Dr. Tahera Kalsoom | Industrial IoT | Best Researcher Award

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Dr. Tahera Kalsoom | Industrial IoT | Best Researcher Award 

Dr. Tahera Kalsoom, Manchester Metropolitan University, United Kingdom

Dr. Tahera Kalsoom is a dedicated lecturer and researcher with over five years of experience in teaching undergraduate and postgraduate courses. She has supervised more than 100 theses and published 14 articles in leading journals and conferences. Her research focuses on the Internet of Things (IoT), Industry 4.0/5.0, data analytics, digitalization, firm performance, and technology management. Dr. Kalsoom holds a Ph.D. in Computing, Engineering, and Physical Sciences from the University of the West of Scotland, where her thesis explored the impact of IoT and dynamic data processing on firm performance. She has also earned an MSc in Financial Management from Middlesex University and a BBA in International Hospitality Management from Stenden University. In addition to her teaching roles at Manchester Metropolitan University and other institutions, Dr. Kalsoom actively contributes to the academic community as a reviewer for various journals and conferences, including IEEE and Wiley & Sons. She is a member of several professional organizations, including IEEE, the British Academy of Management, and the American Finance Association.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award: Dr. Tahera Kalsoom

Dr. Tahera Kalsoom is highly suitable for the Best Researcher Award based on her outstanding interdisciplinary research profile, international academic exposure, and clear contributions to emerging domains such as the Internet of Things (IoT), Industry 4.0/5.0, and Data Analytics. With a Ph.D. from a reputable UK institution and over 14 research publications in well-regarded journals and conferences, she demonstrates a consistent research trajectory aligned with modern technological transformations impacting firm performance and digitalisation.

🎓 Education

  • PhD in Computing, Engineering and Physical Sciences
    University of the West of Scotland, Glasgow, UK (2017–2021)
    📘 Thesis: Impact of the Use of IoT, Visibility and Dynamic Data Information Processing Capabilities on Firm Performance

  • MSc in Financial Management
    Middlesex University, London, UK (2014–2015)
    📘 Thesis: Performance of banks after the financial recession, a study of market trends

  • BBA (Hons) in International Hospitality Management
    Stenden University, Qatar (2006–2010)
    📘 Dissertation: Performance analysis of Vodafone call centre in Doha

💼 Professional Experience

  • Lecturer
    Manchester Fashion Institute, MMU, UK (2022–Present)
    📊 Teaching Business Analytics, Strategic Fashion Management, supervising PG students, and PhD co-supervision.

  • Associate Lecturer
    Arden University, Manchester, UK (2022)
    🖥️ Delivered courses on Data Analytics, Operations Management, and Digital Supply Chain 4.0.

  • Research Assistant
    University of the West of Scotland, UK (2021–2022)
    🧠 Contributed to IoT frameworks for EU projects ATHIKA and Safe-RH.

  • Associate Lecturer
    UWS, School of Business and Creative Industries (2020–2021)
    🧾 Delivered tutorials and designed assessments in Operations Management.

  • Lecturer
    ICON College, London, UK (2019–2020)
    🌐 Led IoT module, attended exam boards, and taught Project Management & Strategic Management.

  • Lecturer
    St. Patrick’s College, London, UK (2018–2019)
    🏫 Delivered lectures in HR, Leadership, and Operations Management.

  • Assistant Manager
    M.H. AL-Muftah Est., Doha, Qatar (2016–2017)
    📈 Handled payroll, financial audits, and reporting.

  • Payroll Administrator
    Hamad Int. Airport Project, Civil Aviation Authority, Qatar (2010–2014)
    💼 Managed payroll processing, appraisals, and timesheets.

🌟 Key Achievements

  • 📚 Supervised 100+ UG and PG theses

  • 📝 Published 14 research articles in reputable journals and conferences

  • 🔍 Regular reviewer for journals such as IEEE Access, IEEE Sensors Journal, Sensors (MDPI), Sustainability, and Wiley Books

  • 🎤 TPC Member for IEEE CAMAD, BAM, LRN, and UK-China Emerging Tech Conference

  • 🧑‍🏫 Module Leader and Exam Board Member at ICON and St. Patrick’s Colleges

  • 📦 Developed modules on IoT and Digital Supply Chain 4.0

🏅 Awards & Honours

  • 🥇 Merit Award – Top 20 MSc students, Middlesex University

  • 🏆 Distinction Award – Top 10 in BBA, Stenden University

  • 🎓 First Class Scholarship – Stenden University

  • 📜 Roll of Honour – Top 20 in HSSC, PEC Doha

Publication Top Notes:

Advances in sensor technologies in the era of smart factory and industry 4.0

CITED:325

Impact of IoT on manufacturing industry 4.0: A new triangular systematic review

CITED:112

Towards supply chain visibility using internet of things: A dyadic analysis review

CITED:107

IoT for 5G/B5G applications in smart homes, smart cities, wearables and connected cars

CITED:46

Market orientation and SME performance: Moderating role of IoT and mediating role of creativity

CITED:43

Millimeter-wave smart antenna solutions for URLLC in industry 4.0 and beyond

CITED:42

 

 

 

Dr. Samprit Banerjee | Sensor integration Awards | Excellence in Innovation

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Dr. Samprit Banerjee | Sensor integration Awards | Excellence in Innovation

Dr. Samprit Banerjee, Weill Medical College of Cornell University, United States

Dr. Samprit Banerjee is an Associate Professor of Biostatistics at the Weill Medical College of Cornell University, where he has held various academic appointments since 2011. He currently serves as an Associate Professor in both the Division of Biostatistics and the Department of Psychiatry, as well as the Director of the PhD program in Population Health Sciences. Dr. Banerjee’s expertise lies in biostatistics, data science, and epidemiology, with a focus on statistical methods for health research and healthcare policy. He is also a Special Government Employee at the FDA, contributing to the Center for Devices and Radiological Health. Dr. Banerjee has a distinguished academic background, holding a B.Stat and M.Stat from the Indian Statistical Institute, Kolkata, and a PhD in Biostatistics from the University of Alabama at Birmingham. His teaching experience includes directing multiple graduate-level courses in biostatistics, statistical learning, and big data in medicine. Throughout his career, he has mentored numerous junior researchers and contributed to the development of MS and PhD programs in Biostatistics and Data Science. Dr. Banerjee has also served as an elected representative for the Mental Health Statistics Section of the American Statistical Association.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Excellence in Innovation

Samprit Banerjee, PhD, is highly suitable for the “Research for Excellence in Innovation” award based on his extensive academic background, research contributions, and leadership roles in biostatistics, epidemiology, and data science. His expertise in high-dimensional data analysis, machine learning, and multivariate statistics, combined with his significant contributions to medical and healthcare research, makes him a standout candidate.

Education:

  • 1998-2001: B.Stat (Bachelors in Statistics), Indian Statistical Institute, Kolkata, India
  • 2001-2003: M.Stat (Masters in Statistics), Indian Statistical Institute, Kolkata, India
  • 2003-2008: PhD in Biostatistics, Department of Biostatistics, University of Alabama at Birmingham

Work Experience:

  • Jan 2020 – Present: Associate Professor, Division of Biostatistics, Department of Population Health Sciences, Weill Medical College, Cornell University, New York, NY
  • May 2023 – Present: Associate Professor of Biostatistics, Department of Psychiatry, Weill Medical College, Cornell University, New York, NY
  • Jan 2018 – Jan 2020: Associate Professor, Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Medical College, Cornell University, New York, NY
  • Jan 2018 – Present: Adjunct Associate Professor, Department of Statistics and Data Science, Cornell University, Ithaca, NY
  • Nov 2020 – Present: Director (Founding) of PhD Program in Population Health Sciences, Department of Population Health Sciences, Weill Medical College, Cornell University, New York, NY
  • 2014 – Present: Special Government Employee, Center for Devices and Radiological Health (CDRH), Food and Drug Administration (FDA), Silver Springs, MD
  • 2022 – 2024: Elected Council of Sections Representative for the Mental Health Statistics Section of American Statistical Association (ASA)

Past Positions:

  • 2016 – 2020: Director (Founding) of MS Program in Biostatistics & Data Science, Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Medical College, Cornell University, New York, NY
  • May 2011 – Dec 2017: Assistant Professor, Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Medical College, Cornell University, New York, NY
  • May 2011 – Dec 2017: Adjunct Assistant Professor, Department of Statistical Science, Cornell University, Ithaca, NY
  • Aug 2008 – May 2011: Instructor, Division of Biostatistics and Epidemiology, Department of Public Health, Weill Medical College of Cornell University, New York, NY
  • Jun 2005 – Aug 2008: Graduate Research Assistant, Department of Biostatistics, University of Alabama, Birmingham (Supervisor: Dr. Nengjun Yi) – Developed Bayesian methods for detecting gene by gene and gene by environment interactions for QTLs in inbred mice.
  • Aug 2003 – Jun 2005: Graduate Research Assistant, Department of Biostatistics, University of Alabama at Birmingham (Supervisor: Dr. Varghese George) – Worked on Marginal Structural Models to investigate genetic effects in AIDS and developed Bayesian methods for QTL detection in Human Genetics.

Publication top Notes:

Perioperative comparative effectiveness of anesthetic technique in orthopedic patients

CITED:581

Rearrangements of the RAF kinase pathway in prostate cancer, gastric cancer and melanoma

CITED:556

Mechanism-based epigenetic chemosensitization therapy of diffuse large B-cell lymphoma

CITED:219

Epigenetic repression of miR-31 disrupts androgen receptor homeostasis and contributes to prostate cancer progression

CITED:195

Elevated prefrontal cortex GABA in patients with major depressive disorder after TMS treatment measured with proton magnetic resonance spectroscopy

CITED:156

R/qtlbim: QTL with Bayesian interval mapping in experimental crosses

CITED:153

 

Mr Anandarup Roy | Internet of Things | Best Researcher Award

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Mr Anandarup Roy| Internet of Things | Best Researcher Award

Mr Anandarup Roy,Senior Research Fellow, Indian Statistical Institute, Kolkata,India

Anandarup Roy is a Ph.D. candidate in Computer Science at the Indian Statistical Institute (ISI), Kolkata, specializing in combinatorial secret sharing. His thesis was submitted on July 19, 2024, and he expects to receive his degree by December 2024. He is advised by Prof. Bimal Kumar Roy and co-supervised by Prof. Mridul Nandi, both from the Applied Statistics Unit at ISI.

Professional Profile:

Summary of Suitability for the Best Researcher Award:

Anandarup Roy, a Ph.D. candidate at the Indian Statistical Institute, has made significant contributions to the field of computer science, particularly in combinatorial secret sharing. His research extends previous work in Bayesian incentive-compatible mechanism design and social learning, demonstrating a robust understanding of complex statistical models and their applications.

Education

He Naifeng is pursuing a PhD at the prestigious Nanjing University of Aeronautics and Astronautics, where he has built a strong foundation in automation and robotics. His academic journey reflects a commitment to advancing technology in mobile robotics, demonstrating a keen interest in both theoretical knowledge and practical applications.

Work Experience

From 2016 to 2018, Anandarup worked as a project-linked person at the Economics Research Unit of ISI, where he contributed to a project on Bayesian incentive-compatible mechanism design under the supervision of Prof. Manipushpak Mitra. This research extended his master’s thesis by examining learning processes in a social choice environment with risk-neutral agents.

Skills

Anandarup is proficient in using Linux OS (Ubuntu) and LaTeX. He possesses basic programming knowledge in C, making him well-equipped for computational tasks related to his research.

Research Focus

His research focuses on autonomous navigation for wheel-legged robots, with particular emphasis on reinforcement learning in control systems and intelligent motion control. He aims to develop practical applications that enhance the performance and adaptability of mobile robots in challenging environments.

Publication top Notes:

  • Combining Dynamic Selection and Data Preprocessing for Imbalance Learning
    Year: 2018
    Journal: Neurocomputing
    Volume/Pages: 286, 179-192
  • SVM-based Hierarchical Architectures for Handwritten Bangla Character Recognition
    Year: 2009
    Journal: International Journal on Document Analysis and Recognition (IJDAR)
    Volume/Pages: 12, 97-108
  • Lecithin and Venom Haemolysis
    Year: 1945
    Journal: Nature
    Volume/Pages: 155 (3945), 696-697
  • A Novel Approach to Skew Detection and Character Segmentation for Handwritten Bangla Words
    Year: 2005
    Journal: Digital Image Computing: Techniques and Applications (DICTA’05)
    Pages: 30-30
  • JCLMM: A Finite Mixture Model for Clustering of Circular-Linear Data and Its Application to Psoriatic Plaque Segmentation
    Year: 2017
    Journal: Pattern Recognition
    Volume/Pages: 66, 160-173
  • An HMM Framework Based on Spherical-Linear Features for Online Cursive Handwriting Recognition
    Year: 2018
    Journal: Information Sciences
    Volume/Pages: 441, 133-151
  • Pair-Copula Based Mixture Models and Their Application in Clustering
    Year: 2014
    Journal: Pattern Recognition
    Volume/Pages: 47 (4), 1689-1697
  • Character Segmentation for Handwritten Bangla Words Using Artificial Neural Network
    Year: 2005
    Journal: Proceedings of the 1st IAPR TC3 NNLDAR
  • SWGMM: A Semi-Wrapped Gaussian Mixture Model for Clustering of Circular–Linear Data
    Year: 2016
    Journal: Pattern Analysis and Applications
    Volume/Pages: 19, 631-645
  • Headline Based Text Extraction from Outdoor Images
    Year: Not specified (conference paper)
    Journal: Pattern Recognition and Machine Intelligence: 4th International Conference