As a Behavioral Data Analyst at CalendAI, I bring together my expertise in computer science and psychology to design innovative solutions that enhance user productivity and engagement. By integrating principles of behavioral psychology with advanced data analytics, I analyze user interaction patterns, identify trends, and develop predictive models that personalize smart scheduling algorithms based on individual needs and preferences.I collaborate with cross-functional teams, including data scientists, product managers, and UX designers, to translate psychological insights into actionable strategies for improving user experiences. My work involves designing A/B tests, conducting in-depth behavioral analyses, and refining features to align with how users think, behave, and manage their time.With a commitment to ethical data management, I prioritize transparency and privacy while leveraging cutting-edge AI and psychological principles to create tools that empower users to optimize their time and achieve their goals. By combining computer science and psychology, I contribute to shaping the future of productivity through an empathetic, user-centric approach.

MeAsmi represents a groundbreaking initiative in community psychology, focusing on neurodivergent individuals, their families, and therapists. Key aspects of the project included:Data Collection and Analysis: We gathered extensive data on diagnoses, symptoms, and the efficacy of various therapies. This rich dataset formed the foundation for our subsequent machine learning analysis.Machine Learning Integration: To uncover new insights from the collected data, we employed machine learning algorithms. These algorithms were designed to analyze patterns and correlations in the data, identifying trends that might not be immediately apparent through traditional analysis methods. For example, we used unsupervised learning techniques to cluster similar cases and supervised learning to predict therapy outcomes based on symptom profiles and treatment histories.Collaborative Team Leadership: I led a diverse team comprising three professors and five therapists. Together, we worked on aligning our domain expertise with machine learning insights to interpret the data meaningfully and accurately.Community Engagement and Platform Design: We designed the MeAsmi platform to be an interactive space where families of neurodivergent members could access information about therapies and their effectiveness. The platform also allowed for sharing insights derived from our machine learning analysis, providing a data-driven approach to understanding mental disorders.Ongoing Research and Collaboration: The project was grounded in continuous research and collaboration, ensuring that the machine learning models were regularly updated with new data and findings, thus maintaining the relevance and accuracy of the insights provided.

Working at D2/DX, fast-paced dining establishment. I led and directed a diverse team, managing multiple operations. I oversee daily operations, ensuring optimal functionality of all aspects of our dining service. I am responsible for training, and mentoring staff, providing continuous performance feedback and creating a team-focused environment that encourages top-level service, establishing and maintaining exceptional standards of customer service and also adhere to and enforce all food safety laws and guidelines.

I am passionate about transforming mental health care through technology. With a background in computer science and psychology, I specialize in leveraging machine learning to develop personalized therapeutic interventions for neurodivergent individuals. By integrating data-driven algorithms with behavioral science, I strive to create impactful solutions that enhance lives and improve mental health outcomes. Recently, I had the opportunity to speak at the Google Developer Student Clubs event, where I shared insights on the role of interdisciplinary collaboration in advancing AI-driven healthcare innovations. I explored how machine learning can be applied to analyze large-scale data and provide meaningful, personalized therapeutic outcomes.

For an internship project, I optimized productivity and reduced workloads by building datasets and databases for ZAD. I created advanced data structures through Power BI and through statistical analysis, I analyzed the data to provide the most optimal outcomes for the scenarios given for the project. I also did a cost-benefit analysis to further optimize the final result.

I created an optimal plan data plan that was based on the customers usage and needs. The plan proposed based on a model created using Customer data. The plan was produced and further optimized using Statistical inferencing and data modelling using PowerBI.