Mohammad Arafat Hussain, PhD

✧ Integrated multimodal health data (EHRs, neuroimaging, genomics, clinical measures) to develop explainable AI models for patient outcome prediction, advancing core principles of health informatics. ✧ Published high-impact studies demonstrating accelerated brain aging in adolescents with congenital heart disease and predictive models linking cognitive outcomes with demographic, genetic, and imaging features. ✧ Secured and led American Heart Association funding (Grant 919799; 2022–2023) as Principal Investigator, introducing transfer learning frameworks that leveraged large population datasets (N > 16,000) to improve prediction accuracy in small clinical cohorts (N < 100). ✧ Developed the Relational Connectivity Transformer, a novel graph-based architecture that outperformed existing models in predicting cognitive outcomes from neuroimaging data, demonstrating innovation in graph-based deep learning for healthcare. ✧ Contributing to NIH-funded initiatives (Grant OS00000958; 2024–2025) on clinical data integration and outcome modeling, with results directly applicable to health informatics education and scalable healthcare technology.

Offering strategic consulting and mentorship for students, researchers, and professionals pursuing graduate education or research careers in the U.S. and Canada. Services: ✧ Graduate admissions consulting (program selection, SOP, CV, interview prep) ✧ Research project planning and scientific writing ✧ AI and data science guidance for academic or biomedical research ✰ Successfully supported applicants in securing admissions and research opportunities at institutions including Harvard, UBC, McGill, and other top North American universities.

✧ Advanced interpretable machine learning for healthcare, developing explainable radiomic feature extraction methods that improved the assessment of organ function. ✧ Designed active learning pipelines that reduced expert annotation requirements in clinical AI systems, lowering manual labeling effort and accelerating deployment in real-world medical imaging. ✧ Co-developed learning-to-augment strategies that enhanced deep learning performance for COVID-19 detection and mental health prediction, demonstrating translational impact in public health surveillance. ✧ Collaborated across interdisciplinary teams of computer scientists, clinicians, and public health experts to ensure model interpretability and adoption in clinical workflows. ✧ Contributed to peer-reviewed publications and international conferences, strengthening the visibility of explainable AI in healthcare and population health informatics.

📚 Ph.D. Program: ✧ Conducted research in kidney abnormality detection in CT images using machine learning 📚 M.A.Sc. Program: ✧ Conducted research on medical ultrasound-guided orthopedic surgery procedures ✧ Addressed the challenges of bone segmentation in 2D and 3D ultrasound images ✧ Developed better algorithms for more accurate bone boundary delineation

✍️ Responsibilities: ✧ Administering the BiSICL website and internal Wiki. ✧ In charge of purchasing and maintenance of lab computers.

✍️ Responsibilities: ✧ Invigilating the examinations ✧ Helping students in office hours ✧ Marking the assignments ✧ Marking exam scripts 🖍 Courses taught: 📘 CPSC 340: Machine Learning and Data Mining 📘 APSC 160: Introduction to Computation in Engineering Design

✍️ Responsibilities: ✧ Preparing tutorial lectures and teaching the class ✧ Invigilating the examinations ✧ Demonstrating in the laboratory sessions ✧ Marking exam scripts 🖍 Courses taught: 📘 EECE 269: Signals and Systems (January 2014) 📘 EECE 360: Systems and Control (September 2014) 📘 EECE 380: Electrical Engineering Design Studio (January 2015) 📘 CPEN 312: Digital Systems and Microcomputers (January 2016, 2017, 2018) 📘 CPEN/ELEC 481: Economic Analysis of Engineering Projects (May 2016) 📘 ELEC 221: Signals and Systems (September 2016, September 2017, 2018, 2019) 📘 APSC 160: Introduction to Computation in Engineering Design (May 2017, 2018, 2019, September 2017, January 2018) 📘 ELEC 211: Engineering Electromagnetics (January 2019)

✍️ Responsibilities: ✧ Acting as the president when the president is absent ✧ Coordinating the communication of the ECEGSA ✧ Keeping the minutes of meetings and make them available to the membership ✧ Acting as the auxiliary administrator of the ECEGSA bank account with signing authority as defined in the ECEGSA financial policy

✍️ Responsibilities: ✧ Calling meetings of the ECEGSA ✧ Chairing meetings on the ECEGSA ✧ Acting as an auxiliary administrator of the ECEGSA bank account with signing authority

✍️ Responsibilities: ✧ Taught three major electrical engineering courses in the undergraduate level ✧ Taught three laboratory courses in the undergraduate level ✧ Prepared the assessment tools and marked the exam scripts 🖍 Courses taught: 📘 EEE 431: Microprocessor and Interfacing 📘 EEE 432: Microprocessor and Interfacing Laboratory 📘 EEE 353: Measurement and Instrumentation 📘 EEE 354: Measurement and Instrumentation Laboratory 📘 EEE 433: Solid State Devices 📘 EEE 340: Electronic Project Design

✍️ Responsibilities: ✧ Developed database software for patient' information management ✧ Trained a group of 20 physicians on how to use the database software

✍️ Responsibilities: ✧ Developed techniques for ultrasound-based strain imaging and tissue attenuation estimation ✧ Worked as a key member in a World Bank funded project ✧ Organized a national-level workshop for physicians on ultrasound-based elastography