diff --git a/.circleci/config.yml b/.circleci/config.yml
index 50c966fb3d..af2c5ea078 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -480,7 +480,7 @@ jobs:
         - checkout
         - run:           
             name: Install EvaDB package from GitHub repo and run tests
-            no_output_timeout: 40m # 40 minute timeout
+            no_output_timeout: 30m # 30 minute timeout
             command: |
               python -m venv test_evadb
               source test_evadb/bin/activate
diff --git a/evadb/executor/create_function_executor.py b/evadb/executor/create_function_executor.py
index 773e0b94bc..9488195927 100644
--- a/evadb/executor/create_function_executor.py
+++ b/evadb/executor/create_function_executor.py
@@ -423,7 +423,6 @@ def handle_forecasting_function(self):
                 AutoNHITS,
                 AutoPatchTST,
                 AutoTFT,
-                AutoTimesNet,
             )
 
             # from neuralforecast.auto import AutoAutoformer as AutoAFormer
@@ -436,7 +435,6 @@ def handle_forecasting_function(self):
                 FEDformer,
                 Informer,
                 PatchTST,
-                TimesNet,
             )
 
             # from neuralforecast.models import Autoformer as AFormer
@@ -456,8 +454,6 @@ def handle_forecasting_function(self):
                 # "AutoAFormer": AutoAFormer,
                 "Informer": Informer,
                 "AutoInformer": AutoInformer,
-                "TimesNet": TimesNet,
-                "AutoTimesNet": AutoTimesNet,
                 "TFT": TFT,
                 "AutoTFT": AutoTFT,
             }
@@ -546,7 +542,7 @@ def get_optuna_config(trial):
                 raise FunctionIODefinitionError(err_msg)
 
             model = StatsForecast(
-                [model_here(season_length=season_length)], freq=new_freq, n_jobs=-1
+                [model_here(season_length=season_length)], freq=new_freq
             )
 
         data["ds"] = pd.to_datetime(data["ds"])
diff --git a/test/integration_tests/long/test_model_forecasting.py b/test/integration_tests/long/test_model_forecasting.py
index 76e5562357..d2f645ad7e 100644
--- a/test/integration_tests/long/test_model_forecasting.py
+++ b/test/integration_tests/long/test_model_forecasting.py
@@ -80,55 +80,55 @@ def tearDownClass(cls):
     @forecast_skip_marker
     def test_forecast(self):
         create_predict_udf = """
-            CREATE FUNCTION AirForecast FROM
-            (SELECT unique_id, ds, y FROM AirData)
+            CREATE FUNCTION AirPanelForecast FROM
+            (SELECT unique_id, ds, y, trend FROM AirDataPanel)
             TYPE Forecasting
             HORIZON 12
-            PREDICT 'y';
+            PREDICT 'y'
+            LIBRARY 'neuralforecast'
+            AUTO 'false'
+            FREQUENCY 'M';
         """
         execute_query_fetch_all(self.evadb, create_predict_udf)
 
         predict_query = """
-            SELECT AirForecast() order by y;
+            SELECT AirPanelForecast() order by y;
         """
         result = execute_query_fetch_all(self.evadb, predict_query)
-        self.assertEqual(len(result), 12)
+        self.assertEqual(len(result), 24)
         self.assertEqual(
             result.columns,
             [
-                "airforecast.unique_id",
-                "airforecast.ds",
-                "airforecast.y",
-                "airforecast.y-lo",
-                "airforecast.y-hi",
+                "airpanelforecast.unique_id",
+                "airpanelforecast.ds",
+                "airpanelforecast.y",
+                "airpanelforecast.y-lo",
+                "airpanelforecast.y-hi",
             ],
         )
 
         create_predict_udf = """
-            CREATE FUNCTION AirPanelForecast FROM
-            (SELECT unique_id, ds, y, trend FROM AirDataPanel)
+            CREATE FUNCTION AirForecast FROM
+            (SELECT unique_id, ds, y FROM AirData)
             TYPE Forecasting
             HORIZON 12
-            PREDICT 'y'
-            LIBRARY 'neuralforecast'
-            AUTO 'false'
-            FREQUENCY 'M';
+            PREDICT 'y';
         """
         execute_query_fetch_all(self.evadb, create_predict_udf)
 
         predict_query = """
-            SELECT AirPanelForecast() order by y;
+            SELECT AirForecast() order by y;
         """
         result = execute_query_fetch_all(self.evadb, predict_query)
-        self.assertEqual(len(result), 24)
+        self.assertEqual(len(result), 12)
         self.assertEqual(
             result.columns,
             [
-                "airpanelforecast.unique_id",
-                "airpanelforecast.ds",
-                "airpanelforecast.y",
-                "airpanelforecast.y-lo",
-                "airpanelforecast.y-hi",
+                "airforecast.unique_id",
+                "airforecast.ds",
+                "airforecast.y",
+                "airforecast.y-lo",
+                "airforecast.y-hi",
             ],
         )