Hey, I'm Imran Iqbal, an enthusiastic Research Scientist based in USA and Germany with a passion for advancing healthcare through cutting-edge technology. My primary research focus lies in the dynamic field of Deep Learning for Medical Image Analysis. With a strong foundation in Machine Learning and a commitment to improving patient care, I utilize the power of Artificial Intelligence (AI) to develop innovative solutions for the interpretation and diagnosis of medical images. My work strives to bridge the gap between Technology & Healthcare, ultimately aiming to enhance the accuracy and efficiency of medical diagnoses. Join me on my journey as we explore the limitless potential of AI in transforming the landscape of medical imaging and ushering in a new era of healthcare excellence.
My experience
Postdoctoral Fellow
New York University Langone Health, USA
Job Description: Applying Machine Learning Approaches to Aid in the Classification and Prediction of Clinical Outcomes in Human Cancers using Digital Images.
2024 - present
Research Assistant
Helmholtz-Zentrum Hereon, Germany
Job Description: High-resolution Imaging and Computational Analysis to Study the Dynamics of Stem Cell-Biomaterial Interaction.
2021 - 2024
Teaching Assistant
Air University, Pakistan
Job Description: Help professors in delivering lectures, conducting lab sessions, and facilitating discussions. Responsible for grading assignments, quizzes, and exams. Hold regular office hours where students can seek help, ask questions, and discuss course material. Support instructors to develop course materials, including lecture slides, assignments, and assessment tools.
2016Research Assistant
Air University, Pakistan
Job Description: I worked on project associated to Energy Saving in Buildings in Pakistan sponsored through Higher Education Commission (HEC) Social Integration Outreach Program.
2015
Software Engineer
County Cambridge School, Pakistan
Job Description: Assisting in the testing and debugging of software to identify and resolve errors. Helping to maintain and update existing software by making small changes, adding new features, or addressing reported issues. Collaborating with other team members to complete tasks, troubleshoot issues, and understand the software development process. Supporting with quality assurance testing, ensuring that software functions correctly and meets specified requirements.
2012My education
Doctor of Natural Science in Applied Mathematics
Peking University, China
CGPA: 4.00/4.00
Dissertation: Deep Learning to Medical Images for Classification and Detection tasks; To identify lesions or abnormalities, I utilized Magnetic Resonance Imaging, Photomicrographs, Dermoscopic images, and Endoscopy images.
2021Master of Science in Mathematical Modeling and Scientific Computing
Air University, Pakistan
CGPA: 3.80/4.00
Dissertation: Cost Effective Net Zero Energy Home in Karachi Climate.
2014
Master of Information Technology
Isra University, Pakistan
CGPA: 3.85/4.00
Dissertation: An Improved Numerical Technique for the Solution of Integration.
2007
Bachelor of Computer and Information Technology
University of Sindh, Pakistan
CGPA: 3.57/4.00
Dissertation: Artificial Intelligence, Expert Systems, and Data Structures.
2003My honors
Helmholtz Visiting Research Grant
Helmholtz-Zentrum Hereon to Helmholtz Munich, Germany
Description: The Helmholtz Information & Data Science Academy (HIDA) Trainee Network funding is awarded by the HIDA to the most qualified information and data scientists of the Helmholtz Association and its partner institutions. I received this grant for Electron Microscopy Dataset for Mitochondria Segmentation project.
2022
Innovation Information Biologisation (I2B)
Germany
Description: I2B Funds for Postdoc Project (High-resolution Imaging and Computational Analysis to Study the Dynamics of Stem Cell-Biomaterial Interaction)
2021
Outstanding International Students 2020
Ministry of Education, China
Description: I earned the award and grant for the Best International Student of 2020 in China.
2020International Students Excellence Award 2020
Peking University, China
Description: I received the award for the Best International Student of 2020 at Peking University. This prestigious award also included a financial grant.
2020Chinese Government Scholarship
Peking University, China
Description: I was awarded a five-year China Scholarship Council (CSC) fellowship for a Ph.D. program (Doctor of Natural Science in Applied Mathematics) at the School of Mathematical Sciences.
2016My skills
- ANSYS
- ASP
- ASP.net
- C/C++
- Cool Edit Pro
- Electronic Work Bench
- EnergyPlus
- Ecotect
- FORTRAN
- FeatFlow
- JavaScript
- Java
- Julia
- Keras
- Maple
- MATLAB
- OpenCV
- Prolog
- Python
- R
- Rational Rose
- RATScreen
- Revit
- Ruby
- SQL
- Simulink
- SketchUp
- SAM
- SPSS
- Scikit-learn
- TensorFlow
- TRNSYS
- UML
- VB Script
- VB6
- VB.net
- XML
My projects
Substrates mimicking the blastocyst geometry revert pluripotent stem cell to naivety
Naive pluripotent stem cells, transient in the blastocyst, can be reverted in vitro using a blastocyst motif substrate. This substrate enhances E-cadherin/RAC1 signaling and YAP activation, increasing NANOG levels. Cultured cells show improved developmental potential, advancing substrate design for promoting stem cell naivety and large-scale applications
- Blastocyst Motif Substrate
- E-cadherin/RAC1 Signaling
- Naive Pluripotent Stem Cells
- Pluripotency Reversion
- YAP Activation
An end-to-end deep convolutional neural network-based data-driven fusion framework for identification of human induced pluripotent stem cell-derived endothelial cells in photomicrographs
This study introduces a deep convolutional neural network for classifying human induced pluripotent stem cell-derived endothelial cells from photomicrographs. The framework employs diverse convolutional modules, pooling layers, and activation functions, optimizing efficiency with fewer trainable parameters. A labeled dataset of 16,278 images supports future research in cell biology.
- Endothelial cells
- Human induced pluripotent stem cells
- Image processing
- Information fusion
- Machine learning
- Photomicrograph
Deep learning-based automated detection of human knee joint's synovial fluid from magnetic resonance images with transfer learning
The main aim of this study is to apply the deep learning model to detect the synovial fluid of human knee joint from magnetic resonance images. Two independent datasets are introduced in the training, development, and evaluation of the proposed model.
- COCO Dataset
- Deep Learning
- Human Knee Joint
- MRI
- Radiologists
- Synovial Fluid
Deep Learning-Based Morphological Classification of Human Sperm Heads
A specialized convolutional neural network architecture to accurately classify human sperm heads based on sperm images is proposed. It is carefully designed with several layers, and multiple filter sizes, but fewer filters and parameters to improve efficiency.
- DCNN
- Embryologists
- Infertility
- Microscopic Images
- Sperm Morphology
Automated multi-class classification of skin lesions through deep convolutional neural network with dermoscopic images
The main objective of this research is to develop, implement, and calibrate an advanced deep learning model in the context of automated multi-class classification of skin lesions. This proposed approach provides a novel and feasible way for automating and expediting the skin lesion classification task as well as saving effort, time, and human life.
- Deep Learning
- Dermatologists
- Dermoscopic Images
- ISIC-19 dataset
- Skin Cancer
Automated identification of human gastrointestinal tract abnormalities based on deep convolutional neural network with endoscopic images
Automated identification of gastrointestinal abnormalities with endoscopic images is a challenging task even for experienced gastroenterologists which could greatly aid medical diagnosis and reduce the time and cost of investigational procedures. Nonetheless, in medical diagnosis, the human gastrointestinal tract findings are manually determined, and greatly depend on the prowess of the gastrointestinal endoscopist.
- DCNN
- Endoscopists
- Gastrointestinal Diseases
- Kvasir dataset
- Wire & capsule endoscopy
My Editorial Activities
I'm also actively engaged in editorship.
Peer Reviewer
Peer Reviewer
I serve as a Peer Reviewer for more than 50 esteemed journals, including the following:
My Gallery
Grateful moment: Receiving an award at the International Conference on Modeling and Simulation for my contributions and achievements in the field.
Engaging in the World Robot Conference at Etrong International Exhibition and Convention Center—a captivating exploration of cutting-edge robotics and innovation
Competing in the exhilarating squash tournament in Beijing—an unforgettable experience on the court
Helmholtz AI Conference, Deutschen Elektronen-Synchrotron, Hamburg, Germany
Contact me
Please contact me directly at imraniqbalrajput@hotmail.com; imran.iqbal@nyulangone.org or through this form.