diff --git a/Project.toml b/Project.toml
index 7af4146..54c3a99 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,8 +1,13 @@
 name = "ModelOrderReduction"
 uuid = "207801d6-6cee-43a9-ad0c-f0c64933efa0"
-authors = ["Bowen S. Zhu"]
+authors = ["Bowen S. Zhu", "Rahul Manavalan"]
 version = "0.1.0"
 
+[deps]
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+RandomizedLinAlg = "0448d7d9-159c-5637-8537-fd72090fea46"
+TSVD = "9449cd9e-2762-5aa3-a617-5413e99d722e"
+
 [compat]
 julia = "1.6"
 
@@ -10,4 +15,4 @@ julia = "1.6"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test"]
+test = ["Test"]
\ No newline at end of file
diff --git a/examples/POD/lorenz.jl b/examples/POD/lorenz.jl
new file mode 100644
index 0000000..e32cec8
--- /dev/null
+++ b/examples/POD/lorenz.jl
@@ -0,0 +1,39 @@
+using ModelOrderReduction
+using Plots
+using OrdinaryDiffEq
+
+function lorenz_prob()
+    function lorenz!(du, u, p, t)
+        du[1] = p[1] * (u[2] - u[1])
+        du[2] = u[1] * (p[2] - u[3]) - u[2]
+        du[3] = u[1] * u[2] - p[3] * u[3]
+    end
+
+    u0 = [1, 0, 0]
+    p = [10, 28, 8 / 3]
+    tspan = (0, 100)
+    prob = ODEProblem(lorenz!, u0, tspan, p)
+    sol = solve(prob, Tsit5())
+    sol
+end
+
+sol = lorenz_prob()
+solution = Array(sol)
+plot(solution[1, :], solution[2, :], solution[3, :])
+# savefig("lorenz_attractor.png")
+
+## Two way POD
+reducer = POD(solution, 2)
+reduce!(reducer, SVD())
+bases = reducer.rbasis
+plot(bases[:, 1], bases[:, 2], label = "POD2")
+# savefig("pod2.png")
+
+## One way POD
+reducer = POD(solution, 1)
+reduce!(reducer, SVD())
+bases = reducer.rbasis
+plot(bases[:, 1], label = "POD1")
+# savefig("pod1.png")
+plot(solution[:, 3], label = 'z')
+# savefig("z.png")
diff --git a/src/DataReduction/POD.jl b/src/DataReduction/POD.jl
new file mode 100644
index 0000000..7c7dfce
--- /dev/null
+++ b/src/DataReduction/POD.jl
@@ -0,0 +1,68 @@
+function matricize(VoV::Vector{Vector{FT}}) where {FT}
+    Matrix(reduce(hcat, VoV))
+end
+
+mutable struct POD{FT} <: AbstractDRProblem
+    snapshots::Union{Vector{Vector{FT}}, Matrix{FT}}
+    nmodes::Int
+    rbasis::Matrix{FT}
+    renergy::FT
+
+    function POD(snaps::Vector{Vector{FT}}, nmodes::Int) where {FT}
+        errorhandle(matricize(snaps), nmodes)
+        new{eltype(snaps[1])}(snaps, nmodes, Array{FT, 2}(undef, size(snaps, 1), nmodes),
+                              FT(0))
+    end
+
+    function POD(snaps::Matrix{FT}, nmodes::Int) where {FT}
+        errorhandle(snaps, nmodes)
+        new{eltype(snaps)}(snaps, nmodes, Array{FT, 2}(undef, size(snaps, 1), nmodes),
+                           FT(0))
+    end
+
+    function POD(snaps::Adjoint{FT, Matrix{FT}}, nmodes::Int) where {FT}
+        POD(Matrix(snaps), nmodes, Array{FT, 2}(undef, size(snaps, 1), nmodes), FT(0))
+    end
+end
+
+function reduce!(pod::POD{FT}, ::SVD) where {FT}
+    op_matrix = pod.snapshots
+    if typeof(pod.snapshots) == Vector{Vector{FT}}
+        op_matrix = matricize(pod.snapshots)
+    end
+    u, s, v = svd(op_matrix)
+    pod.rbasis .= u[:, 1:(pod.nmodes)]
+    sr = s[1:(pod.nmodes)]
+    pod.renergy = sum(s) / (sum(s) + (size(op_matrix, 1) - pod.nmodes) * s[end])
+    nothing
+end
+
+function reduce!(pod::POD{FT}, ::TSVD) where {FT}
+    op_matrix = pod.snapshots
+    if typeof(pod.snapshots) == Vector{Vector{FT}}
+        op_matrix = matricize(pod.snapshots)
+    end
+    u, s, v = tsvd(op_matrix, pod.nmodes)
+    pod.renergy = sum(s) / (sum(s) + (size(op_matrix, 1) - pod.nmodes) * s[end])
+    pod.rbasis .= u
+    nothing
+end
+
+function reduce!(pod::POD{FT}, ::RSVD) where {FT}
+    op_matrix = pod.snapshots
+    if typeof(pod.snapshots) == Vector{Vector{FT}}
+        op_matrix = matricize(pod.snapshots)
+    end
+    u, s, v = rsvd(op_matrix, pod.nmodes)
+    pod.renergy = sum(s) / (sum(s) + (size(op_matrix, 1) - pod.nmodes) * s[end])
+    pod.rbasis .= u
+    nothing
+end
+
+function Base.show(io::IO, pod::POD)
+    print(io, "POD \n")
+    print(io, "Reduction Order = ", pod.nmodes, "\n")
+    print(io, "Snapshot size = (", size(pod.snapshots, 1), ",", size(pod.snapshots[1], 2),
+          ")\n")
+    print(io, "Relative Energy = ", pod.renergy, "\n")
+end
diff --git a/src/ErrorHandle.jl b/src/ErrorHandle.jl
new file mode 100644
index 0000000..acba209
--- /dev/null
+++ b/src/ErrorHandle.jl
@@ -0,0 +1,5 @@
+function errorhandle(data::Matrix{FT}, modes::IT) where {FT, IT}
+    @assert size(data, 1)>1 "State vector is expected to be vector valued."
+    s = size(data, 2)
+    @assert (modes > 0)&(modes < s) "Number of modes should be in {1,2,...,$(s-1)}."
+end
diff --git a/src/ModelOrderReduction.jl b/src/ModelOrderReduction.jl
index 5ae21ae..c94ac26 100644
--- a/src/ModelOrderReduction.jl
+++ b/src/ModelOrderReduction.jl
@@ -1,5 +1,17 @@
 module ModelOrderReduction
+#========================Data Reduction=========================================#
+include("Types.jl")
+include("ErrorHandle.jl")
 
-# Write your package code here.
+using LinearAlgebra
+using TSVD
+using RandomizedLinAlg
 
+include("DataReduction/POD.jl")
+
+export SVD, TSVD, RSVD
+export POD, reduce!, matricize
+#========================Model Reduction========================================#
+
+#===============================================================================#
 end
diff --git a/src/Types.jl b/src/Types.jl
new file mode 100644
index 0000000..d877a07
--- /dev/null
+++ b/src/Types.jl
@@ -0,0 +1,8 @@
+abstract type AbstractReductionProblem end
+abstract type AbstractMORProblem <: AbstractReductionProblem end
+abstract type AbstractDRProblem <: AbstractReductionProblem end
+
+abstract type AbstractSVD end
+struct SVD <: AbstractSVD end
+struct TSVD <: AbstractSVD end
+struct RSVD <: AbstractSVD end
diff --git a/test/DataReduction.jl b/test/DataReduction.jl
new file mode 100644
index 0000000..e177d89
--- /dev/null
+++ b/test/DataReduction.jl
@@ -0,0 +1,59 @@
+#--------- Data Reduction -----------------#
+
+function lorenz_prob()
+    function lorenz!(du, u, p, t)
+        du[1] = p[1] * (u[2] - u[1])
+        du[2] = u[1] * (p[2] - u[3]) - u[2]
+        du[3] = u[1] * u[2] - p[3] * u[3]
+    end
+
+    u0 = [1, 0, 0]
+    p = [10, 28, 8 / 3]
+    tspan = (0, 100)
+    prob = ODEProblem(lorenz!, u0, tspan, p)
+    sol = solve(prob, Tsit5())
+    sol
+end
+
+@testset "POD-Utils" begin
+    solution = lorenz_prob()
+    VoV = solution.u
+    M = matricize(VoV)
+    @test size(M, 1) == length(VoV[1]) # Parameters
+    @test size(M, 2) == length(VoV) # Time
+end
+
+@testset "POD - Attractor Test" begin
+    sol = lorenz_prob()
+    solution = Array(sol)
+
+    order = 2
+    solver = SVD()
+    reducer = POD(solution, order)
+    reduce!(reducer, solver)
+
+    reducer.renergy
+
+    # Ad-hoc tests. To be checked with Chris.
+    @test size(reducer.rbasis, 2) == reducer.nmodes
+    @test size(reducer.rbasis, 1) == size(solution, 1)
+    @test reducer.renergy > 0.9
+
+    order = 2
+    solver = TSVD()
+    reducer = POD(solution, order)
+    reduce!(reducer, solver)
+
+    # Ad-hoc tests. To be checked with Chris.
+    @test size(reducer.rbasis, 2) == reducer.nmodes
+    @test size(reducer.rbasis, 1) == size(solution, 1)
+
+    order = 2
+    solver = RSVD()
+    reducer = POD(solution, order)
+    reduce!(reducer, solver)
+
+    # Ad-hoc tests. To be checked with Chris.
+    @test size(reducer.rbasis, 2) == reducer.nmodes
+    @test size(reducer.rbasis, 1) == size(solution, 1)
+end
diff --git a/test/Project.toml b/test/Project.toml
new file mode 100644
index 0000000..9aaa105
--- /dev/null
+++ b/test/Project.toml
@@ -0,0 +1,3 @@
+[deps]
+OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
diff --git a/test/runtests.jl b/test/runtests.jl
index 1f356e7..434234f 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -1,6 +1,6 @@
 using ModelOrderReduction
 using Test
+using OrdinaryDiffEq
 
-@testset "ModelOrderReduction.jl" begin
-    # Write your tests here.
-end
+include("DataReduction.jl")
+#---------- Model Reduction ----------------#