Imran portrait
đź‘‹

Hey, I'm Imran Iqbal, an enthusiastic Research Scientist based in Germany and USA 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 leverage 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

Logo

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
Logo

Postdoctoral Researcher

Helmholtz-Zentrum Hereon, Germany

Job Description: High-resolution Imaging and Computational Analysis to Study the Dynamics of Stem Cell-Biomaterial Interaction.

2021 - 2024
Logo

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.

2016
Logo

Research 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
Logo

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.

2012

My education

Logo

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.

2021
Logo

Master 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
Logo

Master of Information Technology

Isra University, Pakistan

CGPA: 3.85/4.00

Dissertation: An Improved Numerical Technique for the Solution of Integration.

2007
Logo

Bachelor of Computer and Information Technology

University of Sindh, Pakistan

CGPA: 3.57/4.00

Dissertation: Artificial Intelligence, Expert Systems, and Data Structures.

2003

My honors

Logo

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
Logo

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
Logo

Outstanding International Students 2020

Ministry of Education, China

Description: I earned the award and grant for the Best International Student of 2020 in China.

2020
Logo

International 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.

2020
Logo

Chinese 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.

2016

My skills

My projects

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

Contact me

Please contact me directly at imraniqbalrajput@hotmail.com; imran.iqbal@nyulangone.org or through this form.