Leading experts in inverse problems have joined forces to produce a new edition of the definitive reference that allows readers to understand, implement, and benefit from a variety of problem-solving techniques. The focus of most of the work in this new edition is on parabolic and elliptic problems typified by transient and steady-state heat conduction; however, the scope of application extends to any mathematically similar problems (in chemical transport, mass transfer, etc.) As well as revision to existing chapters, this second edition includes four new chapters: a new chapter on the classis Tikhonov regularization technique, a new chapter on the topic of filter coefficient concepts for linear problems, a chapter dedicated to Bayesian solution of inverse problems, and finally a new chapter on machine learning and artificial intelligence. Anyone interested in inverse problems, regardless of their specialty, will find the Inverse Engineering Handbook to be a unique and invaluable compendium of up-to-date techniques.