Sukhes Mukherjee | Neuroscience | Outstanding Scientist Award

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Dr. Sukhes Mukherjee | Neuroscience | Outstanding Scientist Award

Additional Professor at All India Institute of Medical Sciences Bhopal, India.

Dr. Sukhes Mukherjee is an accomplished biochemist and educator, currently serving as Additional Professor in the Department of Biochemistry at the All India Institute of Medical Sciences (AIIMS), Bhopal, India. With over two decades of experience spanning academia, research, and clinical biochemistry, Dr. Mukherjee has established himself as a leading figure in the field of medical biochemistry and molecular diagnostics. He holds a Ph.D. in Clinical Biochemistry from Amrita Vishwa Vidyapeetham, preceded by an M.Sc. (Gold Medalist) in Medical Biochemistry from Sikkim Manipal University and a B.Sc. in Chemistry from the University of Calcutta. Dr. Mukherjee’s contributions encompass extensive research on biochemical markers, liver diseases, oxidative stress, and neurochemistry, with multiple awards acknowledging his excellence in both scientific inquiry and pedagogy. He has been invited to deliver over 40 national and international lectures and serves on editorial boards of reputed journals. His affiliations include the Royal Society of Biology (UK), American Association of Clinical Chemistry (AACC), and the Association of Clinical Biochemists of India. Through consistent academic leadership, research productivity, and global engagement, Dr. Mukherjee exemplifies dedication to biomedical science and its application in improving healthcare outcomes.

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Education

Dr. Sukhes Mukherjee possesses a strong academic foundation rooted in chemistry and medical biochemistry. He began his higher education journey with a B.Sc. (Hons.) in Chemistry from the University of Calcutta in 2000, laying the groundwork for a career in biomedical sciences. His academic excellence became evident during his M.Sc. in Medical Biochemistry from Sikkim Manipal University, where he earned the Gold Medal as the Best Outgoing Student in 2004. This accomplishment signified not only academic merit but also his commitment to the discipline. Dr. Mukherjee pursued doctoral studies at Amrita Vishwa Vidyapeetham, earning his Ph.D. in Clinical Biochemistry in 2009. His doctoral work focused on key clinical aspects of biochemistry and toxicology, marking the beginning of his specialization in liver diseases and neurochemistry. This multidisciplinary training across chemistry, medical biochemistry, and clinical diagnostics has provided him with a well-rounded perspective, enabling impactful contributions in both teaching and translational research. His academic background continues to support his success in mentoring, scholarly publication, and grant-winning projects at the national and international levels.

Professional Experience

Dr. Sukhes Mukherjee has accumulated extensive professional experience in academic institutions across India. His current role as Additional Professor in the Department of Biochemistry at AIIMS Bhopal, a position he has held since July 2020, builds upon a decade-long academic trajectory marked by increasing leadership responsibilities. Prior to this, he served as Associate Professor at AIIMS Bhopal (2017–2020) and in several other institutions including GIMSH, Government Medical College Saharanpur, NRIIMS, and VCSGGIMS&R. His earliest faculty appointment as Assistant Professor at VCSGGIMS&R in 2010 laid the foundation for his continued focus on teaching and clinical research. Across these roles, Dr. Mukherjee has consistently demonstrated commitment to academic excellence, curriculum development, and laboratory quality assurance. His professional journey reflects versatility, having served in both government and private medical colleges. These positions have allowed him to lead departmental activities, mentor postgraduate students, and supervise diagnostic laboratories. His expertise in ISO-15189 standards and internal auditing further enhances his contributions to laboratory quality management systems. Dr. Mukherjee’s academic mobility and leadership across diverse healthcare institutions underline his adaptability and sustained excellence in biochemistry education and practice.

Research Interest

Dr. Sukhes Mukherjee’s research interests lie at the intersection of clinical biochemistry, neurochemistry, hepatology, and molecular toxicology. His primary focus areas include the biochemical and molecular underpinnings of liver diseases, particularly alcoholic and non-alcoholic liver disorders. He has led research initiatives examining ethanol’s impact on liver function, angiogenesis, and brain damage, utilizing both biochemical markers and enzymatic studies. His early interest in free radical biology has matured into comprehensive investigations on oxidative stress and its implications for neurotoxicity and hepatic injury. Additionally, Dr. Mukherjee has contributed to cancer biochemistry through his studies on Ehrlich’s ascites carcinoma. Another key theme in his research is the development and validation of diagnostic biomarkers for various chronic diseases. He has also examined risk factors for metabolic disorders and the interplay between nutrition, toxicology, and biochemical signaling. His approach integrates classical biochemical techniques with modern molecular and analytical tools, enabling translational insights applicable to both clinical and public health settings. Dr. Mukherjee’s research continues to bridge basic biochemical mechanisms with applied clinical science, addressing current gaps in diagnosis, disease monitoring, and therapeutic intervention.

Research Skills

Dr. Sukhes Mukherjee brings a diverse array of research skills that encompass clinical diagnostics, biochemical assay development, molecular biology, and quality control. He is proficient in executing and interpreting a wide range of laboratory techniques, including enzymatic assays, electrophoresis, spectrophotometry, and chromatographic analyses. His training in ISO 15189 standards as an internal auditor and quality manager equips him to maintain rigorous standards in clinical laboratories, ensuring data integrity and diagnostic accuracy. Dr. Mukherjee is adept in designing experimental protocols for studying oxidative stress, free radical damage, and hepatotoxicity. His collaborative projects with organizations like CSIR and Daiichi Pure Chemicals demonstrate his capability in handling complex, multidisciplinary research themes. His experience spans both in vivo and in vitro models, allowing him to dissect the biochemical pathways involved in neurotoxicity and liver disease. Furthermore, his familiarity with statistical tools, scientific writing, and peer review enhances his ability to contribute to high-quality publications and research proposals. Whether as a principal investigator or co-investigator, Dr. Mukherjee’s methodical and quality-driven research approach has earned him recognition in academic, industrial, and regulatory research environments.

Awards and Honors

Dr. Sukhes Mukherjee has been the recipient of numerous national and international awards that recognize his academic distinction, research contributions, and leadership in medical biochemistry. Early in his career, he was honored with the Best Outgoing Student Gold Medal from Sikkim Manipal University (2004), followed by multiple awards from the Association of Clinical Biochemists of India, including the P.S. Murthy Award (2008), Sita Devi Award (2009), and the Pitabus Jamuna Memorial Award (2012). His research in neurochemistry earned him the prestigious Young Investigator Award from the International Society for Neurochemistry (2009), and international recognition continued with travel fellowships from AACC, USA, and a fellowship in South Korea. Dr. Mukherjee is a Fellow of the National Academy of Medical Sciences (MNAMS), the Linnean Society (FLS), and the Royal Society of Biology (CSi), among others. His inclusion in Marquis Who’s Who and awards from MAIER and NMMTA further reflect his scientific impact and professional visibility. These honors underscore a career marked by excellence in research, education, and service to the biomedical community.

Author Metrics

Dr. Sukhes Mukherjee’s scholarly contributions to the fields of medical biochemistry and clinical sciences are reflected in his impressive author metrics. As of the latest data, he has accumulated a total of 1,581 citations, demonstrating the significant influence and widespread recognition of his research in national and international scientific communities. With an h-index of 20, Dr. Mukherjee has at least 20 publications that have each been cited a minimum of 20 times, indicating both productivity and the sustained academic relevance of his work. His i10-index of 35 further illustrates that 35 of his research articles have received 10 or more citations, highlighting the consistent quality and impact of his contributions over time. These metrics reflect his expertise across a broad spectrum of biomedical research areas, including clinical biochemistry, neurochemistry, toxicology, free radical biology, and liver disease biomarkers. His work continues to be cited in leading peer-reviewed journals and used as a reference in both academic and clinical settings. These quantitative indicators affirm Dr. Mukherjee’s position as a respected researcher and thought leader in his field, underlining the continued academic and translational value of his scientific endeavors.

Publications Top Notes

1. Alcoholism and its effects on the central nervous system

  • Authors: S. Mukherjee

  • Journal: Current Neurovascular Research

  • Year: 2013

  • Citations: 146

2. Consequences of alcohol consumption on neurotransmitters – an overview

  • Authors: S. Mukherjee, S.K. Das, K. Vaidyanathan, D.M. Vasudevan

  • Journal: Current Neurovascular Research

  • Year: 2008

  • Citations: 87

3. Evaluation of blood oxidative stress‐related parameters in alcoholic liver disease and non‐alcoholic fatty liver disease

  • Authors: S.K. Das, V. Balakrishnan, S. Mukherjee, D.M. Vasudevan

  • Journal: Scandinavian Journal of Clinical and Laboratory Investigation

  • Year: 2008

  • Citations: 82

4. Oxidative stress is the primary event: effects of ethanol consumption in brain

  • Authors: S.K. Das, K.R. Hiran, S. Mukherjee, D.M. Vasudevan

  • Journal: Indian Journal of Clinical Biochemistry

  • Year: 2007

  • Citations: 80

5. Evolving interplay between dietary polyphenols and gut microbiota—an emerging importance in healthcare

  • Authors: S.K. Ray, S. Mukherjee

  • Journal: Frontiers in Nutrition

  • Year: 2021

  • Citations: 79

  • DOI: 10.3389/fnut.2021.634944

6. Medicinal properties of milk thistle with special reference to silymarin – an overview

  • Authors: S.K. Das, S. Mukherjee, D.M. Vasudevan

  • Publisher: CSIR

  • Year: 2008

  • Citations: 79

  • (This might be a review report or a book chapter – not always indexed in peer-reviewed journals.)

7. Comparison of haematological parameters in patients with non-alcoholic fatty liver disease and alcoholic liver disease

  • Authors: S.K. Das, S. Mukherjee, D.M. Vasudevan, V. Balakrishnan

  • Journal: Singapore Medical Journal

  • Year: 2011

  • Citations: 74

8. Biochemical and immunological basis of silymarin effect, a milk thistle (Silybum marianum) against ethanol-induced oxidative damage

  • Authors: S.K. Das, S. Mukherjee

  • Journal: Toxicology Mechanisms and Methods

  • Year: 2012

  • Citations: 67

9. Prediction of crushing behaviour of honeycomb structures

  • Authors: A. Chawla, S. Mukherjee, D. Kumar, T. Nakatani, M. Ueno

  • Journal: International Journal of Crashworthiness

  • Year: 2003

  • Citations: 56

10. Protective effect of resveratrol and vitamin E against ethanol-induced oxidative damage in mice: biochemical and immunological basis

  • Authors: S.K. Das, S. Mukherjee, G. Gupta, D.N. Rao, D.M. Vasudevan

  • Publisher: CSIR

  • Year: 2010

  • Citations: 53

  • (Possibly a CSIR report or chapter in a collected work.)

Conclusion

Dr. Sukhes Mukherjee exemplifies a dynamic and dedicated medical biochemist with extensive experience in teaching, research, and clinical diagnostics. Over the years, he has significantly contributed to the understanding of liver disease, neurotoxicity, and oxidative stress through interdisciplinary research backed by strong biochemical methodology. His professional appointments across renowned institutions and his progression to the role of Additional Professor at AIIMS Bhopal demonstrate his commitment to academic leadership and institutional development. With over 40 invited lectures, numerous editorial and peer-review roles, and active involvement in national and international societies, Dr. Mukherjee maintains a prominent presence in the global scientific community. His accolades and fellowships reflect both early promise and sustained excellence in medical biochemistry. A skilled educator, auditor, and mentor, Dr. Mukherjee continues to advance translational research and quality laboratory practices, fostering innovations that directly impact patient care and biomedical education. His career is a testament to perseverance, interdisciplinary thinking, and lifelong learning in the service of science and society.

Jinfu Fan | Machine Learning | Best Researcher Award

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Assoc. Prof. Dr. Jinfu Fan | Machine Learning | Best Researcher Award

Professor at Qingdao University, China.

Assoc. Prof. Dr. Jinfu Fan is a dedicated researcher and academic currently serving as an Associate Professor at the College of Computer Science Technology, Qingdao University (QU), China. He earned his Ph.D. in Computer Science from Tongji University, Shanghai, and further expanded his academic horizons as a visiting scholar at the School of Computing (SoC), National University of Singapore (NUS), from January to December 2022. Dr. Fan specializes in the fields of machine learning, data mining, and computer vision, with a notable emphasis on weakly supervised multi-label learning and super-resolution image reconstruction. His recent research project, MDiffSR, explores the application of mutual information and diffusion models in image super-resolution and has been published in the renowned Neurocomputing journal. His scholarly work demonstrates a solid blend of theoretical foundations and practical innovation, offering new directions in data-efficient learning and visual computing. Beyond research, Dr. Fan is actively involved in curriculum development and student mentorship at QU, contributing significantly to academic growth and collaborative learning. His passion for integrating advanced algorithms with real-world applications marks him as a progressive thinker and an impactful contributor in the field of artificial intelligence and computational imaging.

Publication Profile

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Educational Details

Dr. Jinfu Fan obtained his Ph.D. degree in Computer Science from Tongji University, Shanghai, one of China’s leading research universities known for its engineering and technological disciplines. During his doctoral training, he focused on advanced learning algorithms and optimization techniques, gaining strong expertise in machine learning and data-driven modeling. His academic foundation combines rigorous computational training with a deep understanding of mathematical modeling, which laid the groundwork for his current research in weakly supervised learning and super-resolution technologies. In addition to his doctoral studies, Dr. Fan further honed his academic skills through a postdoctoral or visiting scholar tenure at the National University of Singapore (NUS), a globally recognized institution in computer science and AI research. This international experience provided him with broader research exposure, particularly in collaborative and cross-disciplinary projects, and allowed him to work alongside some of the field’s top minds. His educational background not only reflects technical depth but also a proactive approach toward lifelong learning and global academic engagement. His training in both national and international settings has helped cultivate a well-rounded understanding of computer science principles and their real-world applications, making him a versatile researcher and educator in the evolving tech landscape.

Professional Experience

Assoc. Prof. Dr. Jinfu Fan is currently affiliated with the College of Computer Science Technology at Qingdao University (QU), where he serves as an Associate Professor. In this role, he is actively involved in both research and teaching, guiding undergraduate and graduate students in areas related to machine learning, computer vision, and artificial intelligence. Prior to joining QU, he completed his Ph.D. at Tongji University and enriched his professional experience as a visiting scholar at the National University of Singapore (NUS) from January to December 2022. During his time at NUS, Dr. Fan collaborated with prominent researchers at the School of Computing, which broadened his research scope and provided him with valuable international experience. At Qingdao University, he has initiated and led several research projects, including the development of image super-resolution frameworks using mutual information and diffusion models. His role as an academic also includes curriculum development, research supervision, and interdisciplinary collaboration. His professional journey reflects a strong commitment to technological advancement and academic excellence, marked by his ability to integrate research with education and translate theory into practical innovations. Dr. Fan’s progressive academic and research track record underscores his dedication to scholarly leadership in AI and computational science.

Research Interest

Dr. Jinfu Fan’s research interests span across several cutting-edge areas within artificial intelligence and computer vision. He is particularly focused on machine learning and data mining, with a growing specialization in weakly supervised multi-label learning, an area that seeks to develop intelligent systems capable of learning from limited or incomplete labeled data. This field is crucial for reducing the cost and effort associated with data annotation, making AI more accessible and scalable. In addition, Dr. Fan is extensively involved in super-resolution image reconstruction, aiming to enhance the resolution of images using deep learning techniques and novel optimization models. His recent work on MDiffSR integrates mutual information and diffusion modeling to boost image quality and reconstruction accuracy, addressing core challenges in medical imaging, remote sensing, and surveillance. He also maintains active interest in areas such as representation learning, information theory in AI, and unsupervised learning strategies. His goal is to bridge the gap between theoretical development and real-world application, and his projects frequently target practical outcomes in health diagnostics, smart cities, and digital imaging. Dr. Fan’s interdisciplinary vision and technical versatility position him at the forefront of research aimed at making AI models more robust, efficient, and interpretable.

Research Skills

Assoc. Prof. Dr. Jinfu Fan possesses a comprehensive suite of research skills in both theoretical and applied computer science. His primary strength lies in machine learning algorithm design, where he has developed and evaluated models for classification, multi-label learning, and super-resolution tasks. He is proficient in deep learning frameworks such as TensorFlow and PyTorch, which he uses to build and test neural networks tailored for image processing and representation learning. Additionally, Dr. Fan has a strong grasp of information theory, particularly mutual information, which he applies to improve learning efficiency and performance in weakly supervised environments. His research methodology is firmly rooted in rigorous mathematical modeling and statistical analysis, supported by tools like Python, MATLAB, and R. He is also skilled in experimental design and evaluation, ensuring that his studies follow reproducible and scalable processes. Moreover, his experience with image reconstruction techniques, especially in the context of the MDiffSR project, demonstrates his ability to integrate domain-specific knowledge with advanced AI models. Dr. Fan’s collaborative experience at the National University of Singapore further highlights his international research exposure and ability to work on multidisciplinary teams, equipping him with both technical and cross-cultural collaboration skills vital for modern scientific research.

Awards and Honors

While specific awards and honors are not detailed in the available records, Assoc. Prof. Dr. Jinfu Fan’s academic and research career reflects commendable achievements that position him as a strong candidate for national and international recognition. His selection as a visiting scholar at the National University of Singapore (NUS)—a prestigious institution ranked among the top in Asia for computer science—demonstrates peer recognition of his academic potential and research capabilities. His publication in Neurocomputing, a well-regarded SCI-indexed journal, adds to his credentials, showcasing his ability to contribute impactful research to the scientific community. Dr. Fan’s research project “MDiffSR: Mutual information and diffusion model in image super-resolution” represents an innovative stride in AI-based imaging solutions and has earned citation attention, indicating its influence in the academic domain. As his body of work continues to expand, it is likely that his contributions will be recognized by leading societies and research funding bodies. He is an ideal candidate for honors such as the Best Researcher Award, Excellence in Research, or Outstanding Scientist Award, given his growing research portfolio, international collaborations, and commitment to academic advancement in machine learning and computer vision.

Author Metrics

  • Total Citations: 186

  • h-index: 8
    (8 publications have at least 8 citations each)

  • i10-index: 8
    (8 publications have at least 10 citations each)

Top Noted Publication

  • A dynamic ensemble method for residential short-term load forecasting
    Author: sY. Yang, F. Jinfu, W. Zhongjie, Z. Zheng, X. Yukun
    Journal: Alexandria Engineering Journal, 2023, 
    Citations: 25

  • GraphDPI: Partial label disambiguation by graph representation learning via mutual information maximization
    Author: J. Fan, Y. Yu, L. Huang, Z. Wang
    Journal: Pattern Recognition, 2023, 
    Citations: 23

  • Spatial-frequency dual-domain feature fusion network for low-light remote sensing image enhancement
    Author: Z. Yao, G. Fan, J. Fan, M. Gan, C.L.P. Chen
    Journal: IEEE Transactions on Geoscience and Remote Sensing, 2024.
    Citations: 17

  • A new multi-source transfer learning method based on two-stage weighted fusion
    Author: L. Huang, J. Fan, W. Zhao, Y. You
    Journal: Knowledge-Based Systems, 2023, 
    Citations: 17

  • Partial label learning based on disambiguation correction net with graph representation
    Author: J. Fan, Y. Yu, Z. Wang, J. Gu
    Journal: IEEE Transactions on Circuits and Systems for Video Technology, 2021, 
    Citations: 17

Conclusion

Assoc. Prof. Dr. Jinfu Fan exemplifies a forward-thinking academic who integrates rigorous research with practical innovation in the fields of machine learning and computer vision. With a solid educational foundation from Tongji University and global exposure through his time at the National University of Singapore, he brings a well-rounded and internationally informed perspective to his work. His specialized interests in weakly supervised multi-label learning and image super-resolution position him at the cutting edge of artificial intelligence research. The MDiffSR project, as one of his leading contributions, reflects his ability to blend theory with impactful applications. At Qingdao University, he not only leads significant research initiatives but also plays a vital role in mentoring students and fostering academic excellence. His research skills, encompassing deep learning, data mining, and mathematical modeling, make him a valuable contributor to both academic and industry-oriented projects. As he continues to expand his publication record and research collaborations, Dr. Fan stands as a promising candidate for recognition in scientific innovation. His commitment to knowledge advancement, problem-solving, and global engagement makes him a distinguished figure in the AI research landscape, with continued potential to make meaningful contributions to science and society.