diff --git a/Project.toml b/Project.toml
index 7af36c4e58..0db429253d 100644
--- a/Project.toml
+++ b/Project.toml
@@ -10,6 +10,7 @@ AdvancedPS = "576499cb-2369-40b2-a588-c64705576edc"
 AdvancedVI = "b5ca4192-6429-45e5-a2d9-87aec30a685c"
 BangBang = "198e06fe-97b7-11e9-32a5-e1d131e6ad66"
 Bijectors = "76274a88-744f-5084-9051-94815aaf08c4"
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DistributionsAD = "ced4e74d-a319-5a8a-b0ac-84af2272839c"
diff --git a/src/inference/Inference.jl b/src/inference/Inference.jl
index 73f190dcc6..1969f7fc95 100644
--- a/src/inference/Inference.jl
+++ b/src/inference/Inference.jl
@@ -23,6 +23,7 @@ using AbstractMCMC: AbstractModel, AbstractSampler
 using DocStringExtensions: TYPEDEF, TYPEDFIELDS
 using DataStructures: OrderedSet
 using Setfield: Setfield
+using CSV
 
 import AbstractMCMC
 import AdvancedHMC; const AHMC = AdvancedHMC
@@ -249,7 +250,7 @@ function AbstractMCMC.sample(
     chain_type=MCMCChains.Chains,
     progress=PROGRESS[],
     kwargs...
-)
+)   
     return AbstractMCMC.mcmcsample(rng, model, sampler, ensemble, N, n_chains;
                                    chain_type=chain_type, progress=progress, kwargs...)
 end
@@ -488,6 +489,23 @@ end
 # Utilities  #
 ##############
 
+function SaveCSV(rng::AbstractRNG,
+    model::DynamicPPL.Model,
+    sampler::DynamicPPL.Sampler,
+    transition::HMCTransition,
+    state::HMCState,
+    iteration::Int64;
+    kwargs...
+)
+    vii = deepcopy(state.vi)
+    DynamicPPL.invlink!!(vii, model)
+    θ = vii[sampler]
+    # it would be good to have the param names as in the chain
+    chain_name = get(kwargs, :chain_name, "chain")
+    CSV.write(string(chain_name,".csv"), Dict("params"=>[θ]);
+              append=true, delim=";")
+end
+
 DynamicPPL.getspace(spl::Sampler) = getspace(spl.alg)
 DynamicPPL.inspace(vn::VarName, spl::Sampler) = inspace(vn, getspace(spl.alg))
 
diff --git a/src/inference/hmc.jl b/src/inference/hmc.jl
index 5ba3831481..39b131a042 100644
--- a/src/inference/hmc.jl
+++ b/src/inference/hmc.jl
@@ -100,7 +100,7 @@ function AbstractMCMC.sample(
     discard_adapt=true,
     discard_initial=-1,
     kwargs...
-)
+)          
     if resume_from === nothing
         # If `nadapts` is `-1`, then the user called a convenience
         # constructor like `NUTS()` or `NUTS(0.65)`,