Hello! Iโm 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.
๐ Career Summary
- ๐ Ph.D. Student in Computer Science with a research focus on HPC and Machine Learning at Texas State University.
- ๐ Expertise in graph-based modeling, performance analysis, and scalable computing systems.
- ๐ค Collaborator with U.S. national laboratories on performance anomaly detection and scalable system design in High Performance Computing (HPC).
- ๐ง Passionate about performance-aware ML systems that drive efficiency in large-scale computational environments.
- ๐ป 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.
๐ง Research Interests
My research interests lie at the intersection of intelligent algorithms and high-performance systems.
- High Performance Computing (HPC):
- Analyzing and optimizing resource utilization in large-scale architectures.
- Developing scalable methods for anomaly detection and performance prediction.
- Machine Learning (ML):
- Designing adaptive, explainable, and data-driven models.
- Using ML to identify complex patterns in performance data.
- Graph Representation Learning:
- Building graph-based models to capture complex relationships in system performance data.
- Applying GNNs for anomaly classification in HPC workflows.
- Decision Making & Explainable AI:
- Developing decision-support systems for navigating performance trade-offs in HPC.
- Making ML-driven recommendations transparent and interpretable.
- Anomaly Detection:
- Designing early-warning systems for performance degradation in large-scale computing systems.
- Synthetic Performance Data Generation:
- Generating realistic synthetic traces to augment training data for performance models.
- HumanโComputer Interaction (HCI):
- Creating intuitive interfaces to bridge human insight with ML-powered systems.
๐ My Vision
Iโm 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 frameworksโultimately enabling faster, more efficient scientific discovery and real-time decision-making.
๐ Academic & Professional Background
Aug 2022 โ Present: Ph.D. in Computer Science, Texas State University (Expected Graduation: Summer 2027)
- Spring 2023 โ Present: Doctoral Research Assistant, Per4ML Lab, Texas State University
- Developed a unified decision-intelligence system for HPC environments to recommend performant configurations by balancing speed, cost, and reliability trade-offs with explainable outputs and uncertainty-aware ranking, scaling to traces with 1.3B samples (126 GB) and achieving up to 100ร faster training and 80ร faster inference than state-of-the-art generative baselines.
- Design graph-based and explainable AI methods that turn complex system logs into intuitive signals, enabling early detection and diagnosis of unusual performance behavior in large-scale HPC systems.
- Engineered scalable GPU log-analysis pipelines for large trace datasets using distributed partitioning and parallel processing, achieving a 67% improvement in scalability while enabling fast identification of performance variability, memory stalls, and system bottlenecks.
- Collaborate with national laboratory partners to validate methods on large-scale clusters and integrate results into production monitoring workflows.
- June 2023 โ August 2023: Summer Research Intern, Brookhaven National Laboratory, Upton, New York
- Worked on the Chimbuko Project, a performance analytics framework for monitoring and improving efficiency of large-scale supercomputing applications.
- Developed a novel representation learning approach to automatically detect performance anomalies in complex computing workflows.
- Analyzed real HPC performance data to identify inefficiencies and unusual behaviors.
- Fall 2022: Doctoral Instructional Assistant, Texas State University
- Assisted in teaching Computer Architecture (CS4310), supporting both lectures and lab sessions.
- Guided and mentored undergraduate students in assignments, lab work, and term projects.
- Collaborated with faculty to design and evaluate course assignments, ensuring alignment with learning objectives.
- Encouraged active learning by fostering technical discussions and peer-to-peer problem solving.
- May 2012 โ Feb 2017: B.Sc. in Computer Science and Engineering, Bangladesh University of Engineering and Technology (BUET)
๐ผ 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.
๐ง๐ฉ DataBird (DeshiPay & Ridmik Labs) โ Software Engineer (2020โ2022)
- 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.
๐ฝ๏ธ Prefeex Ltd. โ Senior Software Engineer (2019โ2020)
- 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 appโs scalability to support an expanding user base and feature set.
๐ณ iPay Systems Ltd. โ Software Engineer (2017โ2019)
- 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.
๐ข BellBizzer Inc. (Seattle, WA) โ 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.
๐งฐ 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
