OpenAImer

OpenAImer is the flagship Machine Learning event of SRIJAN’26, designed to test participants on real-world data-driven problem solving. This competition challenges participants to build robust and efficient machine learning models across multiple problem tracks. Participants will work on structured datasets, develop predictive models, and optimize performance based on defined evaluation metrics. The event emphasizes both technical implementation and the ability to clearly communicate solutions. The competition consists of two rounds — an online qualifying stage followed by an offline final round. Event Format: Machine Learning competition with multiple problem tracks Participants must attempt all tracks Evaluation based on model performance and overall approach Final round includes solution presentation and evaluation by judges Rules & Guidelines: Participants must attempt both problem tracks in the prelims Shortlisting will be based on combined performance across tracks Only shortlisted participants will advance to the final round Finalists must present their solutions to a judging panel Submissions must be original; plagiarism or unfair practices will lead to disqualification Participants must follow all instructions provided during the competition The decision of the organizing committee will be final and binding Eligibility: Open to all undergraduate and postgraduate students Individual participation or teams (if allowed by organizers; clarify if needed) Participants can register only once