diff --git a/nums/core/array/application.py b/nums/core/array/application.py
index ea9d85ed..48654617 100644
--- a/nums/core/array/application.py
+++ b/nums/core/array/application.py
@@ -19,9 +19,11 @@
 
 import opt_einsum as oe
 import numpy as np
+import sparse
 
 from nums.core.array import utils as array_utils
 from nums.core.array.blockarray import BlockArray, Block
+from nums.core.array.sparse import SparseBlockArray
 from nums.experimental.zarrgroup import ZarrGroup
 from nums.core.array.random import NumsRandomState
 from nums.core.kernel.kernel_manager import KernelManager
@@ -228,8 +230,8 @@ def loadtxt(
     def scalar(self, value):
         return BlockArray.from_scalar(value, self.km)
 
-    def array(self, array: Union[np.ndarray, List[float]], block_shape: tuple = None):
-        if not isinstance(array, np.ndarray):
+    def array(self, array: Union[np.ndarray, sparse.COO, List[float]], block_shape: tuple = None):
+        if not isinstance(array, (np.ndarray, sparse.COO)):
             if array_utils.is_array_like(array):
                 array = np.array(array)
             else:
@@ -237,9 +239,14 @@ def array(self, array: Union[np.ndarray, List[float]], block_shape: tuple = None
                     "Unable to instantiate array from type %s" % type(array)
                 )
         assert len(array.shape) == len(block_shape)
-        return BlockArray.from_np(
-            array, block_shape=block_shape, copy=False, km=self.km
-        )
+        if isinstance(array, np.ndarray):
+            return BlockArray.from_np(
+                array, block_shape=block_shape, copy=False, km=self.km
+            )
+        else:
+            return SparseBlockArray.from_sparse(
+                array, block_shape=block_shape, copy=False, km=self.km
+            )
 
     def zeros(self, shape: tuple, block_shape: tuple, dtype: np.dtype = None):
         return self._new_array("zeros", shape, block_shape, dtype)
diff --git a/nums/core/array/sparse.py b/nums/core/array/sparse.py
index b12c6f2d..fb71b0bd 100644
--- a/nums/core/array/sparse.py
+++ b/nums/core/array/sparse.py
@@ -285,6 +285,25 @@ def from_np(cls, arr, block_shape, copy, km, fill_value=0):
             rarr.blocks[grid_entry].dtype = getattr(np, dtype_str)
         return rarr
 
+    @classmethod
+    def from_sparse(cls, arr, block_shape, copy, km, fill_value=0):
+        dtype_str = str(arr.dtype)
+        grid = ArrayGrid(arr.shape, block_shape, dtype_str)
+        rarr = SparseBlockArray(grid, km, fill_value)
+        grid_entry_iterator = grid.get_entry_iterator()
+        for grid_entry in grid_entry_iterator:
+            grid_slice = grid.get_slice(grid_entry)
+            block = arr[grid_slice]
+            if copy:
+                block = sparse.COO.copy(block)
+            # TODO: generalize for different kernels
+            rarr.blocks[grid_entry].oid = km.put(
+                block,
+                syskwargs={"grid_entry": grid_entry, "grid_shape": grid.grid_shape},
+            )
+            rarr.blocks[grid_entry].dtype = getattr(np, dtype_str)
+        return rarr
+
     @classmethod
     def from_scalar(cls, val, km):
         if not array_utils.is_scalar(val):
diff --git a/nums/core/settings.py b/nums/core/settings.py
index 37369b46..cc6357c2 100644
--- a/nums/core/settings.py
+++ b/nums/core/settings.py
@@ -76,7 +76,6 @@
 # and converting back to the original block shape.
 doctest_fallbacks = {
     "argwhere",
-    "asscalar",
     "clip",
     "compress",
     "convolve",
diff --git a/nums/numpy/api/creation.py b/nums/numpy/api/creation.py
index 4633c0ce..a76e815c 100644
--- a/nums/numpy/api/creation.py
+++ b/nums/numpy/api/creation.py
@@ -16,6 +16,7 @@
 
 import warnings
 import numpy as np
+import sparse
 
 from nums.core.application_manager import instance as _instance
 from nums.core.array.blockarray import BlockArray
@@ -225,6 +226,15 @@ def array(object, dtype=None, copy=True, order="K", ndmin=0, subok=False) -> Blo
     return app.array(result, block_shape)
 
 
+def from_coo(a: sparse.COO):
+    assert(isinstance(a, sparse.COO))
+    dtype = np.__getattribute__(str(a.dtype))
+    shape = a.shape
+    app = _instance()
+    block_shape = app.compute_block_shape(shape, dtype)
+    return app.array(a, block_shape)
+
+
 def copy(a: BlockArray, order="K", subok=False):
     """Return an array copy of the given object.
 
diff --git a/tests/core/array/test_sparse.py b/tests/core/array/test_sparse.py
index febf6b4d..4ef9bc06 100644
--- a/tests/core/array/test_sparse.py
+++ b/tests/core/array/test_sparse.py
@@ -13,11 +13,24 @@ def test_sparse_init(app_inst: ArrayApplication):
     x_ba = app_inst.array(x1, block_shape=(2, 2))
     x_sba = SparseBlockArray.from_ba(x_ba, fill_value=0)
     assert x_sba.nnz == 8
-    assert x_sba.nbytes == 8 * 8 + 2 * 8 * 8
+    assert x_sba.nbytes == 8 * 4 + 2 * 8 * 8
     y_ba = x_sba.to_ba()
     assert np.array_equal(x1, y_ba.get())
 
 
+def test_from_coo(app_inst: ArrayApplication):
+    row_coords = [0, 1, 0, 1, 2, 2, 3, 3]
+    col_coords = [3, 2, 2, 3, 0, 1, 0, 1]
+    values     = [1, 1, 1, 1, 2, 2, 2, 2]
+    x_sp = sparse.COO([row_coords, col_coords], values)
+    x_de = x_sp.todense()
+    x_sba = app_inst.array(x_sp, block_shape=(2, 2))
+    assert x_sba.nnz == 8
+    assert x_sba.nbytes == 8 * 4 + 2 * 8 * 8
+    y_ba = x_sba.to_ba()
+    assert np.array_equal(x_de, y_ba.get())
+
+
 def test_sparse_random(app_inst: ArrayApplication):
     rs: NumsRandomState = app_inst.random_state(1337)
     x_sba = rs.sparse_randint(
@@ -185,6 +198,8 @@ def test_sdtd(app_inst):
     import conftest
 
     app_inst = conftest.get_app("serial")
+    test_from_coo(app_inst)
+    test_sparse_init(app_inst)
     test_sdtp(app_inst)
     # test_sdtd(app_inst)
     # test_sparse_init(app_inst)