Skip to: Main Content Search Navigation Secondary Navigation

Gary Weckman

Associate Professor
Industrial and Systems Engineering
STKR 275
weckmang@ohio.edu
Phone: 740.593.1548

https://sites.google.com/site/garyweckman/home

Before joining the Ohio University faculty in 2002 as an associate professor in Industrial and Systems Engineering, Dr. Weckman was a faculty member at Texas A&M University-Kingsville for six years. He has also practiced industrial engineering for more than 12 years at such firms as General Electric Aircraft Engines, Kenner Products and The Trane Company. During his varied career, he has had a number of different technical responsibilities, which involved developing and implementing various decision support and forecasting systems and techniques. He is currently living in Athens, Ohio, with his wife, Jan, and two children, Brad and Nick.


Research Interests: Artificial Neural Networks, Safety and Health Engineering, Decision Support, Intelligent Systems,

All Degrees Earned: Ph.D., Industrial Engineering, University of Cincinnati, 1996. M.E., Industrial Engineering, 1980, University of Louisville, Louisville, Kentucky B.S., Industrial Engineering, 1979, University of Louisville, Louisville, Kentucky

Publications:

William A. Young II, Gary R. Weckman, Maimuna H. Rangwala and Harry S. Whiting II, Helmut W. Paschold, Andrew H. Snow and Chad L. Mourning, An investigation of TREPAN utilising a continuous oracle model, Int. J. Data Analysis Techniques and Strategies, Vol. 3, No. 4, 2011 325-352.

Millie, D. F., Weckman, G. R., Young, W. A., Ivey, J. E. & Fahnenstiel, G. L. Submitted 6/2011. Modeling algal abundance with artificial neural networks: demonstration of a heuristic, ‘Grey-Box’ technique to deconvolve and quantify environmental influences. Environmental Modeling & Software

Young, W. A. II, Millie, D. F., Weckman, G. R., Anderson, J., Klarer, D. M., & Fahnenstiel, G. L. 2011. Modeling net ecosystem metabolism with an artificial neural network and a bayesian belief network. Environmental Modeling & Software 26: 1199-1210.

Millie, D. F., Fahnenstiel, G. L., Weckman, G. R., Klarer, D. M., Dyble Bressie, J., Vanderploeg, H. A., & Fishman, D. 2011. An ‘enviro-informatic’ assessment of Saginaw Bay (Lake Huron USA) phytoplankton: characterization and modeling of Microcystis (Cyanophyta). Journal of Phycology 47: 714-730.

Holland, W., Young, W., & Weckman, G. (2011) Facility RFID Localization System based on Artificial Neural Networks, International Journal of Industrial Engineering - Theory, Applications, and Practice (IJIETAP), Vol. 18. Iss. 1, pp. 16-24

Awards:

• 2010 Awarded IARIA Fellows is in recognition for:
* outstanding scientific research results endorsed by international peers
* exceptional scientific contribution to the IARIA events
* continuous leadership roles in IARIA conferences

• University of Louisville (UL) Professional Award in Engineering: an alumnus award for my dedication to students and understanding research. –2007

• Industrial and Systems Engineering Department Research Award - 2007

• Industrial and Systems Engineering Department Research Award - 2006

• University of Cincinnati: Finalist in the 1996 Graduate Assistant Teaching Award.

Journal Article, Academic Journal (32)

  • Young II, W., Nykl, S., Weckman, G., Chelberg, D. Using Voronoi diagrams to improve classification performances when modeling imbalanced datasets. Springer London: Neural Computing and Applications; 1-14. http://dx.doi.org/10.1007/s00521-014-1780-0.
  • Ardjmand, E., Weckman, G., Park, N., Taherkhani, P., Singh, M. Applying genetic algorithm to a new location and routing model of hazardous materials. International Journal of Production Research; 916-928.
  • Ardjmand, E., Park, N., Weckman, G., Amin-Naserib, M. The Discrete Unconscious Search and Its Application to Uncapacitated Facility Location Problem. Computers & Industrial Engineering; 73: 32-40.
  • Young II, W., Kinn, A., Weckman, G. The Implications of the NFL Scouting Combine. 2. International Journal of Sports Science and Engineering; 8.
  • Young II, W., Weckman, G. The Pythagorean Winning Percentage Formula Derived for the National Football League. 1. International Journal of Sports Science and Engineering; 8.
  • Millie, D., Weckman, G., Fahnenstiel, G., Carrick, H., Ardjmand, E., Young II, W., Sayers, M., Shuchman, R. Using artificial intelligence for CyanoHAB niche modeling: discovery and visualization of Microcytis-environmental associations within western Lake Erie. Canadian Journal of Fisheries & Aquatic Sciences.
  • Young II, W., Nykl, S., Weckman, G., Chelberg, D. Using Voronoi Diagrams to Improve Classification Performances when Modeling Imbalanced Datasets. Neural Computing and Applications.
  • Shyirambere, A., Snow, A., Arauz, J., Weckman, G. A Reliability and Survivability Analysis of US Local Telecommunication Switches. 3&4. International Journal On Advances in Telecommunications; 6.
  • Millie, D., Weckman, G., Young, W., Ivey, K., Fries, D., Ardjmand, E., Fahnenstiel, G. Coastal 'Big Data' and Nature-Inspired Computation.
  • Millie, D., Weckman, G., Young II, W., Ivey, J., Fries, D., Ardjmand, E., Fahnenstiel, G. Coastal 'big data' and nature-inspired computation: prediction potentials, uncertainties, and knowledge derivation of neural networks for an algal metric. Estuarine Coastal & Shelf Science; 125: 57-67.
  • Young, W., Young, R., Weckman, G. Improving an Internal Combustion Engine's Fuel Map through an Artificial Neural Network. International Journal of Decision Sciences.
  • Young, W., Weckman, G. The Pythagorean Winning Percentage Formula Derived for the National Football League. International Journal of Sports Science.
  • Weckman, G., Bondal, A., Rinder, M., Young, W. Applying a Hybrid Artificial Immune Systems to the Job Shop-Scheduling Problem. 7. Journal of Neural Computing and Applications; 21: 1465-1475.
  • Rinder, M., Weckman, G., Schwerha, D., Snow, A., Dreher, P., Park, N., Paschold, H., Young, W. Healthcare Scheduling by Data Mining, Literature Review and Future Directions. 3. Journal of Healthcare Engineering; 3: 477-502.
  • Millie, D., Weckman, G., Young, W., Ivey, J., Carrick, H., Fahnenstiel, G. Modeling Microalga Abundance with Artificial Neural Networks: Demonstration of a Heuristic, 'Grey-Box' Technique to Deconvolve and Quantify Environmental Influences. Environmental Modeling & Software; 37: 27-39.
  • Snow, A., Chen, Y., Weckman, G. The Impact of Multi-Outage Episodes on Large-Scale Wireless Voice Networks. 3 & 4 . International Journal on Advances in Networks and Services; 5: 174-188.
  • William, Y., Weckman, G., Hari, V., Whiting, H., Snow, A. Using Artificial Neural Networks to enhance CART. 7. Journal of Neural Computing and Applications; 21: 1477-1489.
  • Young II, W., Weckman, G., Holland, W. A Survey of the Methodologies for the Treatment of Missing Values with Datasets: Limitations and Benefits. 1. Theoreticals Issues in Ergonomics Science; 12: 15-43.
  • Millie, D., Fahnenstiel, G., Weckman, G., Klarer, G., Bressie, D., Vanderploeg, H., Fishman, D. An 'Enviro-informatic" assessment of Saginaw Bay (Lake Huron USA) Hytoplankton: Characterization and Modeling of Microcystis (Cyanophyta). Journal of Phycology; 47: 714-730.
  • Young II, W., Weckman, G., Rangwala, M., Whiting, H., Paschold, H., Snow, A., Mourning, C. An Investigation of TREPAN Utilizing a Continuous Oracle Model. 4. International Journal of Data Analysis Techniques and Strategies; 3: 325-352.
  • Holland, W., Young II, W., Weckman, G. Facility RFID Localization System based on Artificial Neural Networks. 1. International Journal of Industrial Engineering-Theory, Applications, and Practice; 18: 16-24.
  • Young II, W., Millie, D., Weckman, G., Anderson, J., Klarer, D., Fahnenstiel, G. Modeling Net Ecosystem Metabolism with an Artificial Neural Network and Bayesian Belief Network. Environmental Modeling & Software; 26: 1199-1210.
  • Young, W., Weckman, G., Holland, W. A Survey of the Methodologies for the Treatment of Missing Values within Datasets: Limitations and Benefits. Theoretical Issues in Ergonomics Science.
  • Tuncel, S., Weckman, G., Genaidy, A., Kara, K. Assessment Tool for Engineering Labs in a University Setting: Development and Application. Journal of Safety Research.
  • Weckman, G., Paschold, H., Dowler, J., Whiting, H., Young, W. Using Neural Networks with Limited Data to Estimate Manufacturing Cost. Journal of Industrial and Systems Engineering.
  • Young, II, W., Kaya, S., Weckman, G. Learning Before Erring: A Brief Note on the Influence of Dielectric Materials to Pursue Moore’s Law. 2. International Journal of Industrial Engineering - Theory, Applications and Practice; 16: 91-98.
  • Young II, W., Weckman, G. Using a Heuristic Approach to Derive a Grey-box Model through an Artificial Neural Network Knowledge Extraction Technique. 3. Journal of Neural Computing and Applications; 19: 353-366.
  • Young, II, W., Holland, W., Weckman, G. Determining Hall of Fame Status for Major League Baseball using an Artificial Neural Network. 4. Journal of Quantitative Analysis in Sports; 4.
  • Young, II, W., Weckman, G. Evaluating the Effects of Aging for Professional Football Players in Combine Events using Performance-aging Curves. 03. International Journal of Sports Science and Engineering; 02: 131-143.
  • Millie, D., Weckman, G., Paerl, H., Pinckney, J., Bendis, B., Pigg, R., Fahnenstiel, G. Neural Network Modeling of Estuarine Indicators: Hindcasting Phytoplankton Biomass and Net Ecosystem Production in the Neuse (North Carolina) and Trout (Florida) Rivers. Ecological Indicators; 6: 589-608.
  • Millie, D., Weckman, G., Pigg, R., Tester, P., Dyble, J., Litaker, R., Carrick, H., Fahnenstiel, G. Modeling Phytoplankton Abundance in Saginaw Bay, Lake Huron: Using Artificial Neural Networks to Discern Functional Influence of Environmental Variables and Relevance to a Great Lakes Observing System. 2. Journal of Phycology; 42.
  • Weckman, G., Shell, R., Marvel, J. Modeling the Reliability of Repairable Systems in the Aviation Industry. 1-2. Computers in Industrial Engineering; 40: 51-63.

Book, Chapter in Scholarly Book (2)

  • Young, W., Bihl, T., Weckman, G. Artificial Neural Networks for Business: A Starting Point. 1st Edition. IGI Global.
  • Bihl, T., Young, W., Weckman, G. Decision Support Systems for Business: A Starting Point. 1st Edition. IGI Global.

Journal Article, Professional Journal (14)

  • Weckman, G., Young, II, W., Hernandez, S., Rangwala, M., Ghai, V. Extracting Knowledge from Carbon Dioxide Corrosion Inhibition with Artificial Neural Networks. International Journal of Industrial Engineering - Theory, Applications and Practice.
  • Weckman, G., Rangwala, M., Millie, D., Ganduri, C., Young, II, W. Knowledge Extraction from the Black Box in Ecological Monitoring.
  • Young, II, W., Weckman, G., Kara, K. Learning before Erring: The Infulence of Dielectric Materials to Pursue Moore's Law. International Journal of Industrial Engineering - Theory, Applications and Practice.
  • Maudgalya, T., Genaidy, A., Weckman, G., Shell, R., Karwowski, W., Wallace, S. A Critical Appraisal of Epidemiological Studies Investigating the Effects of Ultrafine Particles on Human Health. 3. Human Factors and Ergonomics in Manufacturing; 18: 358-373.
  • Weckman, G., Ganduri, C., Koonce, D. A Neural Network Job-Shop Scheduler Based on Knowledge Extraction from a Genetic Algorithm. 2. Journal of Intelligent Manufacturing; 19: 191-201.
  • Lakshminarayanan, S., Snow, A., Marvel, J., Weckman, G. An Integrated Stock Market Forecasting Model Using Neural Networks. 1. International Journal of Business Froecasting and Marketing Intelligence ; 1.
  • Marvel, J., Schaub, M., Weckman, G. Assessing the Availability and Allocation of Production Capacity in a Fabrication Facility Through Simulation Modeling: A Case Study. International Journal of Industrial Engineering: Theory Applications and Practice.
  • Sequeira, R., Genaidy, A., Weckman, G., Shell, R., Karwowski, W., Acosta-Leon, A. Health Effects of Nanomaterials: A Critical Appraisal Approach and Research to Practice. 3. Human Factors and Ergonomics in Manufacturing; 18: 293-341.
  • Kara, K., Kothari, J., Genaidy, A., Weckman, G., Shell, R., Karwowski, W. The Factors Affecting Healthcare Costs in Manufacturing. 2. Human Factors and Ergonomics in Manufacturing; 18: 199-211.
  • Young, II, W., Weckman, G., Brown, M., Thompson, J. Extracting Knowledge of Concrete Shear Strength from Artificial Neural Networks. 1. International Journal of Industrial Engineering: Theory Applications and Practice; 15.
  • Sequeira, R., Genaidy, A., Shell, R., Karwowski, W., Weckman, G., Salem, S. The Nano Esterprise: A Survey of Health and Safety Concerns, Considerations and Proposed Improvement Strategies to Reduce Potential Adverse Effects. 4. Human Factors and Ergonomics in Manufacturing; 16: 343-368.
  • Hernandez, S., Nesic, S., Weckman, G., Ghai, V. Use of Artificial Neural Networks for Predicting Crude Oil Effect on CO2 Corrosion of Carbon Steels. 6. Corrosion Journal; 62.
  • Snow, A., Weckman, G., Chayanam, K. Modeling Telecommunication Outages due to Power Loss. 1. International Journal of Industrial Engineering: Theory Applications and Practice; 13.
  • Marvel, J., Shell, R., Weckman, G. An Application of Heuristic Algorithms for Determining Inventory Location in a Distribution Warehouse. 1. International Journal of Industrial Engineering: Theory Applications and Practice; 8: 5-15.

Conference Proceeding (47)

  • Kayaalp, N., Celikbilek, C., Weckman, G. Analytical Assessment of Highway Fatalities in United States: Frontier Approaches. Montreal: Industrial and Systems Engineering Research Conference.
  • Snow, A., Weckman, G. Trends in Local Telecommunication Switch Resiliency. Nice: Thirteenth International Conference on Networks.
  • Amin-Naseri, M., Ardjmand, E., Weckman, G. Training the Feedforward Neural Network Using Unconscious Search. IJCCN 2013 - International joint Conference on Neural Networks.
  • Snow, A., Arauz, J., Weckman, G., Shyirambere, A. A Reliability and Survivability Analysis of Local Telecommunication Switches Suffering Frequent Outages. Eleventh International Conference of Networks.
  • Snow, A., Weckman, G., Chen, A. Multi-Episodic Dependability Assessments for Large-Scale Networks. 10th International Conference on Networks.
  • Snow, A., Weckman, G., Gupta, V. Meeting SLA Availabiilty Guarantees through Engineering Margin. International Academy, Research and Industry Association (IARIA).
  • Young, R., Young, W., Weckman, G. Utilization of a Neural Network to Improve Fuel Maps of an Air-Cooled Internal Combustion Engine. Industrial Engineering Research Conference.
  • Weckman, G., Snow, A., Rastogi, P., Rangwala, M. Assessing Wireless Network Dependability through Knowledge Extraction via Decision Trees. International Academy, Research, and Industry Accociation: International Conference on Systems.
  • Young, II, W., Weckman, G. Performance Aging Curves: Modeling the Effects of Aging through a Rating System. IIE Annual Conference, 2008.
  • Young, II, W., Weckman, G. Treatment Methods for the Missing Value Problem: Benefits and Limitations. IIE Annual Conference, 2008.
  • Young, II, W., Weckman, G., Marvel, J. Generating Variable Relationships by Optimization Techniques through Sensitivity Analysis from a Neural Network. IIE Annual Conference, 2007.
  • Marvel, J., Schaub, M., Weckman, G. Integrating Simulation into the Redesign of a Capacity Planning Process. IIE Annual Conference, 2007.
  • Rangwala, M., Weckman, G., Marvel, J., Young, II, W. TREPAN-PLUS: An Extension of a Decision Tree Extration Algorithm Utilizing Artificial Neural Networks. St. Louis, MO: 2007 Artificial Neural Networks in Engineering Conference.
  • Young, II, W., Weckman, G. Output and Input Response Surfaces Generated from an Artificial Neural Network for an Empirical to Semi-Mechanistic Model: A Heuristic Approach. St. Louis, MO: 2007 Artificial Neural Networks in Engineering Conference.
  • Snow, A., Weckman, G. What are the Chances an Availability SLA will be Violated?. April. Sixth International Conference on Networking, IEEE; 35-50.
  • Bondal, A., Weckman, G. A Job Shop Scheduling Application Based on Artificial Immune Systems. Orlando, FL: 2006 IIE Annual Conference.
  • Rangwala, M., Weckman, G. Extracting Rules from Artificial neural Networks Utilizing TREPAN. Orlando, FL: 2006 IIE Annual Conference.
  • Lakshminarayanan, S., Weckman, G., Snow, A., Marvel, J. Stock Market Hybrid Forecasting Model Using Neural Networks. Orlando, FL: 2006 IIE Annual Conference.
  • Snow, A., Chatanyam, K., Weckman, G., Campbell, P. Power Related Network Outages: Impact, Triggering Events, and Root Causes. Vancouver, CA: 10th IEEE/IFIP network Operations and Management Symposium (NOMS 2006).
  • Weckman, G., Snow, A., Chatanyam, K., Campbell, P. Power Related Network Outages: Impact, Triggering Events, and Root Causes. Vancouver, CA: 10th IEEE/IFIP Netwrok Operations and Management Symposium 2006.
  • Marvel, J., Schaub, M., Weckman, G. Validating the Capacity Planning Process and Flowline Product Sequencing through Simulation Analysis. Orlando, FL: 2005 Winter Simulation Conference.
  • Weckman, G., Millie, D., Ghai, V., Ganduri, C. A Comparison of Knowledge Extraction Techniques from an Artificial Neural Network in Ecological Monitoring. St. Louis, MO: 2005 Artificial Neural Networks in Engineering Conference.
  • Snow, A., Rastogi, P., Weckman, G. Assessing Dependability of Wireless Networks using Neural Networks. Atlantic City, NJ: IEEE Military Communication Conference MILCOM 2005; 05CH37719C.
  • Weckman, G., Marvel, J. Forecasting Engine Removal Comparing Neural Network to a Hazard Model. Atlanta, GA: 2005 IIE Annual Conference.
  • Weckman, G., Lakshminarayanan, S. Identifying Effects of Low Sensitivity Indicators in a Stock Market Forecasting Model. St. Louis, MO: 2004 Artificial Neural Networks in Engineering Conference.
  • Weckman, G., Ganduri, C., Koonce, D. Rule Driven Job-Shop Derived from Neural Networks. St. Louis, MO: 2004 Artificial Neural Networks in Engineering Conference.
  • Weckman, G., Lakshminarayanan, S. Identifying Technical Indicators for Stock Market Prediction with Neural Networks. Houston, TX: 2004 IIE Annual Conference.
  • Whiting, H., Weckman, G. Reducing Cycle Time for a Restaurant Drive-Thru Simulation. Houston, TX: 2004 IIE Annual Conference.
  • Weckman, G., Lakshminarayanan, S. Short-Term Stock Forecasting Based on Neural Network Model Incorporating Fuzzy Logic and Fibonacci Ratios. St. Louis, MO: 2003 Artificial Neural Networks in Engineering Conference.
  • Weckman, G. A Conceptual Approach for Decision-Making in Reactive Scheduling. Columbus, OH: Group Technology/Cellular Manufacturing World Symposium 2003.
  • Weckman, G., Agarwala, R. Identifying Relative Contribution of Selected Technical Indicators in Stock Market Prediction. Portland, OR: 2003 IIE Annual Conference.
  • Weckman, G., Lakshminarayanan, S. Predicting Stock Market Trends Utilizing a Wavelet Driven Artificial Neural Network. Portland, OR: 2003 IIE Annual Conference.
  • Weckman, G., McLauchlan, R., Muniswamy, V. Benchmaking Student Performance in Engineering: A Potential Technique for Identifying Factors Affecting STudent Enrollment and Retention in Engineering Programs. American Society for Engineering Education Gulf Southwest Conference, 2002.
  • Weckman, G. A Framework for Reactive Scheduling in a Cellular Manufacturing Environment. St. Louis, MO: International Conference on Production Research Americas 2002.
  • Agarwala, R., Weckman, G., McLauchlan, R. Techniques to Optimize Data Collection and Training Time for Forecasting Stock Market Trends Using Artificial Neural Network. ST.Louis, MO: 2002 Artificial Neural Networks in Engineering Conference.
  • Weckman, G., Siddiqui, D. Selection of Engine Removal Data using Sensitivity Analysis to Predict Jet Engine Maintenance Removals with Neural Networks. St. Louis, MO: 2001 Artificial Neural Networks in Engineering.
  • Weckman, G., McLauchlan, R. Using Neural Networks to Predict Rainfall Patterns in South Texas. St. Louis, MO: 2001 Artificial Neural Networks in Engineering Conference.
  • Weckman, G., McLauchlan, R., Crosby, J. An Assessment and Evaluation of an Integrated Engineering Curriculum. Albuquerque, New Mexico: Annual ASEE 2001 Conference.
  • Weckman, G., Marvel, J., Shell, R. Forecasting Maintenance Requirements in Aviation Utilizing a Time Series Approach. Dallas, TX: IIE Annual Conference 2001.
  • Weckman, G., McLauchlan, R., Crosby, J. Web Page Design to Monitor Foundation Coalition and ABET 2000 Outcomes. College Station, TX: 2001 American Society for Engineering Education Gulf Southwest Conference.
  • Weckman, G., McLauchlan, R., Muniswamy, V. The Relevance of Assessment and Evaluation to Improving Student Retention in Engineering. Albuquerque, New Mexico: 2000 Annual American Society for Engineering Education Gulf Southwest Conference.
  • McLauchlan, R., Pallerla, S., Weckman, G., Velagaleti, V. Predicting Student Academic Success in the Engineering Curriculum at Texas A&M University - Kingsville Using Neural Networks. St. Louis, MO: 1999 Artificial Neural Networks in Engineering Conference; 9: 1183-1188.
  • Weckman, G., McLauchlan, R. Using Neural Networks to Forcast Jet Engine Removals for Restoration. St. Louis, MO: 1999 Artificial Neural Networks in Engineering Conference; 9: 1189-1194.
  • Marvel, J., Weckman, G. Utilizing Process Information to Dynamically Modify Kanban Sizes for Process Flow Control in a Manufacturing Assembly Cell. 8th Annual International Industrial Engineering Research Conference.
  • Marvel, J., Weckman, G. Analyzing the Effects of Applying an Aggregate TAKT Time for Process Flow Control. 7th Annual International Industrial Engineering Research Conference.
  • Weckman, G., Shell, R., Marvel, J. Modeling Jet Engine Life Distributions Based on Field Data. 7th Annual International Industrial Engineering Research Conference.
  • Weckman, G. CFM56-3 Maintenance Cost. Paris, France: All Operator Conference.

Journal Article, Public or Trade Journal (1)

  • Weckman, G., Marvel, J., Shell, R. A Decision Support Approach to Fleet Maintenance Requirements in the Aviation Industry. 5. Journal of Aircraft; 43: 1352-1360.