diff --git a/Search/ExponentialSearch.js b/Search/ExponentialSearch.js
new file mode 100644
index 000000000..d866ed5d8
--- /dev/null
+++ b/Search/ExponentialSearch.js
@@ -0,0 +1,61 @@
+/*
+ * Exponential Search
+ *
+ * The algorithm consists of two stages. The first stage determines a 
+ * range in which the search key would reside if it were in the list. 
+ * In the second stage, a binary search is performed on this range.
+ * 
+ *
+ *  
+ */
+
+function binarySearch(arr, x, floor, ceiling) {
+    // Middle index
+    let mid = Math.floor((floor + ceiling) / 2);
+
+    // If value is at the mid position return this position
+    if (arr[mid] === x) {
+        return mid;
+    }
+
+    if(floor > ceiling) return -1;
+
+    // If the middle element is great than the value 
+    // search the left part of the array
+    if (arr[mid] > value) {
+        return binarySearch(arr, value, floor, mid - 1);
+        //If the middle element is lower than the value
+        //search the right part of the array
+    } else {
+        return binarySearch(arr, value, mid + 1, ceiling);
+    }
+
+
+}
+
+
+function exponentialSearch(arr, length, value) {
+    // If value is the first element of the array return this position 
+    if (arr[0] == value) {
+        return 0;
+    }
+
+    // Find range for binary search 
+    let i = 1;
+    while (i < length && arr[i] <= value) {
+        i = i * 2;
+    }
+
+    // Call binary search for the range found above 
+    return binarySearch(arr, value, i / 2, Math.min(i, length));
+}
+
+let arr = [2, 3, 4, 10, 40, 65 , 78 , 100];
+let value = 78;
+let result = exponentialSearch(arr, arr.length, value);
+
+if (result < 0) {
+    console.log("Element not found");
+} else {
+    console.log("Element found at position :" + result);
+}
diff --git a/Search/InterpolationSearch.js b/Search/InterpolationSearch.js
new file mode 100644
index 000000000..f9a54bf60
--- /dev/null
+++ b/Search/InterpolationSearch.js
@@ -0,0 +1,49 @@
+/*
+ * Interpolation Search
+ *  
+ * Time Complexity:
+ * -Best case: O(1)
+ * -Worst case: O(n)
+ * -O((log(log(n))) If the data are uniformly distributed
+ *
+ *  
+ */
+
+function interpolationSearch(arr, key) {
+
+    let length = arr.length - 1;
+    let low = 0;
+    let high = length;
+    let position = -1;
+    let delta = -1;
+
+    //Because the array is sorted the key must be between low and high
+    while (low <= high && key >= arr[low] && key <= arr[high]) {
+
+        delta = (key - arr[low]) / (arr[high] - arr[low]);
+        position = low + Math.floor((high - low) * delta);
+
+        //Target found return its position
+        if (arr[position] === key) {
+            return position;
+        }
+
+        //If the key is larger then it is in the upper part of the array
+        if (arr[position] < key) {
+            low = position + 1;
+            //If the key is smaller then it is in the lower part of the array    
+        } else {
+            high = position - 1;
+        }
+    }
+
+    return -1;
+}
+
+
+let arr = [2, 6, 8, 10, 12, 14, 16, 18, 20, 22, 26, 34, 39];
+
+console.log("Found at position :" + interpolationSearch(arr, 2));
+console.log("Found at position :" + interpolationSearch(arr, 12));
+console.log("Found at position :" + interpolationSearch(arr, 1000));
+console.log("Found at position :" + interpolationSearch(arr, 39));
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