Morteza S
- Research Program Mentor
PhD at Massachusetts Institute of Technology (MIT)
Expertise
Biotech and bioengineering, writing papers (any type), Engineering (especially Mechanical & Biomedical), Medical Device, Physics, Data Science, Programming, Code writing, Machine Learning, Image Processing, Mathematics
Bio
Can we leverage AI, Robotics, and Engineering tools to make life easier for more than 95% of the world population who are living unhealthy lives? My passion centers on this goal by leveraging technology toward solving major scientific problems in healthcare and medicine. I finished my PhD in Mechanical Engineering at MIT with a focus on developing AI-optimized devices that can make treatment of diseases easier and more accessible to the patients. Previously, I did my Masters and Bachelors degrees both in Mechanical Engineering. I have published ~ 40 scientific publications in competitive journals and conferences, cited more than 850 times as of April 2025, in addition to one licensed US patent. I earned a graduate certificate in Business Analytics and another in Healthcare from MIT Sloan School of Management with a focus on application of AI to healthcare, as well as a graduate certificate in Medicine from Harvard-MIT Division of Health Sciences and Technology. I am currently a Senior Research Scientist at Gilead Sciences, a multinational pharmaceutical company in the California Bay Area. Prior to that, I was a research scientist at biotech companies namely SiO2 Medical Products, an advanced Materials Science company, and Syntis Bio, a startup committed to revolutionizing drug delivery systems. I joined Polygence in August 2022, and have ever since mentored over 20 research projects, led over 5 Pods centered on AI, provided career advice to +50 high school students, provided publication support to +30 students, and regularly worked as judge/reviewer for the Polygence Symposium. Over 10 students expressed after working with me that their experience "exceeded their expectations". My students have successfully published their research in top research journals. During my free time, I enjoy biking, outdoor activities such as hiking, walking, and kayaking. I am also an avid fan of audiobooks, especially those related to psychology, neuroscience, physics, entrepreneurship and business. I love listening to music in a variety of genres, especially pop and R&B. Driving cars is also another hobby of mine. I have a passion for fast cars, and am a big Porsche fan!Project ideas
A review article about areas for innovation in medical devices
The goal of this project is to perform research on state of the art technologies and write a review paper to address the following objectives: 1- Identify leading medical device technologies and their areas of application 2- Identify drawbacks and challenges these devices impose on patients 3- Brainstorm about ideas on how to improve the technologies or what additional features are necessary to be considered for next-generation of such devices. We will go over skills such as literature search, data analysis, writing a literature review paper, and developing an original idea. Result: expected results is a scientific article/magazine paper Reference for the submitted image: https://www.plasticstoday.com/medical/future-medical-materials-and-medtech-innovation
Developing machine learning models for automated classification of healthy and cancerous based on MRI images
The goals of this project is to develop a Python script for machine learning and write a research paper aimed at developing machine learning models for classification of MRI images. We will go over the following points: 1- Learn how to perform data analysis, image preprocessing, visualization, correlation study, data mining and exploration in Python. How to find high quality datasets online. 2- Learn how to develop and train machine learning algorithms in Python that can identify unhealthy individuals or people with high risk of cancer by looking at their MRI images. How to optimize and compare the performance of these models. 3- Write the results of findings as a research paper to be published in reputable research journals, also showcase your work on public sites such as GitHub and Kaggle. Many of such projects also were proceeded to science fairs. Image Reference: https://www.healthtravellersworldwide.com/cancer-detection-techniques/
Development of a machine-learning guided assistive device for helping disabled people
The goal of this project is to develop a prototype device using 3D printing, microcontrollers and robotics which can be presented in a science fair and published as a research paper. Throughout the project we will cover three skillsets: 1- Prototyping robotic devices with healthcare applications, using 3D printing (optional) 2 -Programming the device using Python to interact the the environment and process the inputs received from the user 3- Test the prototype and evaluate its performance to report findings as a science fair application and/or scientific paper Reference for the image: https://www.selectmedical.com/why-choose-us/advanced-robotics-and-rehabilitation-technology/
Machine learning modeling for early prediction of heart diseases based on patient's medical records
AI has become an important tool in the classification of diseases and conditions in clinical settings. Machine learning algorithms can be trained on large datasets of patient data to recognize patterns and predict diagnoses with a high degree of accuracy. This allows healthcare professionals to make more informed decisions and provide more personalized treatment plans for their patients. AI can also be used to analyze medical records, laboratory results, and imaging data to identify risk factors for certain conditions or diseases, allowing clinicians to take proactive measures to prevent or mitigate potential health problems. Additionally, AI-powered clinical decision support systems can assist healthcare providers in making more accurate diagnoses and treatment recommendations, leading to better patient outcomes. In this project, we aim to accomplish two goals 1) develop a machine learning based algorithm for classification of disease based on existing patients' medical records, and 2) write a manuscript to summarize the results related to machine learning algorithm to be submitted to student journals in the field of Computer Science.