This is my report on: Rank adjustment strategies for Dynamic PageRank (v1). While doing research work under Prof. Dip Banerjee, Prof. Kishore Kothapalli. Abstract — To avoid calculating ranks of vertices in a dynamic graph from scratch for every snapshot, the ones computed in the previous snapshot of the graph can be used, with adjustment. Four different rank adjustment strategies for dynamic PageRank are studied here. These include zero-fill, 1/N-fill, scaled zero-fill, and scaled 1/N-fill. Results indicate that the scaled 1/N-fill strategy requires the least number of iterations, on average. As long as the graph has no affected dead ends (including dead ends in the previous snapshot), unaffected vertices can be skipped with this adjustment strategy. Index terms — PageRank algorithm, Dynamic graph, Rank adjustment, Initial ranks.