Languages; Computer Networks; Information and Network Security; Artificial Intelligence.

• This paper presents a framework for passive user identification and authentication using onboard sensors of an Android smartphone. Using this framework, we propose a data preprocessing scheme that uses the absolute difference of consecutive repeated measurements of 7 onboard sensors. We developed 5 user identification and authentication models using various machine learning and deep learning methods.
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• Passive biometrics and behavioral analytics seek to identify users based on their unique patterns of activities. In this paper, we test the feasibility of using time-varying inertia data as passive biometrics to be used for user identification and authentication. We present a deep learning model for inertia pattern recognition that achieved a high accuracy of 87.17%.
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Thanks to my educational background in multiple countries, I hold excellent communication and leadership skills. I am an effective communicator and enjoy collaborating with diverse people. The following bar graph gives a quick idea about my technical skills and experience with programming languages, libraries, packages, and tools.

• Java, Python, XML, SQL
• HTML5, CSS3, Javascript, C/C++
• Android Studio, IntelliJ, Google Colab, Jupyter Notebook
• Visual Studio, .NET (C#)
• TensorFlow, Scikit-learn, Pandas, NumPy, NetworkX
• Google Firebase, RestAPI, NetBeans, LaTeX
• Microsoft Office, PyCharm, Spyder, Eclipse
• Adobe Photoshop, Unity, Mitre Caldera, Microsoft Power Bi