Jean L
- Research Program Mentor
Industry expert at St. John's University
Expertise
Computer Science is my main area of expertise as it is my current job is as a software engineer. I have to use calculus and statistics in my job as well since I focus on machine learning and artificial intelligence in that role. I am an active investor so I can also tell students about business. As a former frontend developer I also have a solid understand of product design.
Bio
As a seasoned professional with extensive experience at leading tech companies like Google, Snapchat, Facebook, WhatsApp, and Microsoft, my academic journey has been deeply rooted in the exploration and innovation within artificial intelligence and machine learning. My passion lies in empowering students by integrating these cutting-edge technologies into practical learning experiences, such as website building and mobile app development, to inspire and cultivate the next generation of tech enthusiasts and problem solvers. Outside the realm of technology and academia, I find balance and joy in the great outdoors, particularly through the exhilarating experiences of skiing, snowboarding, and skateboarding. These hobbies not only challenge me physically but also offer a unique perspective on risk-taking and creativity, qualities that I believe are essential both in personal endeavors and in navigating the ever-evolving landscape of software engineering and AI/ML.Project ideas
SymptomSolver: AI-Powered Symptom Analysis and Treatment Recommendations
SymptomSolver is an innovative platform designed for students to delve into the intersection of healthcare and technology. In this project, students will develop a web-based application that uses AI and machine learning to analyze user-reported symptoms and provide personalized healthcare recommendations. The project journey involves: Research and Development: Students will start by researching various AI and machine learning algorithms suited for medical data analysis. They will explore different symptom databases and medical literature to understand how symptoms correlate with conditions. Application Development: The core of the project is to develop the SymptomSolver application. Students will code the platform, integrating AI models to analyze symptoms and suggest treatments, home remedies, and professional consultations. Testing and Iteration: After development, students will test the application, gather feedback, and refine the algorithm to improve accuracy and user experience. Final Presentation: The project culminates in a comprehensive presentation, where students showcase their application, discuss the technology behind it, and reflect on the impact of AI in healthcare. End Result: Students will present their findings and the developed application through a combination of a detailed research paper and an interactive presentation. The research paper will cover their algorithms, development process, and analysis of the application's effectiveness. The interactive presentation will demonstrate the application in action, allowing the audience to understand its functionality and potential impact on healthcare accessibility. This project not only teaches valuable technical skills but also encourages students to consider ethical implications and the real-world application of AI in improving health outcomes.