Introduction

I'm Kazi Shaharair Sharif. I have 6 years of experience in the field of software engineering. Machine Learning Researcher

My primary focus lies at the intersection of Graph Mining, Geometric Deep Learning, Graph Neural Networks, Hypergraph Neural Networks, Bioinformatics, and Natural Language Processing. Currently, I am dedicated to advancing the frontiers of Complex Network Representations. My approach integrates the capabilities of Large Language Models (LLMs) to develop more interpretable and robust GNN architectures for Biological, Citation, and Social Networks, aiming to set new benchmarks in these fields.

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Short story

About me

Machine Learning Engineer with expertise in designing, deploying, and optimizing scalable ML solutions for real-world applications. Passionate about leveraging AI, data-driven insights, and cutting-edge technologies to drive innovation and deliver impactful results.

Full Name

Kazi Shaharair Sharif

Major

Ungraduate studies: Computer Science and Information System

Graduate studies: Computer Science specialized in Artificial Intelligence

Current Degree

Master

Location

Dallas, United States of America

Phone

4058940048

Email

Sharif.kazi@outlook.com

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Portfolio

Projects Implmentations and Publications

I'm a designer & developer with a passion for web design. I enjoy developing simple, clean and slick websites that provide real value to the end user.

  • All Work

My Work

Publications and Contributions to research in machine learning and AI:

  • IEEE: PrecisionCardio: A Comprehensive Machine Learning Approach for Accurate Prediction of Heart Failure Trajectory, ICT 2024, IEEE, 2024.
  • IEEE: A Comprehensive Framework for Advanced Machine Learning and Deep Learning Models in Cervical Cancer Prediction, APWiMob 2024, IEEE, 2024.
  • IEEE: Advancing Cervical Cancer Risk Stratification via Ensemble Learning Models Integrated with SHAP-Based Interpretability Methods, ICOCO 2024, IEEE, 2024.
  • IEEE: Optimized Ensemble Learning for Chronic Kidney Disease Prognostication: A Stratified Cross-Validation Approach, ICOCO 2024, IEEE, 2024.
  • International Journal on Computational Engineering: Credit Risk Assessment Using Statistical and Machine Learning: Basic Methodology and Risk Modeling Applications, International Journal on Computational Engineering, vol. 1, no. 3, pp. 62–67, 2024.
  • Journal of Computer Science and Technology Studies: Advancing Chronic Kidney Disease Prediction: Comparative Analysis of Machine Learning Algorithms and a Hybrid Model, Journal of Computer Science and Technology Studies, vol. 6, no. 3, pp. 15–21, 2024.
  • American Journal of Computing and Engineering: Product Demand Forecasting for Inventory Management with Freight Transportation Services Index Using Advanced Neural Networks Algorithm, American Journal of Computing and Engineering, 2024.
  • IEEE: A Comparative Framework Integrating Hybrid Convolutional and Unified Graph Neural Networks for Accurate Parkinson’s Disease Classification, 7th ISRITI 2024, IEEE, 2024.
  • IEEE: Synergistic Fusion of Optimized Ensemble Algorithms and Deep Neural Paradigms for Precision Stratification and Prognostication in Cardiovascular Pathologies, 7th ISRITI 2024, IEEE, 2024.
  • IEEE: Augmenting Sleep Quality Prognostics through Internet of Things and Machine Learning: A Rigorous Comparative Analysis for Advanced Personalized Health Metrics, 7th ISRITI 2024, IEEE, 2024.
  • IEEE: NeuroSignal Precision: A Hierarchical Approach for Enhanced Insights in Parkinson’s Disease Classification, ICICyTA 2024, IEEE, 2024.
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Resume

My resume

I'm a designer & developer with a passion for web design. I enjoy developing simple, clean and slick websites that provide real value to the end user.

Experience.

Machine learning Engineer

Jun 2023 - August 2024

Full TIme

Conch technologies, INC

 Develop and Optimize Machine Learning Models: Designed, built, and optimized machine learning models for various applications, including classification, regression, recommendation systems, forecasting, natural language processing (NLP), and computer vision..  Data Preprocessing and Feature Engineering: Cleaned, preprocessed, and transformed raw data into structured formats suitable for training machine learning models. Performed feature extraction, selection, and engineering to enhance model performance.Process and analyze large-scale structured and unstructured datasets to extract actionable insights, perform feature engineering, and build data pipelines.  Deployment and Integration: Deployed machine learning models into production environments using tools like Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Ensured seamless integration with existing systems.  Collaborate with Cross-Functional Teams: Worked closely with data scientists, software engineers, and domain experts to align machine learning solutions with business objectives and technical requirements.  Automate Model Training and Testing Pipelines: Built automated pipelines for data ingestion, model training, testing, and deployment using CI/CD frameworks to streamline machine learning development workflows.  Monitor and Maintain Models: Continuously monitored the performance of deployed models and retrained or updated them as needed to ensure effectiveness and alignment with evolving data trends.  Research and Implement New Techniques: Stayed updated with the latest advancements in machine learning and AI. Experimented with new algorithms, tools, and techniques to enhance model accuracy, scalability, and efficiency. Data Analysis and Visualization: Analyzed data trends and visualized results to derive actionable insights and recommendations for stakeholders. Utilized visualization tools like Matplotlib, Seaborn, and Tableau for effective data communication. Documentation and Reporting: Documented end-to-end model development processes, data findings, and analysis results. Prepared reports and presentations to communicate insights to technical and non-technical stakeholders.

Software Engineer

March 2022 - July 2024

Full TIme

Citibank, N.A & CitiGroup, INC

• Project C1C: Project C1C is focused on building banking & financial domain applications and microservices for transferring and storing of sensitive data for Auto, home, Business , surety Service, credit &loan holders. • Worked in developing microservices-based applications using Java, Spring Boot, and Kubernetes. • Implemented UI requirements using Spring, microservices with Reacts and Angular. • Worked for developing and enhancing the Citi Risk Platform for Commercial technology using Java/J2EE, JSP,JPA, JEE, Hibernate, Webservices, Cloud, SOAP/REST, Spring 3.2, Spring Web Flow 2.0, Spring Boot 2.3, Micro-Services, AWS, JUnit, Python, Spring Data JPA, XML, XSD, Servlets, SNMP,UNIX, Oracle, Mongo DB, PostgreSQL, Swagger and Postman API design tools, and messaging platform Kafka. • Worked on the development of Java-based applications using Spring and Hibernate framework. Designed, developed, and deployed microservices-based solutions using Java, Spring Boot, Docker, Kubernetes, & AWS. Worked with J2EE frameworks such as Spring, Hibernate, Struts, and Java Server Faces (JSF), along with experience in developing web services using SOAP and RESTful APIs. • Worked in Containerization using Docker, Docker CLI and Docker Compose, Building and deploying Docker images. Worked in Kubernetes architecture with Kubernetes deployment and management for Scaling and load balancing in Kubernetes and helped with container networking and storage. • Led the development of a microservices-based payment system that reduced transaction times by 50%. • Optimized database queries and implemented caching strategies to improve application performance by 50%. • Collaborated closely with team of 18 programmers and with one java developer in pair programming arrangement, decreasing the production cost of 4% annually by reviewing the previous implementation code and debugged errors to improve performance. Resulted in 15% reduction in hours spent. Technologies: Core Java, Multithreading/ Concurrency, Java/J2EESpring 5, Spring MVC, Spring Boot, Spring Data, Spring Cloud, Spring AOP, Microservices, Spring Batch, Hibernate, Spring Data, JSP, JSON, XML, SOAP/REST, Spring Web Flow, Oracle, Agile, JDBC Maven, jQuery, WebSphere, Servlets, Mongo DB, Junit, Jerkins, Team City, Netflix OSS Eureka, ribbon, Zuul API gateway, Hystrix circuit breaker, Docker.

Software Developer

October 2021 - March 2022

Full TIme

Pattons labs, INC

• Developed and maintained enterprise-level applications using Java and Spring Framework. • Built RESTful API services using Jersey & Hibernate with Oracle, PostgreSQL, MySQL & MongoDB. • Implemented design &built scalable technical products, resulting in a 30% increase in customer satisfaction. • Developed and maintained batch processing systems using Spring Batch. • Analyzed and adjusted for user/client habits to cut attrition 25%. • Worked with teams of 2-3 developers in 3 projects to improve software testing and troubleshooting. • Designed, developed, and implemented software applications for websites based on analyzed requirements and understanding of industry technical standards. Developed JSP web pages integrating HTML5, XML elements with SOAP/Rest Service. Exceeded job-completion deadlines by 15% on average. Technologies: Java, J2EE, JSP, Servlets, Java Beans, Spring, Spring Boot, Hibernate, XML, RESTFUL, JSTL, JSON, XML, HTML5, CSS3, JavaScript, AWS, Microservices, Mongo DB, AJAX, Continuous Integration, Jenkins, Log4j, JUnit, SQL, HQL, Apache Tomcat, WebLogic Server, Oracle, PL/SQL, JIRA, ANT, GIT, Eclipse

Education.

Oklahoma State University, Bachelor's

Aug 2017 - Jun 2021

Graduated

Developed a strong foundation in computer science and software engineering principles through rigorous coursework and hands-on projects. Key highlights of the program include: Programming Proficiency: Mastered multiple programming languages, including Java, Python, C++, and JavaScript, with a focus on efficient algorithm design and problem-solving. Software Development: Gained expertise in designing, developing, and deploying scalable software applications using industry-standard frameworks and tools such as Spring Boot, React, and Node.js. System Design and Architecture: Learned to design robust, modular, and high-performance software systems while adhering to object-oriented and functional programming paradigms. Data Structures and Algorithms: In-depth knowledge of computational efficiency and optimization techniques, including graph algorithms, dynamic programming, and advanced sorting algorithms. Database Management: Proficient in relational and NoSQL databases like MySQL, MongoDB, and PostgreSQL, with practical experience in designing schemas and writing complex queries. Software Testing and Debugging: Applied advanced testing techniques, including unit, integration, and performance testing, using tools like JUnit and Selenium. Team Collaboration: Participated in collaborative software engineering projects, employing Agile methodologies and version control systems like Git and GitHub. Capstone Project: Designed and implemented a full-stack application that addressed a real-world problem, integrating front-end, back-end, and database technologies to deliver a seamless user experience. Graduation from this program equipped me with the technical expertise, problem-solving skills, and collaborative mindset necessary to excel in software engineering roles and adapt to emerging technologies.

University of South Dakota, Master's

Master of Science in Computer Science, specialized in Artificial Intelligence (GPA: 4.00)

Aug 2024 - Current

Current

Description

Focused on advanced computational techniques, the program provided a comprehensive understanding of core computer science principles with a deep dive into Artificial Intelligence (AI). Key areas of expertise include: Machine Learning: Supervised, Unsupervised, and Reinforcement Learning techniques. Deep Learning: Expertise in frameworks like TensorFlow, PyTorch, and Keras for neural network design. Natural Language Processing (NLP): Hands-on experience with Hugging Face Transformers and sequence modeling for real-world text analytics. Computer Vision: Implementation of cutting-edge architectures for object detection, segmentation, and image synthesis. Data Science and Big Data: Leveraged tools like Apache Spark and Hadoop for large-scale data processing and visualization. Research Methodologies: Developed innovative AI models tailored to specific domains, emphasizing ethical AI and model interpretability.

My Skills.

Software Technical Implementation Skills

Category Skills
Front End Java, Python, Angular, React, Node.js, HTML5, CSS3, jQuery, JavaScript, Bootstrap, PHP, XML, JSON
Back End Spring 5, Spring Boot, Struts, EJB, Microservices, Kafka, Rabbit MQ, Hibernate, Servlets, Soap UI, Rest API
Cloud Dev AWS, GCP, Docker, Kubernetes
Database MongoDB, PostgreSQL, DB2, Oracle SQL, DBMS, Hadoop, NoSQL, JDBC, MySQL
Build Tools Maven, Gradle, OpenShift, Swagger, JUnit, TestNG, Mockito, Team City, Jenkins, GitHub, Bitbucket
Monitoring Prometheus, Grafana, Splunk, Apache Tomcat, Dump Analysis, Netflix, Zuul Keeper, Eureka, Log4j

Contact

Get in Touch

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