diff --git a/src/Initialization/init_Symbolics.jl b/src/Initialization/init_Symbolics.jl
index 7daf003e7b..bfd23ea741 100644
--- a/src/Initialization/init_Symbolics.jl
+++ b/src/Initialization/init_Symbolics.jl
@@ -1,5 +1,4 @@
-using .Symbolics: gradient,
-                  simplify,
+using .Symbolics: simplify,
                   Num,  # variable like, e.g. x[1]
                   Term, # term like, eg. x[1] + x[2] == 1
                   Symbolic,
diff --git a/src/Sets/HPolyhedron/HPolyhedron.jl b/src/Sets/HPolyhedron/HPolyhedron.jl
index f716637a0e..2f9e565e92 100644
--- a/src/Sets/HPolyhedron/HPolyhedron.jl
+++ b/src/Sets/HPolyhedron/HPolyhedron.jl
@@ -111,7 +111,7 @@ function load_symbolics_hpolyhedron()
                     end
                 end
 
-                coeffs = [N(α.val) for α in gradient(sexpr, vars_list)]
+                coeffs = [N(α.val) for α in Symbolics.gradient(sexpr, vars_list)]
                 β = -N(Symbolics.substitute(sexpr, zeroed_vars))
 
                 push!(clist, HalfSpace(coeffs, β))
diff --git a/src/Sets/HalfSpace.jl b/src/Sets/HalfSpace.jl
index b0d6b6c614..404dec5559 100644
--- a/src/Sets/HalfSpace.jl
+++ b/src/Sets/HalfSpace.jl
@@ -627,7 +627,7 @@ function load_symbolics_halfspace()
             end
 
             # compute the linear coefficients by taking first-order derivatives
-            coeffs = [N(α.val) for α in gradient(sexpr, collect(vars))]
+            coeffs = [N(α.val) for α in Symbolics.gradient(sexpr, collect(vars))]
 
             # get the constant term by expression substitution
             zeroed_vars = Dict(v => zero(N) for v in vars)
diff --git a/src/Sets/Hyperplane.jl b/src/Sets/Hyperplane.jl
index cd1b713e02..e87285d782 100644
--- a/src/Sets/Hyperplane.jl
+++ b/src/Sets/Hyperplane.jl
@@ -596,7 +596,7 @@ function load_symbolics_hyperplane()
             end
 
             # compute the linear coefficients by taking first order derivatives
-            coeffs = [N(α.val) for α in gradient(sexpr, collect(vars))]
+            coeffs = [N(α.val) for α in Symbolics.gradient(sexpr, collect(vars))]
 
             # get the constant term by expression substitution
             zeroed_vars = Dict(v => zero(N) for v in vars)