Shervin S
- Research Program Mentor
PhD at University of Pittsburgh
Expertise
computational fluid dynamics, computer aided design, artificial intelligence, high performance computing, machine learning, large language models, product management
Bio
I am a dedicated educator and mentor passionate about fostering scientific curiosity and innovation. As a Grand Award Judge at the International Science and Engineering Fair, I have evaluated and guided students’ STEM projects. I also mentor students preparing for science fairs, helping them refine research questions, strengthen experimental design, and present their work with clarity and confidence. Previously at the University of Pittsburgh’s School of Engineering, I taught undergraduate and graduate courses that bridged theory and application while mentoring research projects across levels. I now work at the intersection of AI and product management, bringing real-world industry perspective to the challenges of building intelligent systems. This combination of academic depth, industry experience, and judging insight allows me to support students in designing rigorous, impactful projects grounded in both scientific excellence and practical application. Beyond formal roles, I teach coding at hackathons and workshops, champion hands-on collaborative learning, and support initiatives like Girls Rock Science to broaden access and inspire the next generation of STEM leaders. I am committed to mentoring students who want to turn curiosity into meaningful research and real-world impact.Project ideas
Simplifying Fiery Reactions with Data
I spearheaded an exciting project called "Simplifying Fiery Reactions with Data" that aimed to make complex combustion simulations easier to understand and work with. Imagine a puzzle where you have to figure out how different things burn and react together. Well, in the world of science and engineering, we use special computer programs to simulate these reactions, which help us design better engines, create cleaner fuels, and even understand how fire behaves. But here's the catch: these simulations can be really complicated and time-consuming. That's where our project would come in! We will use tricks with data to make these simulations faster and simpler, like finding shortcuts in a maze. By doing this, we can unlock valuable insights into combustion and make it much easier for scientists and engineers to study and improve how things burn. It's like making a tough puzzle a whole lot easier to solve, and it's all about making our world safer, cleaner, and more efficient!
Field Survey Proposal for: Building an Eco-Friendly Multipurpose Stadium/
The project’s primary aim is to coduct a study on multipurpose dome for football, among other uses, while adhering to sustainable practices. We aimed to align this project with Saudi Arabia’s national goals of reducing carbon emissions and promoting renewable energy. By using eco-friendly materials and energy-efficient design, the dome will not only minimize environmental impact but also serve as a model for sustainable development in the region. The outcome is presented in the local highschool journal as a scientific research paper.
Advancements at the Intersection of AI and Aerospace Science
This research project aims to explore the transformative role of artificial intelligence (AI) in aerodynamics and highlight its profound impact on the field. It examines how AI algorithms are revolutionizing traditional methods of aerodynamic analysis and design, allowing for more efficient and optimized aircraft configurations. The project delves into specific applications such as airfoil design, where AI decreases the time to results with the design of the experiment. It also explores the challenges that come along with linking AI with aerospace whether that be the guidance, navigation, and control issues or the long-term sustainability and efficiency of current commercial systems.
Developing a Novel Robot Localization Algorithm Using Low-Cost Sensors
In this project, I mentored a student who found a simpler way for robots to track their location using everyday low-cost sensors. Traditional methods often need careful measurements of wheel positions and still struggle with sideways drift. My student showed that for certain wheel setups those measurements aren’t necessary, then built a clean arc-based algorithm that reconstructs the robot’s path while naturally correcting for drift. The results were strong enough that we turned the work into a research article, which has been submitted to a journal for publication.
Modern Technology's Impacts on the Environment and the Effectiveness of Renewable Energy Systems
In this project, I mentored a student in exploring how different methods of electricity production affect the environment and how we can reduce carbon dioxide (CO₂) emissions. We investigated renewable energy technologies, carbon capture methods, and emerging solutions for reducing greenhouse gases. A key part of the project was comparing the environmental benefits, costs, and energy requirements of different approaches to understand which solutions are the most practical and sustainable. This project is a great opportunity for students interested in climate change, renewable energy, and engineering to explore real-world environmental challenges, analyze scientific research, and identify promising technologies that could help build a cleaner future.