diff --git a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
index e73df61c964341..7aa8a0b37c219c 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
@@ -1086,6 +1086,76 @@ struct FoldReshapeWithGenericOpByExpansion
 private:
   ControlFusionFn controlFoldingReshapes;
 };
+
+/// Pattern to bubble up a tensor.expand_shape op through a producer
+/// tensor.collapse_shape op that has non intersecting reassociations.
+struct BubbleUpExpandThroughParallelCollapse
+    : public OpRewritePattern<tensor::ExpandShapeOp> {
+  using OpRewritePattern<tensor::ExpandShapeOp>::OpRewritePattern;
+
+  LogicalResult matchAndRewrite(tensor::ExpandShapeOp expandOp,
+                                PatternRewriter &rewriter) const override {
+    auto collapseOp =
+        expandOp.getSrc().getDefiningOp<tensor::CollapseShapeOp>();
+    if (!collapseOp || !collapseOp->hasOneUse())
+      return failure();
+    auto expandReInds = expandOp.getReassociationIndices();
+    auto collapseReInds = collapseOp.getReassociationIndices();
+
+    // Reshapes are parallel to each other if none of the reassociation indices
+    // have greater than 1 index for both reshapes.
+    for (auto [expandReassociation, collapseReassociation] :
+         llvm::zip_equal(expandReInds, collapseReInds)) {
+      if (collapseReassociation.size() != 1 && expandReassociation.size() != 1)
+        return failure();
+    }
+
+    // Compute new reassociation indices and expanded/collaped shapes.
+    SmallVector<ReassociationIndices> newExpandReInds, newCollapseReInds;
+    Location loc = expandOp->getLoc();
+    SmallVector<OpFoldResult> collapseSizes =
+        tensor::getMixedSizes(rewriter, loc, collapseOp.getSrc());
+    SmallVector<OpFoldResult> expandSizes(getMixedValues(
+        expandOp.getStaticOutputShape(), expandOp.getOutputShape(), rewriter));
+    SmallVector<OpFoldResult> newExpandSizes;
+    int64_t index = 0, expandIndex = 0, collapseIndex = 0;
+    for (auto [idx, collapseReassociation] : llvm::enumerate(collapseReInds)) {
+      if (collapseReassociation.size() != 1) {
+        ReassociationIndices newCollapseReassociation;
+        for (size_t i = 0; i < collapseReassociation.size(); ++i) {
+          newCollapseReassociation.push_back(index);
+          newExpandReInds.push_back({index++});
+          newExpandSizes.push_back(collapseSizes[collapseIndex++]);
+        }
+        newCollapseReInds.push_back(newCollapseReassociation);
+        expandIndex++;
+        continue;
+      }
+      ReassociationIndices newExpandReassociation;
+      auto expandReassociation = expandReInds[idx];
+      for (size_t i = 0; i < expandReassociation.size(); ++i) {
+        newExpandReassociation.push_back(index);
+        newCollapseReInds.push_back({index++});
+        newExpandSizes.push_back(expandSizes[expandIndex++]);
+      }
+      newExpandReInds.push_back(newExpandReassociation);
+      collapseIndex++;
+    }
+
+    // Swap reshape order.
+    SmallVector<Value> dynamicSizes;
+    SmallVector<int64_t> staticSizes;
+    dispatchIndexOpFoldResults(newExpandSizes, dynamicSizes, staticSizes);
+    auto expandResultType = expandOp.getResultType().clone(staticSizes);
+    auto newExpand = rewriter.create<tensor::ExpandShapeOp>(
+        loc, expandResultType, collapseOp.getSrc(), newExpandReInds,
+        newExpandSizes);
+    rewriter.replaceOpWithNewOp<tensor::CollapseShapeOp>(
+        expandOp, newExpand.getResult(), newCollapseReInds);
+    return success();
+  }
+};
+
 } // namespace
 
 //===---------------------------------------------------------------------===//
@@ -2083,6 +2153,7 @@ void mlir::linalg::populateFoldReshapeOpsByExpansionPatterns(
                                                         controlFoldingReshapes);
   patterns.add<FoldWithProducerReshapeOpByExpansion>(patterns.getContext(),
                                                      controlFoldingReshapes);
+  patterns.add<BubbleUpExpandThroughParallelCollapse>(patterns.getContext());
 }
 
 void mlir::linalg::populateFoldReshapeOpsByCollapsingPatterns(
diff --git a/mlir/test/Dialect/Linalg/reshape_fusion.mlir b/mlir/test/Dialect/Linalg/reshape_fusion.mlir
index b8df5fc88e1999..86c2904218385c 100644
--- a/mlir/test/Dialect/Linalg/reshape_fusion.mlir
+++ b/mlir/test/Dialect/Linalg/reshape_fusion.mlir
@@ -887,3 +887,37 @@ func.func @fuse_by_expanding_dynamic_pad(%arg0 : tensor<?x?x?x?x?x?xi32>, %l0: i
 //      CHECK:   %[[COLLAPSE:.+]] = tensor.collapse_shape %[[PAD]] {{\[}}[0], [1, 2], [3], [4, 5]]
 // CHECK-SAME:       : tensor<?x?x?x?x?x?xi32> into tensor<?x?x?x?xi32>
 //      CHECK:   return %[[COLLAPSE]]
+
+// -----
+
+func.func @bubble_parallel_reshapes(%arg0: tensor<?x?x?x?xf32>, %s0: index, %s1: index, %s2: index, %s3: index) -> tensor<?x?x?x?xf32> {
+  %collapse = tensor.collapse_shape %arg0 [[0], [1, 2], [3]] : tensor<?x?x?x?xf32> into tensor<?x?x?xf32>
+  %expand = tensor.expand_shape %collapse [[0], [1], [2, 3]]
+              output_shape [%s0, %s1, %s2, %s3] : tensor<?x?x?xf32> into tensor<?x?x?x?xf32>
+  return %expand : tensor<?x?x?x?xf32>
+}
+//      CHECK: func @bubble_parallel_reshapes
+// CHECK-SAME:   %[[ARG0:.+]]: tensor<?x?x?x?xf32>
+// CHECK-SAME:   %[[S0:.+]]: index, %[[S1:.+]]: index, %[[S2:.+]]: index, %[[S3:.+]]: index
+//  CHECK-DAG:   %[[C1:.+]] = arith.constant 1 : index
+//  CHECK-DAG:   %[[C2:.+]] = arith.constant 2 : index
+//  CHECK-DAG:   %[[DIM1:.+]] = tensor.dim %[[ARG0]], %[[C1]] : tensor<?x?x?x?xf32>
+//  CHECK-DAG:   %[[DIM2:.+]] = tensor.dim %[[ARG0]], %[[C2]] : tensor<?x?x?x?xf32>
+//      CHECK:   %[[EXPAND:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0], [1], [2], [3, 4]]
+// CHECK-SAME:       output_shape [%[[S0]], %[[DIM1]], %[[DIM2]], %[[S2]], %[[S3]]] : tensor<?x?x?x?xf32> into tensor<?x?x?x?x?xf32>
+//      CHECK:   %[[COLLAPSE:.+]] = tensor.collapse_shape %[[EXPAND]] {{\[}}[0], [1, 2], [3], [4]] : tensor<?x?x?x?x?xf32> into tensor<?x?x?x?xf32>
+//      CHECK:   return %[[COLLAPSE]]
+
+// -----
+
+func.func @no_bubble_intersecting_reshapes(%arg0: tensor<?x?x?x?xf32>, %s0: index, %s1: index, %s2: index, %s3: index) -> tensor<?x?x?x?xf32> {
+  %collapse = tensor.collapse_shape %arg0 [[0], [1, 2], [3]] : tensor<?x?x?x?xf32> into tensor<?x?x?xf32>
+  %expand = tensor.expand_shape %collapse [[0], [1, 2], [3]]
+              output_shape [%s0, %s1, %s2, %s3] : tensor<?x?x?xf32> into tensor<?x?x?x?xf32>
+  return %expand : tensor<?x?x?x?xf32>
+}
+//      CHECK: func @no_bubble_intersecting_reshapes
+// CHECK-SAME:   %[[ARG0:.+]]: tensor<?x?x?x?xf32>
+//      CHECK:   %[[COLLAPSE:.+]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0], [1, 2], [3]]
+//      CHECK:   %[[EXPAND:.+]] = tensor.expand_shape %[[COLLAPSE]] {{\[}}[0], [1, 2], [3]]
+//      CHECK:   return %[[EXPAND]]