diff --git a/src/nb_ndarray.cpp b/src/nb_ndarray.cpp
index b2017fdf..6e746997 100644
--- a/src/nb_ndarray.cpp
+++ b/src/nb_ndarray.cpp
@@ -424,9 +424,12 @@ ndarray_handle *ndarray_import(PyObject *o, const ndarray_req *req,
         }
     }
 
+    bool refused_conversion = t.dtype.code == (uint8_t) dlpack::dtype_code::Complex &&
+                              req->dtype.code != (uint8_t) dlpack::dtype_code::Complex;
+
     // Support implicit conversion of 'dtype' and order
     if (pass_device && pass_shape && (!pass_dtype || !pass_order) && convert &&
-        capsule.ptr() != o) {
+        capsule.ptr() != o && !refused_conversion) {
         PyTypeObject *tp = Py_TYPE(o);
         str module_name_o = borrow<str>(handle(tp).attr("__module__"));
         const char *module_name = module_name_o.c_str();
diff --git a/tests/test_ndarray.cpp b/tests/test_ndarray.cpp
index e1ef5ed6..0820cf30 100644
--- a/tests/test_ndarray.cpp
+++ b/tests/test_ndarray.cpp
@@ -296,4 +296,13 @@ NB_MODULE(test_ndarray_ext, m) {
         else
             return Ret(nb::ndarray<nb::numpy, int, nb::shape<>>(i_global, 0, nullptr));
     });
+
+    // issue #365
+    m.def("set_item", [](nb::ndarray<double, nb::ndim<1>, nb::c_contig> data, uint32_t) {
+        data(0) = 123;
+    });
+    m.def("set_item",
+          [](nb::ndarray<std::complex<double>, nb::ndim<1>, nb::c_contig> data, uint32_t) {
+            data(0) = 123;
+          });
 }
diff --git a/tests/test_ndarray.py b/tests/test_ndarray.py
index 195bf405..1bd1bab0 100644
--- a/tests/test_ndarray.py
+++ b/tests/test_ndarray.py
@@ -632,3 +632,15 @@ def test34_complex_decompose():
 
     assert np.all(x1.real == np.array([1, 3, 5], dtype=np.float32))
     assert np.all(x1.imag == np.array([2, 4, 6], dtype=np.float32))
+
+@needs_numpy
+@pytest.mark.parametrize("variant", [1, 2])
+def test_uint32_complex_do_not_convert(variant):
+    if variant == 1:
+        arg = 1
+    else:
+        arg = np.uint32(1)
+    data = np.array([1.0 + 2.0j, 3.0 + 4.0j])
+    t.set_item(data, arg)
+    data2 = np.array([123, 3.0 + 4.0j])
+    assert np.all(data == data2)