Maksym Lupei | Predictive Analytics | Best Paper Award

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Dr. Maksym Lupei | Predictive Analytics | Best Paper Award

Doctorate at The Pennsylvania State University, United States

Summary:

Dr. Maksym Lupei is a dedicated researcher and academic with extensive expertise in machine learning and computational genomics. Holding a Ph.D. in Information Technologies and Machine Learning from Uzhhorod National University, he has contributed significantly to the fields of text mining and artificial intelligence. Currently a Postdoctoral Researcher at The Pennsylvania State University, Dr. Lupei is recognized for his innovative work in developing large language models and optimizing computational frameworks for biomedical data analysis. His career reflects a blend of academic excellence and practical industry experience, underpinned by a strong commitment to advancing technology and data science.

Professional Profile:

👩‍🎓Education:

Ph.D. in Information Technologies and Machine Learning (2021)

  • Institution: Uzhhorod National University
  • Dissertation: Determining the Eligibility of Candidates for a Vacancy Using Artificial Neural Networks

MSc in Applied Mathematics (2013)

  • Institution: Uzhhorod National University
  • Thesis: .NET Websites Optimization

BSc in Applied Mathematics (2012)

  • Institution: Uzhhorod National University
  • Thesis: Modern Methods of Prediction

🏢 Professional Experience:

Dr. Maksym Lupei is currently a Postdoctoral Researcher in Computer Science & Engineering at The Pennsylvania State University (since August 2023), where he leads projects involving large language models for biomedical data fact-checking, computational genomics, and metagenomics. His work includes developing open-source text mining services and optimizing GPU infrastructure. Previously, he served as a Senior Research Fellow at the V. M. Glushkov Institute of Cybernetics of the National Academy of Science of Ukraine, specializing in machine learning and text mining (January 2022 – August 2023). At Uzhhorod National University, Dr. Lupei was an Assistant Professor in the Department of Informative and Operating Systems (December 2019 – January 2023), teaching programming languages and machine learning courses.

Dr. Lupei’s industry experience includes roles as an Engineering Manager at TIBCO Jaspersoft (March 2014 – February 2021), where he led cross-functional teams and established Agile/Scrum processes, and as a Full Stack Developer at JustAnswer (March 2011 – February 2014) and Swan Software Solutions (August 2010 – March 2011).

Research Interests

Dr. Lupei’s research interests encompass machine learning, large language models, computational genomics, metagenomics, and explainable artificial intelligence. His work focuses on processing large information arrays using mathematical methods, particularly in text mining.

Top Noted Publication:

 

 

Anurag Upadhyay | Machine Learning Award | Best Researcher Award

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Mr. Anurag Upadhyay, Machine Learning Award, Best Researcher Award

Anurag Upadhyay at DGI GREATER NOIDA, India

Summary:

Mr. Anurag Upadhyay is a dedicated academician and experienced educator with over 15 years of teaching experience in the field of computer science and technology. He holds a Master’s degree (M.Tech) in Computer Science from IFTM University, Moradabad, and a Bachelor’s degree (B.Tech) in Computer Science from MIT Moradabad (UPTU).

Throughout his career, Mr. Upadhyay has served in various teaching positions at esteemed institutions such as IFTM University Moradabad, KITPS Moradabad, and RIMT Bareilly, among others. Currently, he is an Assistant Professor at Dronacharya Group of Institutions, Greater Noida, where he continues to impart his knowledge and expertise to aspiring students.

Professional Profile:

Google Scholar Profile

👩‍🎓Education & Qualification:

Professional Experience:  

Mr. Anurag Upadhyay has over 15 years of experience in the field of teaching. He has held various positions in different educational institutions, including lecturer positions at Govt Girls Polytechnic Bareilly, FIET Bareilly, and CET IFTM Moradabad. He served as an Assistant Professor at IFTM University Moradabad, KITPS Moradabad, RIMT Bareilly, IIMT Greater Noida, and Dronacharya Group of Institutions Greater Noida. Throughout his career, Mr. Upadhyay has taught a wide range of subjects, including Machine Learning, Cloud Computing, Operating System, Information Technology, Computer Organization, Distributed System, Data Mining & Data Warehousing, Computer Concepts & Programming in ‘C,’ Soft Computing, Design of Algorithm, Software Engineering, and Compiler. He is an active member of professional organizations such as CSTA, ACM, and IAENG. Additionally, Mr. Upadhyay has undergone training and short-term courses in various areas related to computer science and technology.

Research Interest:

Machine Learning: Exploring algorithms and techniques to enable computers to learn from and make predictions or decisions based on data.

Cloud Computing: Investigating cloud-based services, architectures, and technologies for efficient data storage, processing, and management.

Operating Systems: Studying the design, implementation, and optimization of operating systems to enhance system performance and resource utilization.

Information Technology: Researching advancements in IT infrastructure, applications, and management practices to support organizational objectives and improve efficiency.

Data Mining & Data Warehousing: Analyzing large datasets to discover patterns, trends, and insights that can drive informed decision-making in various domains.

Computer Organization: Investigating the architecture and design of computer systems, including hardware components and their interactions, to optimize performance and functionality.

Software Engineering: Exploring methodologies, tools, and best practices for the systematic development, maintenance, and evolution of software systems.

Compiler Design: Studying the theory and implementation of compilers, which translate high-level programming languages into machine-readable code for execution on hardware platforms.

Publication Top Noted:

Title: Empirical Comparison by data mining Classification algorithms (C 4.5 & C 5.0) for thyroid cancer data set

  • Authors: A. Upadhayay, S. Shukla, S. Kumar
  • Journal: International Journal of Computer Science & Communication Networks
  • Volume: 3
  • Issue: 1
  • Page: 64
  • Year: 2013
  • Citation Count: 36

Title: A fresh loom for multilevel feedback queue scheduling algorithm

  • Authors: R.K. Yadav, A. Upadhayay
  • Journal: International Journal of Advances in Engineering Sciences
  • Volume: 2
  • Issue: 3
  • Pages: 21-23
  • Year: 2012
  • Citation Count: 19

Title: Animal husbandry practices in Pithoragarh district of Uttarakhand state

  • Authors: S. Shukla, D.P. Tiwari, A. Kumar, B.C. Mondal, A.K. Upadhayay
  • Journal: Indian Journal of Animal Sciences
  • Volume: 77
  • Issue: 11
  • Page: 1201
  • Year: 2007
  • Citation Count: 12

Title: Evaluation of fish curry from farmed and wild caught Indian major carps of Tarai Region, Uttarakhand

  • Authors: M. Gupta, A.K. Upadhayay, N.N. Pandey, P. Kumar
  • Publisher: Society of Fisheries Technologists (India) Cochin
  • Year: 2013
  • Citation Count: 2

Title: Cryptography and Network Security

  • Author: Anurag Upadhyay
  • Publisher: Lambert Publishing House
  • Volume: 1
  • ISBN: 978-620-2-02336-8
  • Year: 2017

 

 

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:

🎓 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.

🎓 Education

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

🏆 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 Focus 

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

💼 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

🎓 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)

🏆 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)

📚 Lateral Courses Completed

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

🏆 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)

🎉 Awards and Recognitions

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