Ankur Lahiry

Ankur Lahiry

Doctoral Instructional Assistant || CS-PhD || Texas State University, San Marcos, Texas

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👋 Welcome to My Homepage

Hello! I’m Ankur Lahiry, a Ph.D. student in the Department of Computer Science at Texas State University, working in the Per4ML Lab under the supervision of Dr. Tanzima Islam.

I specialize in High Performance Computing (HPC) and Machine Learning, focusing on building intelligent, scalable, and performance-aware systems. My academic journey is driven by the goal of bridging cutting-edge research with real-world impact.

📝 Career Summary

  • 🎓 Ph.D. Candidate in Computer Science with a research focus on HPC and Machine Learning at Texas State University.
  • 💻 5+ years of professional experience in software engineering, with a focus on building large-scale social communication platforms and developing secure, real-time digital payment solutions.
  • 📈 Expertise in graph-based modeling, performance analysis, and scalable computing systems.
  • 🤝 Collaborator with U.S. Department of Energy’s Brookhaven National Laboratory (BNL) on performance anomaly detection projects.
  • 🤝 Collaborator with Argonne National Laboratory (ANL), contributing to performance optimization and scalable system design in High Performance Computing (HPC).
  • 🧠 Passionate about performance-aware ML systems that drive efficiency in large-scale computational environments.

🧠 Research Interests

My research interests lie at the intersection of intelligent algorithms and high-performance systems.

  • Machine Learning (ML):
    • Designing adaptive, explainable, and data-driven models.
    • Using ML to identify complex patterns in performance data.
  • High Performance Computing (HPC):
    • Analyzing and optimizing resource utilization in large-scale architectures.
    • Developing scalable methods for anomaly detection and performance prediction.
  • Human–Computer Interaction (HCI):
    • Creating intuitive interfaces to bridge human insight with ML-powered systems.
  • Internet of Things (IoT):
    • Building intelligent, connected systems that leverage distributed computing.

🌟 My Vision

I’m passionate about bridging research and real-world applications.
My vision is to build scalable, performance-aware ML systems that optimize modern computing infrastructures and make complex technology more transparent, explainable, and efficient.

I aim to contribute to high-impact research that drives innovation in HPC, edge intelligence, and anomaly detection frameworks—ultimately enabling faster, more efficient scientific discovery and real-time decision-making.

📚 Academic & Professional Background

  • Spring 2023 – Present: Doctoral Research Assistant, Per4ML Lab, Texas State University
    • Conducting research on performance analytics in HPC using machine learning.
    • Working on anomaly detection, resource utilization modeling, and scalable system optimization.
    • Developed a distributed data-analysis framework for GPU trace logs to reduce per-node memory pressure and enable low-latency exploration of high-dimensional trace data.
    • Designed a graph-based representation of application performance to enable anomaly classification using graph neural networks, capturing complex relationships among tasks and resources.
    • Applied real-world Nsight Compute trace data from HPC and AI workloads to diagnose memory-transfer latency effects on GPU kernel behavior, uncovering actionable performance optimization insights.
    • Exploring explainable ML techniques to trace anomaly-detection decisions back to low-level system behaviors (e.g., resource contention, data-transfer bottlenecks).
    • Collaborating with national lab partners (BNL, ANL) to validate methods on large-scale clusters and integrate results into production monitoring workflows.
  • Fall 2022 – Spring 2023: Doctoral Instructional Assistant, Texas State University
    • Assisted in Computer Architecture courses, supporting both lectures and lab sessions.
    • Guided and mentored undergraduate students in assignments, lab work, and term projects.
    • Provided one-on-one and group tutoring to help students strengthen their understanding of core architecture concepts such as pipelining, memory hierarchy, and parallelism.
    • Collaborated with faculty to design and evaluate course assignments, ensuring alignment with learning objectives.
    • Helped create and refine lab materials and example problems to support students’ practical learning.
    • Facilitated code debugging sessions, project reviews, and performance analysis exercises.
    • Encouraged active learning by fostering technical discussions and peer-to-peer problem solving.

  • Aug 2022 – Present: Ph.D. in Computer Science, Texas State University (CGPA 4.00 out of 4.00 as of Spring 2025)

  • May 2012 – Feb 2017: B.Sc. in Computer Science and Engineering, Bangladesh University of Engineering and Technology (BUET). (CGPA 3.00 out of 4.00)

💼 Industry Experience Highlights

I bring over five years of hands-on software engineering experience, working with both startups and established companies in Bangladesh and the United States. My background includes mobile application development, secure financial platforms, team leadership, and product architecture.

🇧🇩 DataBird (DeshiPay & Ridmik Labs) — Software Engineer (2020–2022)

  • Spearheaded the iOS development for DeshiPay, a fintech platform enabling secure mobile transactions in Bangladesh.
  • Coordinated and scaled the iOS team to align with product goals and security requirements.
  • Implemented real-time messaging and voice-over-IP services using XMPPFramework and WebRTC for RidmikChat.
  • Worked cross-functionally with security, backend, and design teams to ensure seamless platform integration.
  • Practiced Agile methodologies including sprint planning, code reviews, and feature iteration.

🍽️ Prefeex Ltd. — Senior Software Engineer (2019–2020)

  • Led the complete development of a restaurant reservation iOS application, from design to deployment.
  • Oversaw system architecture, implemented major feature modules, and enhanced user experience.
  • Improved development workflows through Agile processes, boosting team velocity and product stability.
  • Ensured the app’s scalability to support an expanding user base and feature set.

💳 iPay Systems Ltd. — Software Engineer (2017–2019)

  • Developed the iPay iOS app, enabling secure real-time financial transactions.
  • Implemented robust security features and built iPay SDK for third-party payment integration.
  • Created internal frameworks to streamline app development and improve system maintainability.
  • Contributed to code reviews, feature enhancements, and production rollouts in a fast-paced fintech environment.

🏢 BellBizzer Inc. (Seattle, WA) — Senior Software Engineer (Remote, part time)

  • Led iOS development for a rental marketplace platform, contributing to architecture, design, and front-end modules.
  • Actively collaborated with UI/UX designers and stakeholders to build a smooth and intuitive experience.
  • Monitored app performance, optimized user interactions, and improved system reliability.
  • Played a key role in client communication and product strategy discussions to scale the platform effectively.

🧰 Technical Skills

  • Programming: C, C++, Python, Swift, Java, Go

  • Machine Learning & AI (Current Focus):
    • Model Architectures: Graph Neural Networks (GNN), Attention Mechanisms, Deep Neural Networks (DNN), Large Language Models (LLMs)
    • Core Techniques: Representation Learning, Anomaly Detection, Explainable AI (XAI), Feature Engineering, Transfer Learning
    • Applications: Performance Analytics in HPC, System Behavior Modeling, Anomaly Classification, Intelligent Monitoring Systems
  • Past Industry Expertise:
    • Databases: SQL, MySQL
    • Frameworks & Tools: PyTorch, XMPPFramework, WebRTC, Git, Agile/Scrum
    • Mobile App Development (iOS) and Cross-Platform Systems
    • Scalable Architecture Design and Product Development
    • Real-time Communication Platforms & Secure Payment Systems