diff --git a/graph/johnson.ts b/graph/johnson.ts
new file mode 100644
index 00000000..7eac28ac
--- /dev/null
+++ b/graph/johnson.ts
@@ -0,0 +1,52 @@
+import { bellmanFord } from './bellman_ford'
+import { dijkstra } from './dijkstra'
+
+/**
+ * @function johnson
+ * @description Compute the shortest path for all pairs of nodes. The input graph is in adjacency list form. It is a multidimensional array of edges. graph[i] holds the edges for the i'th node. Each edge is a 2-tuple where the 0'th item is the destination node, and the 1'th item is the edge weight. Returned undefined if the graph has negative weighted cycles.
+ * @Complexity_Analysis
+ * Time complexity: O(VElog(V))
+ * Space Complexity: O(V^2) to hold the result
+ * @param {[number, number][][]} graph - The graph in adjacency list form
+ * @return {number[][]} - A matrix holding the shortest path for each pair of nodes. matrix[i][j] holds the distance of the shortest path (i -> j).
+ * @see https://en.wikipedia.org/wiki/Johnson%27s_algorithm
+ */
+export const johnson = (graph: [number, number][][]): number[][] | undefined => {
+  let N = graph.length;
+
+  // Add a new node and 0 weighted edges from the new node to all existing nodes.
+  let newNodeGraph = structuredClone(graph);
+  let newNode: [number, number][] = [];
+  for (let i = 0; i < N; ++i) {
+    newNode.push([i, 0]);
+  }
+  newNodeGraph.push(newNode);
+
+  // Compute distances from the new node to existing nodes using the Bellman-Ford algorithm.
+  let adjustedGraph = bellmanFord(newNodeGraph, N);
+  if (adjustedGraph === undefined) {
+    // Found a negative weight cycle.
+    return undefined;
+  }
+
+  for (let i = 0; i < N; ++i) {
+    for (let edge of graph[i]) {
+      // Adjust edge weights using the Bellman Ford output weights. This ensure that:
+      // 1. Each weight is non-negative. This is required for the Dijkstra algorithm.
+      // 2. The shortest path from node i to node j consists of the same nodes with or without adjustment.
+      edge[1] += adjustedGraph[i] - adjustedGraph[edge[0]];
+    }
+  }
+
+  let shortestPaths: number[][] = [];
+  for (let i = 0; i < N; ++i) {
+    // Compute Dijkstra weights for each node and re-adjust weights to their original values.
+    let dijkstraShorestPaths = dijkstra(graph, i);
+    for (let j = 0; j < N; ++j) {
+      dijkstraShorestPaths[j] += adjustedGraph[j] - adjustedGraph[i];
+    }
+    shortestPaths.push(dijkstraShorestPaths);
+  }
+  return shortestPaths;
+}
+
diff --git a/graph/test/johnson.test.ts b/graph/test/johnson.test.ts
new file mode 100644
index 00000000..24600879
--- /dev/null
+++ b/graph/test/johnson.test.ts
@@ -0,0 +1,107 @@
+import { johnson } from "../johnson";
+
+describe("johnson", () => {
+
+  const init_graph = (N: number): [number, number][][] => {
+    let graph = Array(N);
+    for (let i = 0; i < N; ++i) {
+      graph[i] = [];
+    }
+    return graph;
+  }
+
+  const add_edge = (graph: [number, number][][], a: number, b: number, weight: number) => {
+    graph[a].push([b, weight]);
+    graph[b].push([a, weight]);
+  }
+
+  it("should return the correct value", () => {
+    let graph = init_graph(9);
+    add_edge(graph, 0, 1, 4);
+    add_edge(graph, 0, 7, 8);
+    add_edge(graph, 1, 2, 8);
+    add_edge(graph, 1, 7, 11);
+    add_edge(graph, 2, 3, 7);
+    add_edge(graph, 2, 5, 4);
+    add_edge(graph, 2, 8, 2);
+    add_edge(graph, 3, 4, 9);
+    add_edge(graph, 3, 5, 14);
+    add_edge(graph, 4, 5, 10);
+    add_edge(graph, 5, 6, 2);
+    add_edge(graph, 6, 7, 1);
+    add_edge(graph, 6, 8, 6);
+    add_edge(graph, 7, 8, 7);
+
+    let expected = [
+      [0, 4, 12, 19, 21, 11, 9, 8, 14],
+      [4, 0, 8, 15, 22, 12, 12, 11, 10],
+      [12, 8, 0, 7, 14, 4, 6, 7, 2],
+      [19, 15, 7, 0, 9, 11, 13, 14, 9],
+      [21, 22, 14, 9, 0, 10, 12, 13, 16],
+      [11, 12, 4, 11, 10, 0, 2, 3, 6],
+      [9, 12, 6, 13, 12, 2, 0, 1, 6],
+      [8, 11, 7, 14, 13, 3, 1, 0, 7],
+      [14, 10, 2, 9, 16, 6, 6, 7, 0]
+    ]
+    expect(johnson(graph)).toStrictEqual(expected);
+  });
+
+  it("should return the correct value for graph with negative weights", () => {
+    let graph = init_graph(4);
+    graph[0].push([1, -5]);
+    graph[0].push([2, 2]);
+    graph[0].push([3, 3]);
+    graph[1].push([2, 4]);
+    graph[2].push([3, 1]);
+
+    let expected = [
+      [ 0, -5, -1, 0 ],
+      [ Infinity, 0, 4, 5 ],
+      [ Infinity, Infinity, 0, 1 ],
+      [ Infinity, Infinity, Infinity, 0 ]
+    ]
+    expect(johnson(graph)).toStrictEqual(expected);
+  });
+
+  it("should return the undefined for two node graph with negative-weight cycle", () => {
+    let graph = init_graph(2);
+    add_edge(graph, 0, 1, -1);
+    expect(johnson(graph)).toStrictEqual(undefined);
+  });
+
+  it("should return the undefined for three node graph with negative-weight cycle", () => {
+    let graph = init_graph(3);
+    graph[0].push([1, -1]);
+    graph[0].push([2, 7]);
+    graph[1].push([2, -5]);
+    graph[2].push([0, 4]);
+    expect(johnson(graph)).toStrictEqual(undefined);
+  });
+
+  it("should return the correct value for zero element graph", () => {
+    expect(johnson([])).toStrictEqual([]);
+  });
+
+  it("should return the correct value for single element graph", () => {
+    expect(johnson([[]])).toStrictEqual([[0]]);
+  });
+
+  it("should return the correct value for a linear graph", () => {
+    let linear_graph = init_graph(4);
+    add_edge(linear_graph, 0, 1, 1);
+    add_edge(linear_graph, 1, 2, 2);
+    add_edge(linear_graph, 2, 3, 3);
+
+    let expected = [[0, 1, 3, 6 ], [1, 0, 2, 5], [3, 2, 0, 3], [6, 5, 3, 0]];
+    expect(johnson(linear_graph)).toStrictEqual(expected);
+  });
+
+  it("should return the correct value for a linear graph with unreachable node", () => {
+    let linear_graph = init_graph(3);
+    add_edge(linear_graph, 0, 1, 1);
+
+    let expected = [[0, 1, Infinity], [1, 0, Infinity], [Infinity, Infinity, 0]];
+    expect(johnson(linear_graph)).toStrictEqual(expected);
+  });
+})
+