Balaji Srinivasan | Machine Learning Method | Best Researcher Award

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Mr. Balaji Srinivasan | Machine Learning Method | Best Researcher Award

Balaji Srinivasan at Engineers India Limited, India

Summary:

Balaji Srinivasan is a seasoned analyst with over 16 years of experience in the refinery and petrochemical industries. Specializing in asset lifecycle management and local stress analysis, he has played a pivotal role in ensuring the safety and reliability of complex systems. His expertise in finite element analysis and advanced technology development has earned him recognition in the field.

Professional Profile:

πŸ‘©β€πŸŽ“Education:

Balaji Srinivasan holds a solid educational foundation in engineering, specializing in fields pertinent to the refinery and petrochemical industries. His education laid the groundwork for a successful career in managing complex projects and conducting advanced technology development activities.

🏒 Professional Experience:

With over 16 years of experience, Balaji Srinivasan has made significant contributions to the refinery and petrochemical sectors. He has been with Engineers India Limited in New Delhi since September 2007, where he specializes in local stress analysis. His expertise extends to conducting advanced technology development activities, including transient thermal and creep-fatigue interaction studies.

Balaji has executed finite element, fatigue, creep, and creep-fatigue analyses for pressure vessels and piping components, including high-pressure and high-temperature reactors, coke drums, dryers, and agitator vessels. He has led complex equipment troubleshooting exercises, ensuring safe and reliable plant operations through numerical simulations to identify root causes of fault sequences and performing fitness-for-service assessments on critical components.

Balaji’s knowledge of FEA software like ABAQUS and ANSYS has been instrumental in solving unconventional, complex, and multidisciplinary problems arising from pre- and post-commissioning activities. His interactive management approach has enhanced output, maximized quality, and increased employee satisfaction.

Research Interests:

Balaji’s research interests lie in asset lifecycle management, design basis assessment, local stress analysis, and advanced technology development for the refinery and petrochemical industries. He is particularly focused on enhancing the reliability and safety of critical infrastructure through innovative analysis and simulation techniques.

Author Metric:

Balaji Srinivasan has contributed to several industry-related publications and research projects. His work is well-regarded in the field of stress analysis and lifecycle management, with a focus on enhancing system reliability and safety. His publications have garnered citations, reflecting the impact of his research on the industry.

Top Noted Publication:

1. Strain engineering and one-dimensional organization of metal–insulator domains in single-crystal vanadium dioxide beams

  • Authors: J. Cao, E. Ertekin, V. Srinivasan, W. Fan, S. Huang, H. Zheng, J.W.L. Yim, et al.
  • Journal: Nature Nanotechnology
  • Volume: 4
  • Issue: 11
  • Pages: 732-737
  • Year: 2009
  • DOI: 10.1038/nnano.2009.266
  • Citations: 676

2. Mechanism of thermal reversal of the (fulvalene) tetracarbonyldiruthenium photoisomerization: toward molecular solar–thermal energy storage

  • Authors: Y. Kanai, V. Srinivasan, S.K. Meier, K.P.C. Vollhardt, J.C. Grossman
  • Journal: Angewandte Chemie International Edition
  • Volume: 49
  • Issue: 47
  • Pages: 8926-8929
  • Year: 2010
  • DOI: 10.1002/anie.201003643
  • Citations: 136

3. Proton momentum distribution in water: an open path integral molecular dynamics study

  • Authors: J.A. Morrone, V. Srinivasan, D. Sebastiani, R. Car
  • Journal: The Journal of Chemical Physics
  • Volume: 126
  • Issue: 23
  • Pages: 234504
  • Year: 2007
  • DOI: 10.1063/1.2746330
  • Citations: 90

4. Interplay between intrinsic defects, doping, and free carrier concentration in SrTiO₃ thin films

  • Authors: E. Ertekin, V. Srinivasan, J. Ravichandran, P.B. Rossen, W. Siemons, et al.
  • Journal: Physical Review Bβ€”Condensed Matter and Materials Physics
  • Volume: 85
  • Issue: 19
  • Article: 195460
  • Year: 2012
  • DOI: 10.1103/PhysRevB.85.195460
  • Citations: 56

5. Exploring the potential of fulvalene dimetals as platforms for molecular solar thermal energy storage: computations, syntheses, structures, kinetics, and catalysis

  • Authors: K. BΓΆrjesson, D. Δ†oso, V. Gray, J.C. Grossman, J. Guan, C.B. Harris, et al.
  • Journal: Chemistry–A European Journal
  • Volume: 20
  • Issue: 47
  • Pages: 15587-15604
  • Year: 2014
  • DOI: 10.1002/chem.201402857
  • Citations: 44

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.

 

Yogesh | Artificial Intelligence

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Dr. Yogesh: Leading Researcher in Artificial Intelligence

Congratulations to Dr. Yogesh on Winning the Best Researcher Award! Dr. Yogesh is a dedicated researcher known for his impactful contributions to the field of Artificial Intelligence. His commitment to research, mentorship, and collaboration with international teams has earned him this prestigious recognition.

Dr. Yogesh is a distinguished researcher in the field of Artificial Intelligence, recognized for his outstanding contributions and achievements. Currently serving as Assistant Professor-III in the Department of Computer Science and Engineering at Chitkara University, Punjab, he brings a wealth of experience and expertise to his role.

Professional Profile:

πŸŽ“ Educational Qualifications:

  • Ph.D.: Amity University Uttar Pradesh, Noida, 2021
  • M. Tech: Amity University Uttar Pradesh, Noida, 2013 (84.7%)
  • B. Tech: Magadh University, Patna, 2007 (76%)

Gayan KIncy Kulatilleke | Machine learning

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Dr. Gayan KIncy Kulatilleke: Leading Researcher in Machine learning, AI

Dr. Gayan Kincy Kulatilleke is a distinguished researcher and expert in the field of Artificial Intelligence and Machine Learning. Holding a Ph.D. in AI, M.Sc. degrees in Big Data and Networking, and a B.Sc. in Engineering, he has garnered recognition for his outstanding contributions to the field.

As a leading academic at the University of Queensland, Brisbane, Dr. Kulatilleke serves as a Sessional Academic and Research Assistant, specializing in Computer Networks and High-Performance Computing. He also plays a pivotal role as an AI/ML Mentor for Summer and Internship Projects, showcasing his dedication to nurturing the next generation of innovators.

πŸŽ“ Education

  • PhD(AI), MSc(Big Data), MSc(Networking), BSc(Eng.), ACMA(UK), CGMA(USA), AMIE(SL)

πŸ† Awards

  • Best Paper: Microsoft Award (Cybersecurity, HFES 2020)
  • Best Paper: CSIRO Award (AJCAI 2022)
  • “Global Knowledge Sharing” Award for Best Technical Publication (Virtusa 2003)
  • Runner Up: cmbHack.js 2014 (48-hour JavaScript Hackathon)
  • Multiple Australian Scholarships: UQ RTP, ARC LP for PhD

Professional Profiles:

Publication Top Noted

  • XG-BoT: An explainable deep graph neural network for botnet detection and forensics
  • HFE and cybercrime: Using systems ergonomics to design darknet marketplace interventions
  • Efficient block contrastive learning via parameter-free meta-node approximation
  • Inspection-L: self-supervised GNN node embeddings for money laundering detection in bitcoin
  • DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection

Research FocusΒ 

Dr. Gayan Kincy Kulatilleke’s research encompasses a broad spectrum within the realms of Artificial Intelligence (AI) and Machine Learning (ML). While specific details of his research focus might require more recent information, the provided details indicate several areas of interest and expertise:

  1. Botnet Detection and Forensics
  2. Human Factors Engineering (HFE) and Cybercrime
  3. Contrastive Learning for Efficient Block Analysis
  4. Self-Supervised Learning for Money Laundering Detection
  5. Hybrid Deep Learning for Network Anomaly Detection

πŸ’Ό Work Experience

University of Queensland, Brisbane

  • Sessional Academic & Research Assistant (01/2019 – Present)
    • Lead Tutor: Computer Networks, High-Performance Computing
    • AI/ML Mentor for Summer and Internship Projects
    • Presenter: High-Performance Compute GPU Clusters, ML Pipelines

Freelance AI ML and Software Consultant/Developer, Remote (01/2006 – Present)

  • Advanced skills in C++, OS, Automation, Integration, DevOps, Cloud Management, Google Technologies, Data Engineering, Software Development, AI/ML.

Mailot – Founder CTO, Brisbane (01/2023 – 06/2023)

  • GPT-3 Productivity SaaS Startup
  • NLP and Human Inputs for Augmented Responses
  • Integration of OpenAI, Langchain, Vector Databases with Node.js on Vercel

AMZ Consulting Pty Ltd, Sydney – Consultant/Trainer (05/2023 – Present)

  • PowerBI, Modelling, DAX, Integrations

TeleMARS, Brisbane – Lead AI ML Engineer and Researcher (04/2023 – Present)

  • AI Architecture Design, AI Analytics Solution Design
  • Development and Solution Delivery Management

Space Platform, Brisbane – Head ML (06/2019 – 06/2020)

  • Privacy Preserving Query and Intent Identification Algorithms
  • Research on IOS and Android’s Randomized MAC Addresses
  • Data Engineering, ETL Operations, ML Model Design and Implementation

Capital Staffing, London – Software Developer (10/2017 – 07/2018)

  • C#, .NET MSSQL Server, DevOps, Cloud Services

Central Bank of Sri Lanka – Senior Assistant Director (05/2005 – 10/2022)

  • AI ML Big Data Initiatives
  • Data Science and Analysis Teams Coaching
  • Implementation of Strategic IT Needs
  • Surveillance, Authentication, Access Control Systems Oversight

Virtusa Corporation, Colombo – Software Engineer (R&D) (05/2004 – 08/2004)

  • Managed R&D Portal, Global Technology Center Consultation
  • “Global Knowledge Sharing” Award for Best Technical Whitepaper

MillenniumIT (London Stock Exchange Group) – Application Engineer (08/2003 – 05/2004)

  • Global Support, Technical Advice to Capital Market Clients
  • Performance Benchmarking, Real-time Multithreaded C/C++ Code Development

πŸŽ“ Educational/Professional Qualifications

  • PhD Candidate, Tutor, Research Assistant, University of Queensland (2019 – 2023)
  • MSc Big Data Science, Queen Mary, University of London (2017 – 2018)
  • MSc Computer Science, Networking, University of Moratuwa, Sri Lanka (2004 – 2006)
  • BSc Computer Science & Engineering, University of Moratuwa, Sri Lanka (1999 – 2003)

πŸ† Special Achievements/Publications

  • Google Research Profile: Link
  • “Microsoft Best Paper Award: Cybersecurity Technical Group” (2020)
  • “Global Knowledge Sharing” Award for Best Technical Publication (Virtusa 2003)

🀝 Positions of Responsibility

  • International Reviewer – Multiple AI ML Journals (2022 – Onwards)
  • Operational Committee Member – WiT Cyber Review Committee, Queensland (2023 – 2024)
  • Coordinator – Chess & Drafts Games, Central Bank Recreation Club (2010 – 2017)
  • Chief Examiner – Institute of Bankers, Sri Lanka (2009 – 2017)
  • Volunteer Work with ADB to Create Computer-Aided Educational Software for Schools (2004)

πŸ“š Lateral Courses Completed

  • Macro Econometric Forecasting, IMF, Institute for Capacity Development, 2016
  • Financial Programming and Policies, Part 2: Program Design, IMF, 2012

πŸ† Skills

  • Data, AI, Machine Learning Engineering
  • Software Development (Python, C++, C#)
  • AI ML (GPTx, Langchain Models, TensorFlow)
  • DevOps and Cloud Management (Azure, AWS)
  • Google Technologies (Data Studio, Firebase, Cloud Firestore)
  • Data Engineering (PowerBi, Tableau, DAX, Python-based Web Scraping)

πŸŽ‰ Awards and Recognitions

  • Best Paper Awards (Microsoft, CSIRO)
  • Global Knowledge Sharing Award (Virtusa)
  • Australian Scholarships (UQ RTP, ARC LP)