10completed
completed
peer reviews
Across five journals in AI, biomedical engineering, robotics, and electrical engineering.
View journals
Includes completed review rounds · September 2026
PhD student · Wright State University
Computer Science · Dayton, Ohio
Making AI
worth trusting.
I study how medical AI fails beyond the benchmark—and how better evaluation and structured knowledge can make it more reliable.
100+Citations
13Published + accepted
10Completed peer reviews
Medical imaging.
Reliable ML.
Knowledge engineering.
01 / SELECTED RESEARCHGood accuracy is
Good accuracy is
only the beginning.
Five connected studies of what models learn, how they transfer, and when their confidence breaks.
02 / THE EVIDENCE DESK
Explore the results.
Research findings you can inspect.
Every study links back to its source.
03 / PUBLICATIONS
Full Google Scholar profile The written record.
04 / THE RESEARCHERCuriosity,
Curiosity,
with a method.
I’m a Computer Science PhD student at Wright State University, advised by Dr. Cogan Shimizu.
My work connects medical AI evaluation with knowledge engineering. I’m interested in models whose evidence, confidence, and assumptions can be examined—not just their final score.
Education, experience & full CV ↗Research is a practice.
Selected training in data science, AI for healthcare, and peer review.
LET’S CONNECTBetter questions.
Better questions.
More reliable AI.
Open to research conversations and collaborations in trustworthy AI, medical imaging, and knowledge engineering.
skrakibulislamrahat@gmail.comA little curiosity is allowed.