Nikhil Suryawanshi | Software Development | Best Researcher Award

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Mr. Nikhil Suryawanshi | Software Development | Best Researcher Award

Principal Software Engineer at ADT, United States
Summary:

Mr. Nikhil Suryawanshi is a seasoned Principal Software Engineer with extensive experience in software development, machine learning, and data analysis. His career spans over a decade, during which he has contributed to numerous high-profile projects across industries, including technology, education, and healthcare. His commitment to quality software solutions, coupled with his passion for research, positions him as a thought leader in his field. Nikhil is also actively engaged in the academic community as a peer reviewer for several international journals, including the Cureus Springer Journal and the International Journal of Innovative Research in Engineering (IJIRE). He continues to contribute to advancements in software engineering and data science.

Professional Profile:

👩‍🎓Education:

He holds two Master’s degrees: an M.S. in Technology Management from Campbellsville University, Kentucky, USA, with a CGPA of 3.5, awarded in 2019, and an M.S. in Computer Science from San Francisco Bay University, California, USA, with a CGPA of 3.94, awarded in 2016. He completed his Bachelor of Engineering in Technology at Sinhgad Academy of Engineering, Pune, India, in 2010, graduating with a CGPA of 3.50.

🏢 Professional Experience:

Nikhil Suryawanshi has amassed over 15 years of experience in the IT industry, currently serving as a Principal Software Engineer at ADT Commercial, CA, USA, since July 2019. He leads a team of eight, providing expertise in software development, project management, and training. His technical proficiencies span across Python, .Net, AngularJS, SQL, and software testing, where he has delivered high-quality software solutions and collaborated in leadership meetings to drive corporate strategy. Previously, he worked as a Senior Software Engineer at the same company, contributing to Python-based software development and network testing.

Earlier in his career, Nikhil was an Analytics Manager at IMRB Abacus, Pune, India (2014–2015), where he led data mining and analysis projects for Unilever brands using SPSS and SQL. Before that, he was an Assistant Professor at Sandip Foundation, Nashik, India (2012–2014), teaching Database Management Systems and Computer Networks, while also guiding students on final-year projects. His industry journey began as a Software Engineer at IMRB Abacus, Mumbai, India (2011–2012), where he designed online surveys and dashboards for statistical analysis.

Research Interests:

Nikhil Suryawanshi’s research interests lie in machine learning, sentiment analysis, and data clustering techniques. He is particularly focused on predictive analytics in healthcare and enhancing diagnostic capabilities using machine learning algorithms. His recent research delves into sentiment analysis with machine learning and deep learning techniques, as well as applications of clustering methods like K-Means and Gaussian Mixture Models in healthcare data.

Author Metrics:

Number of Publications: 6

Significant contributions in fields such as machine learning, healthcare, sentiment analysis, air quality prediction, and consumer behavior.

  • Accurate Prediction of Heart Disease Using Machine Learning: 2024
  • Sentiment Analysis with Machine Learning and Deep Learning: A Survey: 2024
  • Enhancing Breast Cancer Diagnosis Through Clustering: 2023
  • Predicting Mental Health Outcomes Using Wearable Device Data and Machine Learning: 2021 
  • Air Quality Prediction in Urban Environment Using IoT Sensor Data: 2020
  • Predicting Consumer Behavior in E-Commerce Using Recommendation Systems: 2019 

Top Noted Publication:

Accurate Prediction of Heart Disease Using Machine Learning: A Case Study on the Cleveland Dataset

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2024
  • Summary: This paper presents a case study on heart disease prediction using the Cleveland dataset, comparing various machine learning models to assess their accuracy and efficacy in diagnosing heart disease.

Sentiment Analysis with Machine Learning and Deep Learning: A Survey of Techniques and Applications

  • Journal: International Journal of Science and Research Archive
  • Volume: 12
  • Issue: 2
  • Pages: 005-015
  • Year: 2024
  • Summary: The paper provides a comprehensive survey of machine learning and deep learning techniques for sentiment analysis, discussing their applications and performance in various domains such as social media, e-commerce, and customer feedback.

Enhancing Breast Cancer Diagnosis Through Clustering: A Study of K-Means, Agglomerative, and Gaussian Mixture Models

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2023
  • Summary: This research explores clustering algorithms like K-Means, Agglomerative, and Gaussian Mixture Models to enhance the accuracy of breast cancer diagnosis, emphasizing the role of unsupervised learning in medical diagnostics.

Predicting Mental Health Outcomes Using Wearable Device Data and Machine Learning

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2021
  • Summary: The study investigates the application of machine learning on data collected from wearable devices to predict mental health outcomes, focusing on stress, anxiety, and other health indicators.

Air Quality Prediction in Urban Environment Using IoT Sensor Data

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2020
  • Summary: The paper discusses air quality prediction using IoT sensor data in urban areas, applying machine learning models to predict air pollution levels and analyze environmental impacts.

Predicting Consumer Behavior in E-Commerce Using Recommendation Systems

  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 4
  • Issue: 9
  • Year: 2019
  • Summary: The study focuses on predicting consumer behavior in e-commerce platforms using recommendation systems, highlighting the effectiveness of machine learning in improving customer engagement and personalization.

Conclusion:

Mr. Nikhil Suryawanshi’s strengths in software development, machine learning, and healthcare analytics, combined with his extensive professional experience, make him a solid candidate for the Best Researcher Award. His technical expertise and contributions to the IT and academic communities are commendable. However, expanding his research impact through more collaborative efforts and publishing in top-tier journals could further enhance his candidacy for such an award. Overall, Nikhil is a deserving candidate, particularly given his innovative work in healthcare and predictive analytics.

 

 

 

ShivaDutt Jangampeta | Machine Learning | Industry Innovation Research Award

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Mr. ShivaDutt Jangampeta, Machine Learning, Industry Innovation Research Award

ShivaDutt Jangampeta at JP Morgan Chase, United States

Mr. ShivaDutt Jangampeta appears to be a highly experienced professional with a strong background in cybersecurity, specifically in Security Information and Event Management (SIEM). However, determining his suitability for the “Research for Community Impact Award” requires an assessment of how his work impacts the community.

Relevant Criteria for the Research for Community Impact Award:

Community Impact: The award typically recognizes research that has a significant positive impact on the community, either through direct application or through contributions to knowledge that benefit the community.

Innovation and Advancement: Contributions to advancing the field and introducing innovative solutions or methodologies.

Collaboration and Dissemination: Engagement with stakeholders and dissemination of research findings to a broader audience.

Evaluation of Mr. Jangampeta’s Suitability:

Strengths:

Professional Experience:

  • Extensive experience in managing and optimizing SIEM systems.
  • Leadership roles in cybersecurity teams at major organizations like JPMorgan Chase and PEPSICO.
  • Development and implementation of advanced cybersecurity measures that could indirectly benefit community security by protecting sensitive data and reducing vulnerabilities.

Research Contributions:

  • Authored several publications related to data security, SIEM, and compliance, indicating a contribution to academic knowledge.
  • Research topics like anomaly detection in SIEM and the role of data security in compliance suggest a focus on enhancing cybersecurity frameworks, which can have broad implications for community safety and trust in digital systems.

Innovative Solutions:

  • Implementation of advanced technologies and automation in cybersecurity, contributing to more resilient and efficient security infrastructures.

Areas to Consider:

Direct Community Impact:

  • While Mr. Jangampeta’s work in cybersecurity is crucial, the direct impact on the community might be less apparent compared to other fields such as public health or environmental science.
  • It would be beneficial to highlight specific examples or case studies where his work directly protected community members or contributed to public safety.

Engagement and Dissemination:

  • The extent of his engagement with community stakeholders and efforts to disseminate his research findings to a broader, non-technical audience would strengthen his case for this award.

Conclusion:

Mr. Jangampeta’s extensive experience and contributions to the field of cybersecurity are impressive and certainly valuable. His work indirectly impacts the community by enhancing the security of digital infrastructures, which is increasingly important in today’s interconnected world. To bolster his application for the Research for Community Impact Award, it would be advantageous to emphasize any direct community benefits resulting from his cybersecurity initiatives and any outreach efforts he has made to educate or involve the community in his work.

If his research and professional activities can be framed to clearly demonstrate significant, tangible benefits to the community, Mr. Jangampeta could be a suitable candidate for the award.

 

Gaurav Sinha | Data Interpretation | Best Researcher Award

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Mr. Gaurav Sinha, Data Interpretation, Best Researcher Award

Gaurav Sinha at Amazon Web Services, United States

Summary:

Mr. Gaurav Sinha is a highly skilled Database Specialist with a strong background in cloud migrations, database architecture, and performance optimization. With a Bachelor of Engineering from BIT Mesra Ranchi and a series of AWS certifications, he possesses comprehensive expertise in designing and implementing database solutions on AWS. His experience spans from troubleshooting complex database issues to architecting large-scale, mission-critical environments. Mr. Sinha’s dedication to excellence and his ability to deliver innovative solutions make him a valuable asset in the field of cloud computing and database management.

Professional Profile:

👩‍🎓Education:

Bachelor of Engineering

  • BIT Mesra Ranchi

Professional Experience:

Mr. Gaurav Sinha is a seasoned Database Specialist with extensive experience in cloud migrations, database architecture, and performance optimization. Currently serving as a Senior Database Migration Consultant at Amazon Web Services in Houston, TX, he provides expertise on heterogeneous database migrations to AWS, designs migration solutions for customer databases, and addresses complex challenges around large-scale cloud migrations. He takes ownership of end-to-end delivery of migration projects, profiles and benchmarks customer databases, and identifies performance bottlenecks. His role involves architecting optimal AWS infrastructure and tuning database platform configurations for post-migration performance.

Prior to his role at AWS, Mr. Sinha worked as a Senior Database Administrator at Tata Consultancy Services, where he honed his skills in database tuning, troubleshooting, and migration. He designed and implemented data modeling, data warehouses, and provided intensive support for Oracle databases. His responsibilities included performance tuning, backup and recovery, and root cause analysis of internal errors. He also led the migration of databases to AWS RDS and VMs hosting databases to AWS EC2.

Research Interest:

Database Migration Strategies: Investigating various approaches and methodologies for migrating databases to cloud platforms like AWS, focusing on optimizing performance, minimizing downtime, and ensuring data integrity during the migration process.

Performance Optimization in Cloud Databases: Exploring techniques to optimize the performance of databases hosted on cloud platforms, such as fine-tuning database configurations, optimizing query execution plans, and leveraging cloud-native features for scalability and performance.

Data Security and Compliance in Cloud Environments: Researching best practices and technologies for ensuring data security, privacy, and compliance with regulatory requirements (such as GDPR or HIPAA) in cloud-based database environments, including encryption, access control, and auditing mechanisms.

Scalability and Elasticity of Cloud Databases: Investigating strategies for designing and managing highly scalable and elastic databases in cloud environments, including auto-scaling, sharding, and distributed database architectures.

Hybrid Cloud Database Solutions: Studying hybrid cloud architectures that integrate on-premises databases with cloud-based solutions, examining challenges and opportunities related to data synchronization, data consistency, and workload management across hybrid environments.

Database-as-a-Service (DBaaS) Models: Analyzing the benefits and challenges of adopting DBaaS models, such as managed database services offered by cloud providers, and investigating factors influencing organizations’ decisions to migrate to DBaaS solutions.

Machine Learning Applications in Database Management: Exploring the use of machine learning techniques for optimizing database performance, automating database administration tasks, and detecting anomalies or security threats in database systems.

Top Noted Publication:

Automating Root Cause Analysis of Refinery Incidents via Generative Deep Learning and Data Analytics

  • Author: GK Sinha
  • Journal: Journal of Technological Innovations
  • Volume: 4
  • Issue: 2
  • Year: 2023

Data Analytics-Enhanced Cloud-Native Computational Reservoir Simulation for Accelerated Oil Prospecting

  • Author: GK Sinha
  • Journal: Journal of Technological Innovations
  • Volume: 4
  • Issue: 2
  • Year: 2023

Utilizing Data Analytics in Computer Vision and Robotics for Autonomous Pipeline Integrity Inspections

  • Author: GK Sinha
  • Journal: Journal of Technological Innovations
  • Volume: 4
  • Issue: 1
  • Year: 2023

Data Analytics-Driven Optimization of Gas Lift Operations Using Reinforcement Learning for Increased Production Efficiency

  • Author: GK Sinha
  • Journal: Journal of Technological Innovations
  • Volume: 2
  • Issue: 4
  • Year: 2021

Developing a Data Analytics Framework for Environmental Impact Assessment and Carbon Footprint Reduction in Upstream Operations

  • Author: GK Sinha
  • Journal: Journal of Technological Innovations
  • Volume: 2
  • Issue: 1
  • Year: 2021

Sadaf Haiyat | Cancer Diagnosis | Best Researcher Award

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Assist Prof Dr. Sadaf Haiyat , Cancer Diagnosis, Best Researcher Award

Assistant Professor at Mahamana Pandit Madan Mohan Malviya Cancer Centre /Tata Memorial Hospital Varanasi, India

Summary:

Dr. Sadaf Haiyat is a distinguished pathologist with extensive expertise in hematology, clinical pathology, and molecular pathology. With an MD in Pathology from Aligarh Muslim University, Dr. Haiyat has over seven years of experience in various pathology disciplines, including significant post-MD roles. Notably, Dr. Haiyat has contributed to the field through independent research on Syndecan-1 as a diagnostic biomarker, which has been published as a book. Currently serving as a Consultant Pathologist and Assistant Professor at Tata Memorial Cancer Centre/MPMMCC in Varanasi, Dr. Haiyat is recognized for excellence in pathology practice, quality control, and medical education. Dr. Haiyat has received multiple awards, including the “Young Clinician in Pathology Award” and accolades for research presentations and diagnostic challenges.

Professional Profile:

👩‍🎓Education:

  • MD (Pathology): 2016, Aligarh Muslim University (AMU), Aggregate – 66%
  • MBBS: 2011, Aligarh Muslim University (AMU), Aggregate – 60%

Professional Experience:

Dr. Sadaf Haiyat has a total of 7 years of professional experience in pathology, including 4.5 years post-MD. During her tenure as a Junior Resident at J.N.M.C.H, A.M.U, Aligarh from June 2013 to June 2016, she gained extensive experience teaching undergraduate MBBS and BDS students, conducting practical classes, and participating actively in postgraduate seminars and journal clubs. Her work encompassed a broad range of pathology disciplines, including hematology, leukemia and cytochemistry reporting, peripheral smears, bone marrow aspiration and biopsy reporting, coagulation studies, anemia profile, clinical pathology, chemical pathology, immunology, serology, blood bank, and histopathology.

From April 2017 to April 2020, Dr. Haiyat served as a Senior Resident / Demonstrator at the same institution, where she further honed her skills in hematology, hemato-oncopathology, chemical pathology, clinical pathology, blood bank/transfusion medicine, histopathology, and cytopathology, with additional expertise in frozen sections and immunofluorescence.

As a Laboratory Head and Consultant Pathologist at Popular Multispeciality Hospital, Varanasi, U.P. from August 2020 to May 2021, Dr. Haiyat supervised and approved reports in hematology, biochemistry, clinical pathology, body fluids, and immunology, ensuring strict adherence to quality control measures and ISO 150189:2012 guidelines. She also participated in the administration and management of the laboratory, including the training of technicians and staff.

In her subsequent role as a Consultant Pathologist at Dr. Lal Path NRL, Reference Lab, New Delhi from August 2021 to February 2021, Dr. Haiyat independently reported on various pathology disciplines including hematology, peripheral smears, bone marrow aspiration, biopsies, clinical pathology, cytopathology, histopathology, and oncopathology.

Currently, Dr. Haiyat serves as a Consultant Pathologist and Assistant Professor at Tata Memorial Cancer Centre/MPMMCC, Varanasi, Uttar Pradesh, where she has started a Molecular Pathology Lab. Her responsibilities include independently reporting on histopathology, oncopathology, hematology, hemato-oncology, peripheral smears, cytochemistry, bone marrow aspiration, biopsies, immunophenotyping interpretation, and coagulation testing. Additionally, she supervises audits for NABL Pathology, participates in EQAS of CAP and NABL, and is involved in multidisciplinary meetings, training of residents and technical staff, teaching, research, and administrative work.

Research Interest:

  • Hematology and Hemato-Oncopathology
  • Diagnostic Biomarkers
  • Clinical and Chemical Pathology
  • Cytopathology and Histopathology
  • Molecular Pathology
  • Blood Bank and Transfusion Medicine
  • Quality Control in Pathology Laboratories

Awards:

“Young Clinician in Pathology Award” at the 2nd Annual Medical Summit and Venus International Medical Awards, Park Hyatt, Chennai, 6th April 2019.

World Championship 2018 in Hematology for the research article titled “A challenging case of Hemophilia A with first presentation at the age of 16 as monoarticular hemophiliac arthropathy: A diagnostic enigma” by the Journal for Hematology.

1st Prize in Oral Paper Presentation on “A Cytological and Histomorphological Case Study Of an Unusual Occurrence of Gonadoblastoma with Seminoma and Yolk Sac Tumor In An Anatomically Normal Male Child” at UP CYTOCON 2015, 3rd Annual Conference Of Indian Academy Of Cytopathologists, 13th September 2015.

Best Poster Award entitled “Cryptococcal Meningitis Presenting As Multiple Fractures in an Immunocompetent Individual-An Unusual Presentation” at NEUROCON 2015, XXI Annual Conference of Neuroscience Society (UP & UK), J.N.M.C, A.M.U., Aligarh, 14th February 2015.

3rd Prize in Poster Presentation on “Primary Lymphoma of Bone: An Oncological Paradox” at the International Symposium on Oncologic Pathology, Department of Pathology, J.N.M.C, A.M.U., Aligarh, 25th January 2018.