Subhodeep Moitra | Artificial Intelligence | Young Researcher Award

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Mr. Subhodeep Moitra | Artificial Intelligence | Young Researcher Award

Techno College Hooghly | India

Subhodeep Moitra is a computer science researcher focused on advancing artificial intelligence through the fusion of human-like visual perception and cognition. His academic foundation spans computer applications at both undergraduate and postgraduate levels, where he built strong expertise in machine learning, deep learning, computer vision, neural networks, adversarial robustness, and cognitive modeling. His research explores self-supervised reconstruction, adversarial recovery, AGI-oriented theoretical computing, medical prediction systems, and environmental forecasting, with publications in journals, conferences, preprint platforms, and book chapters. He has contributed to projects ranging from temperature forecasting and brain-stroke detection to adversarially robust autoencoders and AGI theory. His professional experience includes serving as a visiting faculty member, teaching programming, mentoring research projects, and engaging in active collaborative work. His technical skills extend across Python, deep learning frameworks, MERN stack development, and cloud-based AI tools, supported by multiple certifications from NASA, NVIDIA, CERN, IBM, Oracle, and Coursera. He has presented papers at international conferences and earned best paper presentation awards for his contributions in machine learning–driven forecasting and adversarial perception. His long-term research interest lies in building unified AI systems capable of perceiving, reasoning, and adapting with human-inspired intelligence, aiming to push the boundaries of next-generation cognitive AI.

Profile: Google Scholar

Featured Publications

Moitra, S., & Banerjee, D. (n.d.). Robustness as Latent Symmetry: A Theoretical Framework for Semantic Recovery in Deep Learning. OSF.

Moitra, S., & Banerjee, D. (n.d.). Are We Even on the Right Track? A Theoretical Framework for AGI Beyond Classical Computation. Authorea Preprints.

Moitra, S., & Banerjee, D. (n.d.). Skip the Chaos: A Self-Supervised Learning-Powered Autoencoder for Adversarial Recovery. OSF.

Pintu, P., Subhodeep, M., & Deblina, B. (n.d.). The mystery of Neural Network: Linked with quantum mechanics and universe. ResearchGate.

Pal, P., Moitra, S., & Banerjee, D. (n.d.). The mystery of Neural Network: Linked with quantum mechanics and universe.

Jayachithra R | Bio-Medical | Best Researcher Award

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Dr. Jayachithra R | Bio-Medical | Best Researcher Award

Urumu Dhanalakshmi College | India

Dr. R. Jayachitra is a dedicated researcher and academic specializing in material characterization with extensive contributions to nanomaterial synthesis and application-oriented studies. With advanced qualifications in physics and related disciplines, she has accumulated strong experience in teaching at both postgraduate and undergraduate levels and long-standing research involvement. Her work focuses on graphene-based transition metal oxide nanocomposites for wastewater treatment and the development of nanosized functional materials such as yttrium-doped cerium dioxide for photocatalytic applications. She has also contributed to computational, electronic spectral analysis, and molecular docking investigations of complex organic compounds, highlighting their electronic activity, molecular interactions, and medicinal potential. Her research portfolio includes publications in SCI and Scopus-indexed journals, authorship of several ISBN-listed books, and a patent under process, demonstrating a consistent commitment to scientific innovation. Her Google Scholar profile reflects 366 citations, an h-index of 11, and an i10-index of 11, indicating the visibility and relevance of her scholarly work. She has collaborated with leading national institutes for ultrasonic and metallurgical characterization, adding interdisciplinary strength to her research outcomes. With expertise spanning material science, nanotechnology, and computational studies, she continues to contribute impactful findings aligned with the Best Researcher Award and Women Research Award categories.

Profile: Google Scholar

Featured Publications

Vijayalakshmi, K., Muthupandi, V., & Jayachitra, R. (2011). Influence of heat treatment on the microstructure, ultrasonic attenuation and hardness of SAF 2205 duplex stainless steel. Materials Science and Engineering: A, 529, 447–451.

Kanagavalli, A., Jayachitra, R., Thilagavathi, G., Padmavathy, M., Elangovan, N., & others. (2023). Synthesis, structural, spectral, computational, docking and biological activities of Schiff base (E)-4-bromo-2-hydroxybenzylidene) amino)-N-(pyrimidin-2-yl) benzenesulfonamide. Journal of the Indian Chemical Society, 100(1), 100823.

Thilagavathi, G., Kanagavalli, A., Jayachitra, R., Padmavathy, M., Elangovan, N., & others. (2022). Synthesis, structural, computational, electronic spectra, wave function properties and molecular docking studies of (Z)-4-(((5-methylfuran-2-yl)methylene)amino)-N-(thiazol-2-yl) …. Journal of the Indian Chemical Society, 99(12), 100786.

Jayachitra, R., Thilagavathi, G., Kanagavalli, A., Elangovan, N., Sirajunnisa, A., & others. (2023). Synthesis, computational, electronic spectra, and molecular docking studies of 4-((diphenylmethylene)amino)-N-(pyrimidin-2-yl) benzenesulfonamide. Journal of the Indian Chemical Society, 100(1), 100836.

Kanagavalli, A., Thilagavathi, G., Jayachitra, R., Elangovan, N., Sowrirajan, S., & others. (2023). Synthesis, electronic structure, UV–vis, wave function, and molecular docking studies of Schiff base (Z)-N-(thiazol-2-yl)-4-((thiophene-2-ylmethylene)amino) benzenesulfonamide. Polycyclic Aromatic Compounds, 43(10), 8710–8728.

Aishwarya Jaiswal | Numerical Analysis | Best Researcher Award

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Ms. Aishwarya Jaiswal | Numerical Analysis | Best Researcher Award

IIT BHU| India

Aishwarya Jaiswal is a dedicated researcher in numerical analysis of partial differential equations, contributing to the advancement of efficient and uniformly convergent computational methods. With strong academic preparation in mathematics and computing from premier Indian institutes, she has developed expertise in numerical schemes for singularly perturbed systems, convection–diffusion models, parabolic reaction–diffusion equations, and multiscale interface problems. Her scholarly output includes multiple peer-reviewed publications in international journals, supported by citation metrics that reflect early research impact, including 1 citation, 1 h-index, and 0 i10-index, along with 1 indexed document. She has worked on diverse research themes such as boundary and interior layer phenomena, component-wise splitting algorithms, higher-order numerical schemes, and efficient discretization techniques. Her academic journey includes hands-on research experience through conference presentations, workshops, and collaborative visits at reputed institutions, contributing to global knowledge exchange in applied mathematics. Her interests span numerical PDEs, error analysis, computational methods, and scientific computing. She has been recognized with prestigious competitive awards, including highly regarded research fellowships that support her doctoral investigations. Through her continued focus on accuracy, robustness, and computational efficiency, she aims to contribute impactful advancements to the field of numerical mathematics and applied scientific computation.

Profile: Google Scholar

Featured Publications

Jaiswal, A., Kumar, S., & Ramos, H. Boundary and interior layer phenomena in coupled multiscale parabolic convection–diffusion interface problems: Efficient numerical resolution and analysis. International Journal of Numerical Methods for Heat & Fluid Flow., Cited by: 1

Jaiswal, A., Kumar, S., & Clavero, C. Efficient component-wise splitting approach to solve coupled singularly perturbed parabolic reaction–diffusion systems with interior layers. Numerical Algorithms.

Jaiswal, A., Kumar, S., & Ramos, H. Efficient uniformly convergent numerical methods for singularly perturbed parabolic reaction–diffusion systems with discontinuous source term. Journal of Applied Mathematics and Computing.

Jaiswal, A., Kumar, S., & Kumar, S. A priori and a posteriori error analysis for a system of singularly perturbed Volterra integro-differential equations. Computational and Applied Mathematics, 42(6), 278.

Banushri S | Deep Learning | Best Researcher Award

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Mrs. Banushri S | Deep Learning | Best Researcher Award

Impact College of Engineering and Applied Sciences| India

Dr. Banushri S is an accomplished academician and researcher in Computer Science and Engineering, recognized for her contributions to machine learning, deep learning, image processing, and human activity recognition. She has published impactful research across reputed journals and conferences, contributing to the scientific community with multiple documents, citations, and an evolving h-index that reflects her growing influence in the field. Her academic journey includes strong foundational degrees in engineering and digital electronics, shaping her expertise in logic design, embedded systems, computer architecture, networking, operating systems, programming, and advanced AI-driven technologies. With extensive teaching experience as an Assistant Professor in leading engineering institutions, she has guided numerous undergraduate and postgraduate learners, supervised research projects, and supported curriculum development and departmental academic activities. Her research works span areas such as fall detection, wearable sensor data analysis, transfer learning, and long-range context modeling for human activity recognition, including contributions indexed in Scopus and other reputed platforms. She has actively participated in faculty development programs, workshops, and conferences focusing on artificial intelligence, computer vision, and full-stack technologies, while also being a member of professional bodies like ISTE and CSI. Her work reflects a commitment to advancing intelligent systems research and contributing to academic excellence.

Profile: Scopus

Featured Publications

Banushri, S. (2026). Attention-guided residual shrinkage with gated recurrent unit for human activity recognition. Information Processing and Management.

Runu Banerjee Roy | Artificial Intelligence | Best Researcher Award

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Dr. Runu Banerjee Roy | Artificial Intelligence | Best Researcher Award

Jadavpur University| India

Dr. Runu Banerjee Roy is a Professor in Instrumentation and Electronics Engineering at Jadavpur University, widely recognized for her contributions to electronic olfaction, taste sensing, molecular imprinting, sensor development, and artificial intelligence–based instrumentation. She has an extensive research profile with 1213 citations, an h-index of 17, and an i10-index of 25, reflecting her strong scholarly impact and research productivity. Her publication record includes more than 50 peer-reviewed journal papers, around 40 conference papers, multiple book chapters, and several patents that are granted, published, or filed. She has successfully guided doctoral and postgraduate research scholars and completed multiple sponsored research projects funded by major scientific agencies, focusing on portable sensing devices, electronic nose and tongue systems, and electrochemical detection technologies for applications in food quality and safety. In academics, she has served in leadership roles such as Head of Department, NBA accreditation coordinator, and curriculum committee member, contributing to program development and quality enhancement. Her work has earned recognition through competitive research awards, scientific prizes, and support for international research presentations. With strong expertise spanning instrumentation, intelligent sensing systems, and applied electronics, she continues to advance innovative research, academic excellence, and technology-driven solutions in modern sensor engineering.

Profile: Google Scholar | Scopus

Featured Publications

Roy, R. B., Tudu, B., Shaw, L., Jana, A., Bhattacharyya, N., & Bandyopadhyay, R. (2012). Instrumental testing of tea by combining the responses of electronic nose and tongue. Journal of Food Engineering, 110(3), 356–363.

Banerjee, M. B., Roy, R. B., Tudu, B., Bandyopadhyay, R., & Bhattacharyya, N. (2019). Black tea classification employing feature fusion of E-Nose and E-Tongue responses. Journal of Food Engineering, 244, 55–63.

Banerjee, R., Tudu, B., Bandyopadhyay, R., & Bhattacharyya, N. (2016). A review on combined odor and taste sensor systems. Journal of Food Engineering, 190, 10–21.

Roy, R. B., Chattopadhyay, P., Tudu, B., Bhattacharyya, N., & Bandyopadhyay, R. (2014). Artificial flavor perception of black tea using fusion of electronic nose and tongue response: A Bayesian statistical approach. Journal of Food Engineering, 142, 87–93.

Nag, S., Pradhan, S., Naskar, H., Roy, R. B., Tudu, B., Pramanik, P., … et al. (2021). A simple nano cerium oxide modified graphite electrode for electrochemical detection of formaldehyde in mushroom. IEEE Sensors Journal, 21(10), 12019–12026.

Gaurang Sharma | Mathematics | Young Researcher Award

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Dr. Gaurang Sharma | Mathematics | Young Researcher Award

College of Agricultural Engineering & Technology | India

Dr. Sharma Gaurangkumar Bhanuprasad is a dedicated academician and researcher currently serving as an Assistant Professor at the College of Agricultural Engineering & Technology, Godhra. He holds a doctoral degree in Mathematics with a strong foundation in advanced mathematical concepts and their real-world applications. His primary research interests include mathematical modeling and epidemiology, with a focus on developing analytical frameworks for understanding complex biological and environmental systems. He has contributed significantly to the research community through multiple publications, including five journal papers indexed in reputable scientific databases, two research papers presented at international conferences, and two patents under process. His Google Scholar profile reflects his growing scholarly influence, supported by a citation count of three, documented research outputs, and measurable academic contributions. He is also associated with professional bodies through two memberships, reinforcing his involvement in collaborative scientific initiatives. His research identifiers include an ORCID profile and a Scopus Author ID, ensuring transparent documentation of his academic work. He has been honored with the SHODH scholarship awarded by the Education Department of Gujarat for research excellence. Dr. Sharma continues to advance innovative ideas in mathematical sciences, contributing meaningfully to the academic, scientific, and applied research communities.

Profile: Google Scholar

Featured Publications

Sharma, A., Sharma, G., & Singh, F. (2023). Computational models to study the infectious disease COVID-19: A review. International Journal of Mathematical Modelling and Numerical Optimisation.

Sharma, G., Sharma, A., & Parmar, N. (2024). A delay differential equation model on COVID-19 with vaccination strategy. RAIRO – Operations Research, 58(5), 4093–4117.

Sharma, G., & Sharma, A. (2024). The effect of double dose of vaccination on COVID-19 infection in India: A mathematical study. World Scientific News, 195, 7–18.

Sharma, G., & Sharma, A. (2025). Computational model on viral load dynamics in response to COVID-19 infection in a cell. The European Physical Journal Plus, 140(11), 1–15.

Sharma, G., Sharma, A., & Parmar, N. (2025). Mathematical model on COVID-19 transmission with absence and presence of second dose of vaccination in Turkey. TWMS Journal of Applied and Engineering Mathematics.

Jibin Joy Daniel | Orthodontics | Editorial Board Member

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Dr. Jibin Joy Daniel | Orthodontics | Best Researcher Award

Pushpagiri College Of Dental Sciences | India

Dr Jibin Joy Daniel is an Assistant Professor of Orthodontics at Pushpagiri College of Dental Sciences, Thiruvalla, India, bringing a clinical and academic career grounded in advanced dental-surgery training and postgraduate expertise in orthodontics and dentofacial orthopaedics. His research interests span skeletal malocclusion genetics (notably RUNX2 gene polymorphisms), clear aligner biomechanics, myofunctional appliance compliance, airway dynamics in orthodontic treatment, and the integration of AI in orthodontic diagnostics and therapeutics. He has authored multiple peer-reviewed literature reviews and original research articles, contributing to studies on orthodontic treatment modalities, esthetics, growth patterns, and novel appliances. While a specific h-index, total document count and citation-count are not publicly verified at this time, his publication record and active conference engagement reflect an emerging scholarly footprint. He has been recognized through awards, grants and international presentations for his academic and clinical performance. Dr Daniel continues to develop as a clinician-scientist and educator, aiming to advance evidence-based orthodontics and foster student awareness and patient-centred care in his field.

Profile: Google Scholar 

Featured Publications

Daniel, J. J., & Kumar, A. (2024). Smile esthetics in orthodontics – Review of literature. Journal of Dentistry, 14, 701.

Daniel, J. J., Nizar, A., & Kumar, A. H. (2023). Transverse and sagittal arch development using Transforce appliance – A case report. Saudi Journal of Oral and Dental Research, 8, 59–64.

Geojan, D. G., & Daniel, J. J. (2025). Patient compliance with removable myofunctional appliance wear in central Travancore population: A questionnaire-based study. International Journal of Advanced Research, 11(2), 168–170.

Daniel, J. J. (2023). Awareness about clear aligner among dental students – A cross-sectional study. IP Indian Journal of Orthodontics and Dentofacial Research.

Amir, S., John, J., Thomas, N. O., Abraham, N., Cherian, R. A., & Daniel, J. J. (2023). Different orthodontic treatment modalities on airway – A review. International Journal of Dental and Medical Sciences Research.

Abdus Samad | Pharmacy | Outstanding Scientist Award

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Dr. Abdus Samad | Pharmacy | Outstanding Scientist Award

Post Graduate Institute of Medical Education & Research, Chandigarh | India

Dr. Sahima Tabasum is an emerging Environmental Science researcher with expertise in nanomaterials, water purification, photocatalysis, and environmental remediation, supported by an h-index of 4, over 48 citations, and 10 indexed documents. She holds a Ph.D. in Environmental Sciences, where she focused on nano-structural modification of g-C3N4-based composites for pesticide mineralization and the development of continuous photocatalytic reactor systems. Her multidisciplinary training includes advanced material synthesis, wastewater treatment technologies, solid waste management, and water quality monitoring. Dr. Tabasum has gained research experience through academic and international environmental programs, contributing to nanomaterial-based pollutant degradation, biochar fabrication, membrane technologies, microplastic treatment, and molecularly imprinted polymer (MIP) systems for emerging contaminants such as PFAS, ammonia, and heavy metals. Her research interests span photocatalysis, polymer membranes, CO₂ conversion, energy generation, nanomaterial–pollutant interactions, and sustainable environmental technologies. She has been recognized with distinctions for poster presentations, project excellence, and prestigious Young Scientist–International Travel Support, along with contributions to conferences, workshops, and global sustainability dialogues. With active roles as a reviewer and editorial board member for reputed journals, she continues to advance sustainable materials, green catalytic systems, and innovative solutions for environmental challenges.

Profile: Google Scholar

Featured Publications

Samad, A., Sultana, Y., & Aqil, M. (2007). Liposomal drug delivery systems: An update review. Current Drug Delivery, 4(4), 297–305.
(Cited by: 1310)

Alam, M. I., Beg, S., Samad, A., Baboota, S., Kohli, K., Ali, J., Ahuja, A., & Akbar, M. (2010). Strategy for effective brain drug delivery. European Journal of Pharmaceutical Sciences, 40(5), 385–403.
(Cited by: 557)

Samad, A., Alam, M. I., & Saxena, K. (2009). Dendrimers: A class of polymers in nanotechnology for the delivery of active pharmaceuticals. Current Pharmaceutical Design, 15(25), 2958–2969.
(Cited by: 129)

Beg, S., Samad, A., Alam, M. I., & Nazish, I. (2011). Dendrimers as novel systems for delivery of neuropharmaceuticals to the brain. CNS & Neurological Disorders – Drug Targets, 10(6), 693–702.
(Cited by: 84)

Samad, A., Shams, M. S., Ullah, Z., Wais, M., Nazish, I., Sultana, Y., & Aqil, M. (2009). Status of herbal medicines in the treatment of diabetes: A review. Current Diabetes Reviews, 5(2), 102–111.
(Cited by: 78)

Sadananda Behera | Engineering | Best Researcher Award

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Assist. Prof. Dr. Sadananda Behera | Engineering | Best Researcher Award

NIT Rourkela | India

Dr. Sadananda Behera is a distinguished researcher in optical communication and intelligent network systems, widely recognized for his impactful scientific contributions. With strong academic foundations spanning electronics and communication engineering, advanced communication technologies, and optical systems, he has developed expertise that bridges theory, experimentation, and real-world network challenges. His research experience includes significant roles in premier institutions where he contributed to coherent modulation testbeds, advanced resource-allocation strategies, and machine-learning-driven solutions for elastic and space-division multiplexing networks. He has also conducted notable postdoctoral work focusing on AI-enabled optical networks, traffic prediction, and soft-failure detection frameworks. His scholarly output includes journal articles, conference presentations, and collaborative works addressing impairment-aware routing, bit loading, anomaly detection, and federated learning architectures for communication infrastructures. His research influence is demonstrated through 195 citations, an h-index of 7, and an i10-index of 6, reflecting the depth and applicability of his contributions across the photonics and network-optimization community. He continues to advance high-impact projects related to next-generation 6G hybrid transceivers and secure deep-learning-based channel estimation frameworks. His work focuses on optical communication, machine-learning applications for networks, and quantum key distribution, contributing to the evolution of resilient, high-capacity, and secure communication ecosystems.

Profile: Google Scholar

Featured Publications

Behera, S., Deb, A., Das, G., & Mukherjee, B. (2019). Impairment aware routing, bit loading, and spectrum allocation in elastic optical networks. Journal of Lightwave Technology, 37(13), 3009–3020.

Behera, S., George, J., & Das, G. (2018). Effect of transmission impairments in CO-OFDM based elastic optical network design. Computer Networks, 144, 242–253.

Behera, S., & Das, G. (2020). Dynamic routing and spectrum allocation in elastic optical networks with minimal disruption. In Proceedings of the National Conference on Communications (NCC) (pp. 1–5). IEEE.

Behera, S., Panayiotou, T., & Ellinas, G. (2023). Machine learning framework for timely soft-failure detection and localization in elastic optical networks. Journal of Optical Communications and Networking, 15(10), E74–E85.

Behera, S., Savva, G., Manousakis, K., & Ellinas, G. (2023). Impairment-aware routing, modulation, spectrum, and core allocation with bit loading in spectrally–spatially flexible optical networks. Journal of Optical Communications and Networking, 15(6), 318–332.

Sahima Tabasum | Environmental Science | Women Researcher Award

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Dr. Sahima Tabasum | Environmental Science | Women Researcher Award

Lovely Professional University | India

Dr. Sahima Tabasum is an emerging Environmental Science researcher with expertise in nanomaterials, water purification, photocatalysis, and environmental remediation, supported by an h-index of 4, over 48 citations, and 10 indexed documents. She holds a Ph.D. in Environmental Sciences, where she focused on nano-structural modification of g-C3N4-based composites for pesticide mineralization and the development of continuous photocatalytic reactor systems. Her multidisciplinary training includes advanced material synthesis, wastewater treatment technologies, solid waste management, and water quality monitoring. Dr. Tabasum has gained research experience through academic and international environmental programs, contributing to nanomaterial-based pollutant degradation, biochar fabrication, membrane technologies, microplastic treatment, and molecularly imprinted polymer (MIP) systems for emerging contaminants such as PFAS, ammonia, and heavy metals. Her research interests span photocatalysis, polymer membranes, CO₂ conversion, energy generation, nanomaterial–pollutant interactions, and sustainable environmental technologies. She has been recognized with distinctions for poster presentations, project excellence, and prestigious Young Scientist–International Travel Support, along with contributions to conferences, workshops, and global sustainability dialogues. With active roles as a reviewer and editorial board member for reputed journals, she continues to advance sustainable materials, green catalytic systems, and innovative solutions for environmental challenges.

Profile: Google Scholar| Scopus | Orcid

Featured Publications

Tabasum, S., Singh, P. P., Pramanik, A., Kavitha, V., & Iqbal, R. (n.d.). Mechanistic insights into the synergistic photocatalytic degradation of carbofuran by g-C3N4/GO/V2O5 nano-composite. Topics in Catalysis. https://doi.org/10.1007/s11244-025-02126-8

Tabasum, S., Sharma, A., Dhupar, N., Bagri, U., Yousuf, S., Kumar, V., Singh, A., & Shukla, S. K. (n.d.). Visible light-induced continuous process for photodegradation of chlorpyrifos using g-C3N4/GO/La2O3 photocatalyst from agricultural aquatic waste. Chemical Physics Impact. https://doi.org/10.1016/j.chphi.2024.100751

Tabasum, S., Rani, S., Sharma, A., Dhupar, N., Singh, P. P., Bagri, U., & Kumar, D. (n.d.). Efficient photocatalytic degradation of chlorpyrifos pesticide from aquatic agricultural waste using g-C3N4 decorated graphene oxide/V2O5 nanocomposite. Topics in Catalysis. https://doi.org/10.1007/s11244-023-01865-w

Rani, S., Sharma, A., Tabasum, S., Malik, A. Q., Chaudhary, S., Kumar, D., Singh, H., & Singh, P. P. (n.d.). Highly efficient photocatalytic properties of La-doped ZnO over pristine ZnO for degradation of 2-chlorophenol from aquatic agriculture waste. Chemistry Africa. https://doi.org/10.1007/s42250-023-00630-6

Tabasum, S., Rani, S., Thakur, A., Sindhu, M., Maan, K. S., Upasana, Patel, V., Sarika, Malik, A. Q., Gajbhiye, P., et al. (n.d.). Photo-catalytic detoxification of chlorpyrifos pesticide from the aquatic environment using g-C3N4 doped with GO nano-composite. In The Fourth Scientific Conference for Electrical Engineering Techniques Research (EETR2022). https://doi.org/10.1063/5.0163717