I build scalable, intelligent software that connects high‑performance computing, machine learning and cloud‑native systems.
Designing and optimising parallel applications using MPI, CUDA and OpenMP. Building scalable HPC pipelines on clusters and cloud platforms with thorough performance benchmarking and tuning.
Developing end‑to‑end AI solutions with PyTorch and TensorFlow, including deep learning architectures for computer vision and natural language processing, and deploying models for real‑world inference.
Building robust Applications and APIs with Python, C++ and Java. Automating workflows with CI/CD pipelines, Docker and Kubernetes to ensure reliable, reproducible deployments.
Creating responsive full‑stack web applications using Node.js, React and modern web technologies. Implementing on‑page and technical SEO strategies to improve website visibility and user experience.
I’m a Master’s student in High-Performance Computing at the University of Luxembourg, working at the intersection of HPC, AI/ML, and cloud-native systems. My projects range from regression testing HPC clusters to AI applications like RepoFinder AI, real-time lip-reading, and spatio-temporal video analysis — bridging research with practical solutions.
An automated regression testing suite to validate and monitor MPI communication performance on HPC clusters using ReFrame and OSU Micro-Benchmarks. Identified performance anomalies and optimized software stacks, ensuring stable, high-performance communication fabric.
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Fine-tuned a state-of-the-art R(2+1)D-18 model to detect violent actions in video streams. Engineered data pipelines and training strategies to overcome overfitting and numerical instability, delivering real-time inference.
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Designed a custom CNN+LSTM architecture in PyTorch to translate live lip movements into text in real-time. Implemented CTC loss, data preprocessing, and end-to-end deployment for a complete lip-reading system.
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A full-stack search application that uses a dual-AI pipeline — a Llama-based reasoning agent and a Sentence Transformer — to translate natural language ideas into precise queries and discover relevant GitHub repositories.
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Developed a two-stage computer vision pipeline for the SPARK 2024 challenge, combining YOLO11-Small detection with SegFormer-B1 segmentation to identify spacecraft body and solar panels in synthetic space imagery.
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Built an interactive data visualization dashboard using React and D3.js to explore housing market data across multiple dimensions. Implemented linked visualizations with real-time brushing and selection for intuitive pattern analysis.
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Designed and implemented a complete CI/CD pipeline for a full-stack web application using GitLab, Docker, and Ansible. Automated build, testing, containerization, and deployment across development, staging, and production environments.
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Built an end-to-end DevOps project that provisions a self-hosted GitLab server with Vagrant and Ansible and automates a 4-stage CI/CD pipeline for a Java Maven application using GitLab Runner and Docker.
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Built a full-stack visual analytics application for VAST Challenge 2022 using a D3.js frontend, Node.js/Express backend, and PostgreSQL/PostGIS database to explore complex urban data through linked interactive views.
View on GitHubAvailable upon request
Built and benchmarked custom MapReduce jobs in Java for large-scale text processing, including regex-based filtering and performance evaluation on HPC clusters.
Private RepositoryAvailable upon request
Reimplemented text analytics using Spark RDDs and Scala, leveraging in-memory computation to significantly improve performance over Hadoop-based approaches.
Private RepositoryAvailable upon request
Analyzed passenger data using Spark DataFrames and SQL, implementing custom UDAFs and performing statistical analysis on structured datasets.
Private RepositoryAvailable upon request
Constructed and analyzed a large-scale graph using Spark GraphX, applying PageRank and Connected Components to identify influential nodes and communities.
Private RepositoryAvailable upon request
Processed large-scale geospatial data using Spark, performing borough-level analytics and anomaly detection on trip durations.
Private RepositoryAvailable upon request
Developed a distributed Monte Carlo simulation in Spark to compute financial risk metrics such as VaR and CVaR for stock portfolios.
Private RepositoryAvailable upon request
Built a classification pipeline using Decision Trees and Random Forest with hyperparameter tuning via CrossValidator to predict heart disease risk.
Private RepositoryAvailable upon request
Developed regression models using Spark MLlib to forecast temperature from time-series weather data with feature engineering and preprocessing.
Private RepositoryAvailable upon request
Implemented an ALS-based recommender system with custom train/test splits and evaluated performance using AUC metrics.
Private RepositoryAvailable upon request
Performed topic modeling on 40K+ articles using LSA and cosine similarity to build a semantic document retrieval system.
Private RepositoryAvailable upon request
Applied NLP and LSA techniques on 134K movie plots, integrating metadata to enhance topic interpretation.
Private RepositoryAvailable upon request
Used K-Means clustering on 14M+ sensor records to detect anomalies and identify machine faults.
Private RepositoryAvailable upon request
Implemented a hybrid parallel BFS algorithm with dynamic strategy switching, achieving high performance on massive graphs.
Private RepositoryAvailable upon request
Designed and benchmarked multiple MPI-based algorithms for distributed pathfinding, analyzing communication and scalability trade-offs.
Private RepositoryAvailable upon request
Developed a GPU-based prefix-sum algorithm and used it to build efficient parallel data processing primitives.
Private RepositoryAvailable upon request
Optimized matrix multiplication using shared memory tiling in CUDA to significantly reduce memory latency and improve throughput.
Private RepositoryAvailable upon request
Built a real-time detection system using OpenCV and MediaPipe to identify individuals raising hands, with custom heuristics and tracking logic.
Private RepositoryI communicate clearly with technical and non-technical stakeholders, helping translate ideas, requirements, and feedback into actionable work.
I enjoy understanding user needs, clarifying problems, and guiding discussions toward practical technical solutions.
I work comfortably across research, operations, and engineering contexts, coordinating with different teams to keep work aligned and moving forward.
I can explain technical concepts in a structured way, present work clearly, and produce documentation that improves understanding and execution.
I take responsibility for assigned work, follow through carefully, and focus on delivering tasks with consistency, accuracy, and professionalism.
I am good at listening, identifying the core issue behind a request, and helping connect the right people, tools, and next steps to solve it.
Intern
• Designing swarm-based metaheuristics for an advanced Pickup and Delivery Problem (PDP) with vehicle transfers and electric vehicle constraints.
• Developing high-performance implementations in C++ and CUDA to accelerate large-scale optimization using GPU parallelism on HPC systems.
• Modeling dynamic and large-scale routing scenarios, focusing on efficient exploration of complex solution spaces.
• Evaluating scalability and performance on HPC infrastructure to support next-generation sustainable logistics systems.
Student Employee
SnT – Interdisciplinary Centre for Security, Reliability & Trust
• Streamlined internal workflows by improving documentation, triaging requests, and supporting process automation.
• Maintained and validated IP databases, ensuring data accuracy and consistency across systems.
• Processed disclosure forms and supported compliance workflows within the Technology Transfer Office.
• Collaborated with cross-functional teams to improve operational efficiency and data handling processes.
Seasonal Student Employee
SnT – Interdisciplinary Centre for Security, Reliability & Trust
• Integrated and maintained APIs to support efficient system operations and data exchange.
• Automated dataflows and reduced manual workload through scripting and workflow optimization.
• Maintained IP documentation and supported FOSS compliance pipelines.
• Collaborated with internal teams to streamline processes and improve system reliability.
Student Employee
SnT – Interdisciplinary Centre for Security, Reliability & Trust
• Maintained and updated IP asset databases to support technology transfer operations.
• Reviewed and processed disclosure submissions, ensuring compliance with internal procedures.
• Acted as a primary point of contact for researchers submitting IP-related documentation.
• Ensured data integrity and resolved database inconsistencies in collaboration with stakeholders.
Student Employee
University of Luxembourg
• Assisted in evaluating and validating research metrics using Python-based tools.
• Tested and improved command-line tool functionality through systematic validation.
• Provided feedback to enhance usability and contributed to improving documentation quality.
Full-time Employee
Bizcope BD
• Conducted keyword research and implemented on-page SEO strategies to improve search rankings.
• Performed technical SEO audits and optimized website structure and performance.
• Collaborated with content and development teams to align SEO best practices.
• Monitored performance metrics and continuously improved SEO strategies.
Student Employee
North South University
• Conducted tutorials and lab sessions for courses in C, C++, and Data Structures & Algorithms.
• Mentored students and provided academic support to strengthen problem-solving skills.
• Graded assignments and assisted in designing course materials and assessments.
• Supported faculty in delivering structured and effective programming education.