[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-168202-en":3,"doc-seo-168202-105":29,"detail-sidebar-cat-1-en-105":89},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":11,"category_id":12,"category_name":13,"doc_title":14,"doc_description":15,"doc_content":16,"file_id":17,"file_url":18,"file_type":19,"file_size":20,"view_count":4,"is_deleted":4,"is_public":11,"is_downloadable":11,"audit_status":11,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":15,"update_tm":28,"read_time":11},168202,5909877438554,"Maeve","https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272",1,12,"Resumes","Wolfie Seawolf - Resume","Comprehensive graduate-level resume for Wolfie Seawolf, presenting education, honors, and a skills profile spanning programming, operating systems, cloud services, and relevant certifications. Highlights include production deployment of machine-learning models on AWS, automation at scale with Automation Anywhere and SQL, and research on long-term secure archival systems using cryptographic integrity verification. Includes major academic and independent projects, measurable NLP and retrieval-augmented generation improvements, and leadership experience in teaching and student community activities.","Wolfie Seawolf\nTown, State | professional_email@stonybrook.edu | (123) 456 – 7890 | linkedin_url.com | GitHub\nEDUCATION\nStony Brook University\tStony Brook, New York\nMaster of Science in Computer Science | GPA: 3.0+\tExpected Graduation: Month 202X\nRelevant Coursework: System Security, Data Science, Advancements in Artificial Intelligence, Natural Language Processing, Machine Learning\nHonors/Scholarships/Awards: Dean’s Fellowship | Excellence in Research Award\nUndergraduate University\tTown, State\nBachelor of Science in Computer Science | GPA: 3.0+\t\t\t                  Start Month 202X – End Month 202X\nRelevant Coursework: Computer Networks, Data Structures, Python Programming, Object Oriented Programming\nHonors/Scholarships/Awards: Dean’s List 4 Semesters | University Scholars\nTECHNICAL SKILLS (include any other categories that match your skill set & years of experience)\nProgramming Languages: 6 years - Python, SQL, PostgreSQL, Java, HTML, XML; 2 years - C, Google AppScript; 1 year - C++, JavaScript, ReactJs, Rust\nOperating Systems: 8 years - Windows; 4 years - Linux, Kali Linux, Ubuntu\nCloud Systems: 2 years - Amazon Web Services (Lambda, S3, CloudWatch, SageMaker), Google Project, Google APIs\nCertifications: Cisco Certified Network Associate Routing and Switching (April, 2024), Python for Everybody - University of Michigan (July, 2023) (include any certifications that are relevant: month, year)\nPROFESSIONAL EXPERIENCE (organize categories according to relevance of the position you are applying for)\nAutoSci Innovations\tTown, State\nSoftware Developer\tStart Month 202X – Present\nSkill based bullet #1 (Example: Action verb + quantify task + skill/technologies + result/outcome)\nDeployed and optimized a yield prediction model using AWS SageMaker, Pandas, NumPy, and Spark, increasing production quality by 15% and reducing defects.\nTrained 4 interns and 3 non-developers on Automation Anywhere and SQL, improving automation skills across teams and enhancing business flow efficiency by 30%.\nGlobalFoundries\tTown, State\nData Systems and Automation Analyst \tStart Month 202X – End Month 202X\nEngineered and executed over 20+ automations using Automation Anywhere A360, reducing operational processes time and improving performance.\nLed a major multi-faceted project with 10 sub-projects named “RPA-Driven Semiconductor Reporting Automation”, showcasing leadership and technical acumen, leading to an estimated $200K in annual cost savings.\nDeveloped Python scripts for automation to augment RPA functionalities, and provided support for Java-based applications, demonstrating cross-technology expertise.\nCollaborated with international stakeholders as part of a 5-member data science team, using Python for data manipulation and advanced analytics to streamline production workflows and improve operational efficiency.\nACADEMIC RESEARCH & PROJECTS\nStony Brook University: File System Laboratory (FSL) | Principal Investigator Erez Zadok\tStony Brook, New York\nLong term secure archival systems    \tStart Month 202X – Present\nSkill based bullet #1 (Example: Action verb + quantify task + skill/technologies + result/outcome)\nInvestigating data integrity techniques in archival systems, focusing on secure integrity verification mechanisms that ensure long-term preservation of data.\nLearning Phase: Gained deep expertise in Shamir's Secret Sharing (SSS), Proactive Secret Sharing (PSS) and Verifiable Secret Sharing (VSS).  Explored  Commitment Schemes to support cryptographic integrity in distributed systems.\nImplementation Phase: Implemented cryptographic protocols, SSS, PSS, and VSS, in Rust using libraries ark-ff for finite fields and tonic for secure gRPC services. Developed a leakage-resilient secret sharing scheme to improve the robustness of archival systems against partial leakage of information.\nPublished a paper at the Association for Computing Machinery (ACM) workshop: Hot Topics in Storage and File Systems (July, 2024).\nINDEPENDENT PROJECTS\nEnhanced Medical Q","cbCaimvNGTyJlega","https://ap.wps.com/l/cbCaimvNGTyJlega","docx",14793,2,"English","en",105,"# Education\n# Technical Skills\n# Professional Experience\n# Academic Research & Projects\n# Independent Projects\n# Leadership Experience","[{\"question\":\"What research and technical areas does Wolfie Seawolf focus on?\",\"answer\":\"Seawolf investigates data integrity techniques for long-term secure archival systems, emphasizing secure integrity verification and cryptographic mechanisms such as Shamir’s Secret Sharing, Proactive Secret Sharing, and Verifiable Secret Sharing.\"},{\"question\":\"What are Wolfie Seawolf’s key professional achievements?\",\"answer\":\"He/She deployed and optimized a yield prediction model on AWS SageMaker to improve production quality and reduce defects, and delivered automation solutions using Automation Anywhere A360 that reduced operational processing time.\"},{\"question\":\"What independent projects and outcomes are included?\",\"answer\":\"The resume lists a retrieval-augmented medical question answering system with measured improvements in relevance and evaluation metrics, plus a microchip acceptance prediction model achieving 92% accuracy using regularized logistic regression and cross-validation.\"}]","Wolfie Seawolf - 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