- Research Program Mentor
PhD at Massachusetts Institute of Technology (MIT)
Biotech and bioengineering, writing papers (any type), Engineering (especially Mechanical & Biomedical), Medical Device, Physics, Data Science, Programming, Code writing, Machine Learning, Image Processing, Mathematics
BioCan we 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 devices that can make vaccinations easier and more accessible to the world especially in developing countries. Before that, I did my Masters and Bachelors degrees both in Mechanical Engineering. My research career up to this point has resulted in more than 20 publications in notable journals and conferences, cited more than 300 times to date. I earned a graduate certificate in Business Analytics, Healthcare from MIT Sloan School of Management, and a graduate certificate in Medicine from Harvard-MIT Division of Health Sciences and Technology. I am currently a Staff Scientist at SiO2 Medical Products, an advanced Materials Science company. Simultaneously, I am a postdoctoral researcher at MIT working on next-generation drug delivery devices for application to cancer therapy and infectious diseases. During my free time, I enjoy oil-painting, 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. My favorite artists are The Weeknd and Post Malone. I am originally from Iran and love making Persian foods in my free-time. Driving cars is also another hobby of mine. I have a passion for fast cars.
A review article about areas for innovation in medical devices
The goal of this project is threefold: 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. 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
A code for measuring geometrical features of tumors
The goals of this project are as follows: 1- Learn how to do image analysis with program of choice (Python, ImageJ, or MATLAB or any other software of interest). 2- Drive geometrical feature of a tumors (diameter, density, sphericity, etc) from histology images 3- Use existing literature to classify if the tumor is benign or malignant. Result of this project is a code which can be used by doctors to help identify tumor diagnosis. Reference: https://www.healthtravellersworldwide.com/cancer-detection-techniques/
A survey on acceptability of vaccines among millennials
The goal of this project is to familiarize the student with the following skillsets: 1- How to design a survey based on a scientific question 2- How to identify the responders and expand outreach 3- How to analyze results of the survey. Results of this project can be published in a scientific magazine, LinkedIn article, or similar outlets. Reference for the image: https://www.vectorstock.com/royalty-free-vector/medical-survey-line-icon-hospital-patient-history-vector-23114522
Application of AI to clinical diagnosis and disease classification
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.