Abesh Chakraborty

@rgu.ac

Assistant Professor in Zoology & Assistant Dean (Academic Affairs) RSLSC
Dept.of Zoology, The Assam Royal Global University

Abesh Chakraborty


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https://researchid.co/dr.abeshchakraborty

RESEARCH, TEACHING, or OTHER INTERESTS

Insect Science, Animal Science and Zoology, Ecology, Evolution, Behavior and Systematics, Animal Science and Zoology
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Scopus Publications

Scopus Publications

  • A preliminary analysis of historical range: Distribution mapping of Indian Sepsidae with special reference to Assam
    Mayoushree Gogoi, Bhitali Barkakati, Krishnaa Boro, Abesh Chakraborty
    International Journal of Tropical Insect Science, 2025
  • A checklist of flesh flies (Diptera, Sarcophagidae) from Assam, India
    Mayoushree Gogoi, Annu Kumari, Anurudha Chakraborty, Sangeeta Biswas, Abesh Chakraborty
    Entomon, 2024
    A comprehensive revised checklist pertaining to taxonomy and bionomics of Sarcophagidae of Assam is prepared. The current study revealed the presence of 23 species, including four endemic and 19 non-endemic from Assam, in comparison to elsewhere to the world.
  • Deep learning insights and methods for classifying wildlife
    Meenakshi Anurag Thalor, Rohith Nagabhyrava, K. Rajkumar, Abesh Chakraborty, Rajesh Singh, Upendra Singh Aswal
    2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2023, 2023
    With the introduction of low-cost and widely accessible sensors such as cellphones, drones, satellites, voice recorders, and bio-logging equipment, the amount of information collected about animals has expanded. Meanwhile, modern data processing systems prohibit them from collecting, digesting, and condensing data into usable information. We think that machine learning, especially deep learning algorithms, will be able to tackle this analytical difficulty by enhancing our understanding, monitoring capacities, and animal welfare. By merging machine learning with ecological processes, it may be feasible to expand the inputs to population and behavior models, resulting in integrated hybrid modeling tools where machine learning models give data-supported insights and ecological models act as constraints. Animal ecologists may basically profit from the quantity of data created by contemporary sensor technologies by integrating cutting-edge machine learning methods with ecological domain expertise. This will enable them to assess population abundances more precisely, research animal behavior, and reduce human-wildlife conflicts.
  • Biosystematic checklist of common myiasis causing calliphorids and sarcophagids flies of India
    Journal of Advanced Zoology, 2017
  • Developmental Variation of Indian Thermophilic Variety of Scuttle Fly Megaselia (Megaselia) scalaris (Loew, 1866) (Diptera: Phoridae) on Different Substrates
    Abesh Chakraborty, Atanu Naskar, Panchanan Parui, Dhriti Banerjee
    Scientifica, 2016
    The scuttle flies (Diptera: Phoridae) are important in forensic dipterology, because of their necrophagous habit. They are amongst the first wave of insects visiting human corpses in mechanically barricaded environments; hence their immature stages are generally used for estimation of PMI. The effect of different substrates commonly used for developmental studies was studied to analyze the variation of growth of the thermophilic variety ofMegaselia (M.) scalarisprevalent in India on GDM, EDM, and SMS (n=3). One approach of PMI estimation depends on larvae collected from the crime scene and comparing them with reference data derived from larval rearing to establish PMI. Results showed that there was a significant variation in avg. length (F(2,111)=15.79873,p=0.000000917), width (F(2,111)=14.60528,p=0.00000234), and biomass (F(2,111)=37.01727,p=0.000000000000482) of the immature stages in the three media and the larvae grow maximally in the SMS medium. The results of the present study thus provide baseline data on the growth and developmental pattern of theMegaselia (M.) scalaris, which can be utilized in conjunction with specific geoclimatic reference data, for forensic entomological studies and also for using the phorid as a biocontrol agent of pestiferous insects.