About
BioMind AI Lab offers a dynamic platform where senior undergraduate and graduate students actively engage in projects related to biomedical AI. This endeavor offers students invaluable hands-on experience, enabling them to contribute to joint research efforts that expand the boundaries of medical data analysis.
Principal Investigator
Pegah Khosravi, PhD
Assistant Professor of Biomedical AI, New York City College of Technology
Faculty Member, Biology and Computer Science Program, CUNY Graduate Center
Deputy Editor, Journal of Magnetic Resonance Imaging
Address: 285 Jay Street, Brooklyn, NY 11201
Office: A502D, Phone: 718-260-5986
GoogleScholarGitHub
Saber Mohammadi, MSc
Remote Research Assistant
Abhinita S. Mohanty, MSc
PhD Student
Joining BioMind AI Lab: Opportunities for Students
Internship Opportunities for Undergraduate Students (Fall Semester Only): We appreciate your interest in pursuing an internship course with us at City Tech. The internship program offers students a valuable opportunity to gain practical experience and potentially secure future job positions. If you have previously applied to several institutes without success, we recommend that you compile all relevant documents, including your resume and cover letter, into a single PDF. Our research primarily focuses on medical data analysis, utilizing machine learning and deep learning algorithms. This work involves extensive coding, particularly in Python. If you're interested in joining our team, I strongly recommend improving your Python skills. Additionally, consider taking introductory courses like 'Machine Learning A-Z™: AI, Python & R + ChatGPT Bonus' and 'A Deep Understanding of Deep Learning (with Python intro)' to build a strong foundation in these areas. Students interested in interning (BIO4910/BIO4920) with me should have completed BIO3450 and plan to enroll in BIO4450. Selected interns will collaboratively develop a project proposal, contingent on data availability. We'll work together to determine your project's specifics and direction.
Remote Research Assistant Opportunities for Graduate Students: For those interested in joining the BioMind AI Lab as research assistants, please be aware that, currently, financial support is unavailable. However, you can engage with our projects virtually and gain insights throughout various stages of collaborative projects with multiple medical institutes. To ensure a strong commitment to our projects, we require candidates to undergo an interview process before joining the lab. This process helps us understand your interests, skills, and alignment with our research goals. It's important to emphasize your commitment to seeing the project through, from its inception to the final paper's composition.
Ph.D. Student Opportunities in the Biology and Computer Science Program at CUNY Graduate Center: I am delighted to extend an invitation to prospective students to join the dynamic and innovative Computer Science program at the CUNY Graduate Center, where I serve as a faculty member. Our program is currently welcoming applications for the upcoming fall semester, with a submission deadline of December and January. For detailed information about our curriculum, faculty, and application process, please visit our Biology and Computer Science website. Should you have any questions or require further details, feel free to reach out to me at the professional email address provided on my faculty profile page. I am committed to providing timely responses to all inquiries. We look forward to your application and the possibility of welcoming you to our academic community.
Ongoing Project Titles
Enhancing Autism Detection from fMRI: Impact of Brain Atlases and Batch Correction on Diagnostic Accuracy - In Collaboration with University of California San Diego, San Diego
Beyond Subjectivity: Unsupervised Machine Learning for Objective Categorization and Synthesis of Vocal Fold Lesions - In Collaboration with Weill Cornell Medicine, NYC
Leveraging Advanced Machine Learning for Improved Classification and Prediction of Kidney Diseases - In Collaboration with AdventHealth Global Robotics Institute, Orlando
Image-Based Artificial Intelligence in Cancer Research: Advances in Radiology, Pathology, and Multimodal Approaches - In Collaboration with National Cancer Center, Gyeonggi, South Korea
Published Academic Papers Collection
Thesis and Capstone Project Archive
Deep Neural Network for Automated Scoring of Estrogen Receptor Molecular Marker in Breast Cancer. Ebtisam Mohamed, Biomedical Informatics (B.S.) Student, Department of Biological Sciences, City Tech - Fall 2022
A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using MR Images. Mehnaz Hoque, Biomedical Informatics (B.S.) Student, Department of Biological Sciences, City Tech - Spring 2023
Brain Tumor Detection and Classification from MRI Images Using a Convolutional Neural Network Model. Raecine Greaves, Biomedical Informatics (B.S.) Student, Department of Biological Sciences, City Tech - Spring 2023
Classification of Normal versus Pneumonia from Chest X-ray Using an AI Model. Tassadit Lounes, Biomedical Informatics (B.S.) Student, Department of Biological Sciences, City Tech - Spring 2023
A Deep Learning Model for Detection of Alzheimer's Disease Based on MRI Images. WintPyae LynnHtaik, Biomedical Informatics (B.S.) Student, Department of Biological Sciences, City Tech - Spring 2023
Deep Learning-Based Detection of Breast Cancer Using Pathology Images. Anastasiya Sytina, Biomedical Informatics (B.S.) Student, Department of Biological Sciences, City Tech - Fall 2023
Automated Breast Tumor Segmentation in Ultrasound Images Using U-Net Algorithm. Elijah Zuniga, Biomedical Informatics (B.S.) Student, Department of Biological Sciences, City Tech - Fall 2023
Deep Learning Classification of Gastrointestinal Images. Nora Zougari, Biomedical Informatics (B.S.) Student, Department of Biological Sciences, City Tech - Fall 2023
Exploring a Breast Cancer Dataset: Analysis of Mass and Calcification Information. Victoria Jeter, Biomedical Informatics (B.S.) Student, Department of Biological Sciences, City Tech - Fall 2023
Classifying EEG Signals of Schizophrenia Using Neural Networks. Princess Jones, Biomedical Informatics (B.S.) Student, Department of Biological Sciences, City Tech - Fall 2023
Office Hours
You are welcome to visit me in person during my office hours every Thursday from 9 AM to 5 PM. My office is located in the Academic Complex, specifically in room A-502D. To ensure that I can provide you with my full attention and assistance, please schedule an appointment via email before your visit.
Every Thursday, as the clock ticks from 9 AM to 5 PM, my door opens not just to inquiries, but to dreams, ambitions, and the shared journey of discovery. Bear in mind, no question is too small, no idea too ambitious. In this room, we weave the fabric of our future, stitch by stitch, together. Let this time be your canvas, your voice the brush, as we paint the pathways to your success. Here, in the heart of collaboration, we find not just answers, but inspiration, courage, and a community that believes in the beauty of your dreams. Let's make each moment count, for it's in these hours that the seeds of tomorrow's breakthroughs are sown.
Social Media
LinkedIn is my sole social media presence. I invite you to follow me there to stay connected. Here is the link to my LinkedIn profile.
⭐ Within every data point lies a heartbeat, a story waiting to be told. As we unravel the mysteries of the medical world, remember, our work is not just about algorithms and codes; it's about the lives we touch, the futures we shape, and the silent thank-yous whispered in the corridors of healing. Let's embark on this journey not just as students of science, but as architects of hope. Together, we can turn the impossible into the inevitable, one discovery at a time. Keep dreaming, keep discovering, for the next heartbeat could be the rhythm of change.