One possible way to use quantum computing for conference scheduling is to formulate the problem as a quadratic unconstrained binary optimization (QUBO) problem, which is a type of problem that quantum computers can solve efficiently. A QUBO problem consists of finding the binary variables (0 or 1) that minimize a quadratic function, subject to some constraints. For example, you could assign a binary variable to each session-room-time slot combination, and define a quadratic function that measures the quality of the schedule, based on factors such as session relevance, speaker availability, room suitability, and attendee satisfaction. The constraints could be expressed as penalties in the quadratic function, such as adding a large cost for overlapping sessions or violating speaker preferences. Then, you could use a quantum algorithm, such as quantum annealing or quantum approximate optimization algorithm (QAOA), to find the binary variables that minimize the quadratic function, and thus produce the optimal or near-optimal schedule.