Maksym Lupei | Predictive Analytics | Best Paper Award

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:

πŸ‘©β€πŸŽ“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:

 

 

Gayan KIncy Kulatilleke | Machine learning

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)