Dr. Hamed Ahmadi Born in December 1980 in Yazd, Iran. Primary and High School (Iranshahr School), Yazd (1986-1998). He earned BSc in the field of Animal Science from the Ferdowsi University of Mashhad (1998-2003), MSc in the field of Animal Feed and Nutrition from the University of Guilan (2003-2006), and PhD of Poultry Science from Ferdowsi University of Mashhad (2007-2012). Visiting scholar through a Sabbatical leave, University of Hohenheim, Stuttgart, Germany, working on the Modeling and optimization the nutritional system (2011-2012). In January 2011 he was joint as an Assistant Professor for Bioscience and Agriculture Modeling to the Department of Poultry Science in the College of Agriculture at Tarbiat Modares University. His main responsibilities are to conduct research through the multidisciplinary projects on “Agriculture-Nutrition-Poultry-Modeling-Data Science” and to direct graduate students at MSc and PhD levels. Hamed, holds memberships in the Poultry Science Association (PSA), World's Poultry Science Association (WPSA), and Iranian Society for Animal Science, also contributes in Editorial boards of several scientific journals. He was the Associate Editor for Poultry Science during a 7-year period starting from 2009.
1. Ahmadi H (2017) A mathematical function for the description of nutrient-response curve. PloS one 12(11):e0187292. 2. Ghanaatparast-Rashti M, Mottaghitalab M, & Ahmadi H (2017) Effect of in-ovo feeding of beta-hydroxy beta-methylbutyrate and dextrin and posthatching water and feed deprivation on body glycogen resources and jejunal morphology of broilers at 7 days of age using response surface methodology. Iranian Journal of Animal Science 48(2):273-286.
3. Azad SK, Shariatmadari F, Torshizi MK, & Ahmadi H (2017) Effect of zinc concentration and source on performance, tissue mineral status, activity of superoxide dismutase enzyme and lipid peroxidation of meat in broiler chickens. Animal Production Science. 4. Ahmadi H & Rodehutscord M (2017) Application of Artificial Neural Network and Support Vector Machines in Predicting Metabolizable Energy in Compound Feeds for Pigs. Frontiers in Nutrition 4:27. 5. Ghanaatparast?Rashti M, Mottaghitalab M, & Ahmadi H (2017) In ovo feeding of nutrients and its impact on post?hatching water and feed deprivation up to 48 hr, energy status and jejunal morphology of chicks using response surface models. Journal of Animal Physiology and Animal Nutrition. 6. Abedini M, Shariatmadari F, Torshizi MK, & Ahmadi H (2017) Effects of a dietary supplementation with zinc oxide nanoparticles, compared to zinc oxide and zinc methionine, on performance, egg quality, and zinc status of laying hens. Livestock Science 203:30-36. 7. Abedini M, Shariatmadari F, Torshizi MAK, & Ahmadi H (2017) Effects of Zinc Oxide Nanoparticles on Performance, Egg Quality, Tissue Zinc Content, Bone Parameters, and Antioxidative Status in Laying Hens. Biological Trace Element Research:1-9. 8. Jamshidi S, Yadollahi A, Ahmadi H, Arab M, & Eftekhari M (2016) Predicting in vitro culture medium macro-nutrients composition for pear rootstocks using regression analysis and neural network models. Frontiers in plant science 7. 9. Arab MM, Yadollahi A, Shojaeiyan A, & Ahmadi H (2016) Artificial neural network genetic algorithm as powerful tool to predict and optimize in vitro proliferation mineral medium for G× N15 rootstock. Frontiers in Plant Science 7. 10. Siegert W, Ahmadi H, & Rodehutscord M (2015) Meta-analysis of the influence of dietary glycine and serine, with consideration of methionine and cysteine, on growth and feed conversion of broilers. Poultry science 94(8):1853-1863. 11. Siegert W, Ahmadi H, Helmbrecht A, & Rodehutscord M (2015) A quantitative study of the interactive effects of glycine and serine with threonine and choline on growth performance in broilers1. Poultry science 94(7):1557-1568. 12. Sedghi M, Ebadi M, Golian A, & Ahmadi H (2013) Prediction of digestible amino acid and true metabolizable energy contents of sorghum grain from total essential amino acids. The Journal of Agricultural Science 151(5):693-700. 13. Ahmadi H (2013) Optimizing broiler chicken production using response surface methodology and artificial neural network models. (Ferdowsi University of Mashhad). 14. Tahmoorespur M & Ahmadi H (2012) A neural network model to describe weight gain of sheep from genes polymorphism, birth weight and birth type. Livestock Science 148(3):221-226. 15. Sedghi M, Golian A, Soleimani-Roodi P, Ahmadi A, & Aami-Azghadi M (2012) Relationship between color and tannin content in sorghum grain: application of image analysis and artificial neural network. Revista Brasileira de Ciência Avícola 14(1):57-62. 16. Sedghi M, Ebadi M, Golian A, & Ahmadi H (2012) Prediction of digestible amino acid and true metabolizable energy contents of sorghum grain from total essential amino acids. Journal of Agricultural Science 150. 17. Faridi A, Mottaghitalab M, & Ahmadi H (2012) Sensitivity analysis of an early egg production predictive model in broiler breeders based on dietary nutrient intake. The Journal of Agricultural Science 150(1):87-93. 18. Faridi A, Golian A, & Ahmadi H (2012) Comparison of responses to dietary protein and lysine in broiler chicks reared before and after 2000 via neural network models. The Journal of Agricultural Science 150(6):775-786. 19. Ahmadi H & Rodehutscord M (2012) A meta-analysis of responses to dietary nonphytate phosphorus and phytase in laying hens. Poultry science 91(8):2072-2078. 20. Sedghi M, Golian A, & Ahmadi H (2011) Prediction of digestible amino acids in sorghum. Poultry Science Meeting 2011. 21. Sedghi M, Ebadi M, Golian A, & Ahmadi H (2011) Estimation and modeling true metabolizable energy of sorghum grain for poultry. Poultry science 90(5):1138-1143. 22. Faridi A, Mottaghitalab M, Darmani-Kuhi H, France J, & Ahmadi H (2011) Predicting carcass energy content and composition in broilers using the group method of data handling-type neural networks. The Journal of Agricultural Science 149(2):249-254. 23. Ebadi M, Sedghi M, Golian A, & Ahmadi H (2011) Prediction of the true digestible amino acid contents from the chemical composition of sorghum grain for poultry. Poultry science 90(10):2397-2401. 24. Ahmadi H & Golian A (2011) Optimization of broiler performance fed diets varying in digestible protein and amino acids using response surface model. Poultry Science Meeting 2011. 25. Ahmadi H & Golian A (2011) Response surface and neural network models for performance of broiler chicks fed diets varying in digestible protein and critical amino acids from 11 to 17 days of age. Poultry science 90(9):2085-2096. 26. Sedghi M, Golian A, Kermanshahi H, & Ahmadi H (2010) Effect of dietary supplementation of licorice extract and a prebiotic on performance and blood metabolites of broilers. South African Journal of Animal Science 40(4). 27. Mottaghitalab M, Faridi A, Darmani-Kuhi H, France J, & Ahmadi H (2010) Predicting caloric and feed efficiency in turkeys using the group method of data handling-type neural networks. Poultry science 89(6):1325-1331. 28. Ahmadi H & Golian A (2010) Response surface model for broiler chickens performance fed diets varying in digestible protein and amino acids. Joint Animal Science Meetings (ADSA, PSA, AMPA, CSAS, WSASAS, ASAS). 29. Ahmadi H & Golian A (2010) Growth analysis of chickens fed diets varying in the percentage of metabolizable energy provided by protein, fat, and carbohydrate through artificial neural network. Poultry science 89(1):173-179. 30. Ahmadi H & Golian A (2010) The integration of broiler chicken threonine responses data into neural network models. Poultry science 89(11):2535-2541. 31. Golian A (2009) Modelling and optimising early performance for broiler chicks. British Society of Animal Science 2009. 32. Ahmadi H, Mottaghitalab M, Nariman-Zadeh N, & Golian A (2008) Predicting performance of broiler chickens from dietary nutrients using group method of data handling-type neural networks. British poultry science 49(3):315-320. 33. Ahmadi H, Golian A, Mottaghitalab M, & Nariman-Zadeh N (2008) Prediction model for true metabolizable energy of feather meal and poultry offal meal using group method of data handling-type neural network. Poultry science 87(9):1909-1912. 34. Ahmadi H & Golian A (2008) Neural network model for egg production curve. Journal of Animal and Veterinary Advances 7(9):1168-1170. 35. Ahmadi H & Golian A (2008) Non-linear hyperbolastic growth models for describing growth curve in classical strain of broiler chicken. Research Journal of Biological Sciences 3(11):1300-1304. 36. Ahmadi H, Mottaghitalab M, & Nariman-Zadeh N (2007) Group method of data handling-type neural network prediction of broiler performance based on dietary metabolizable energy, methionine, and lysine. The Journal of Applied Poultry Research 16(4):494-501. 37. Ahmadi H & Mottaghitalab M (2007) Hyperbolastic models as a new powerful tool to describe broiler growth kinetics. Poultry science 86(11):2461-2465. 38. Ahmadi H (2006) Modeling the effects of Dietary nutrients on Performance of Broiler Chickens at the Herd Scale. (University of Guilan). |
