Computer Science Machine Learning

Abhiraj Yogesh Srivastava

San Diego, CA +1-858-***-**** R ******@****.*** abhiraj-srivastava abhisri459 Education

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University Of California, San Diego San Diego, USA Master of Science - Computer Science and Engineering September 2024 - December 2025 Current Courses: Search & Optimization, Fairness in ML and ML Algorithms; GPA: 4/4

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National Institute Of Technology, Patna Patna, India Bachelor of Technology - Computer Science and Engineering; CGPA: 9.26/10.0 2019 - 2023 Skills

• Programming: C++, Java, Data Structures, Algorithms, Python, OOPS, Operating Systems, Computer Networks

• Frameworks: HTML, CSS, ReactJS, Git, CI/CD, PyCharm, VS Code

• Soft Skills: Creative Thinking, Teamwork

Experience

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DataFlow Group - TrueProfile.io Bengaluru, India

Software Development Engineer Nov 2023 - June 2024

Team: Frontend Developer leading the creation of intuitive user interfaces using ReactJS, JavaScript, TypeScript, and Jest, driving innovation and enhancing team collaboration.

Responsibilities: Responsible for leading the design and development of pixel-perfect, intuitive user interfaces to enhance user experiences, while fostering teamwork and collaboration to drive innovative web solutions.

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Cloudera Data Platform India Pvt. Ltd. Bengaluru, India Software Engineering Intern Jan 2023 - Sept 2023

Team: Led automation initiatives within the CDE (Cloud Data Experience) Team, collaborating with team members to develop efficient solutions using Airflow, Python, Kubernetes, and Docker, streamlining workflows and enhancing productivity through strong leadership and teamwork.

Responsibilities: Reduced the CDE Test Matrix to nearly 50% of its original value by combining various Spark versions’ runs into one run and thereby optimizing the overall Test runtime.

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National Institute of Technology Tiruchirappalli Remote Summer Research Intern May 2022 - August 2022

Area of Research: Led a collaborative effort in Extractive Text Summarization, overseeing the preprocessing of raw data and guiding the team in converting it into compact, efficient summaries, ensuring accuracy and effectiveness through teamwork and shared expertise.

Models Used: Implemented TextRank, LexRank, LSA, etc. to summarize large texts to nearly 45% of their original word length accurately and find Rouge Scores for each model. Projects

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Sarcasm Detection Using Machine Learning and Deep Learning Machine Learning Github Link

A 6-model(CNN, RNN, LSTM, BERT, HAN & ELMo) project with high accuracy to detect sarcasm in tweets.

This was done as a B.Tech Minor Project and is under publishing as a Research Paper at SCIE Journal.

Results: The HAN model achieved the highest Accuracy of 95.71%

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Student Grievance Redressal System (Group Project) Website Web Development Github Link

Built an online portal to streamline and address college students’ grievances, reducing resolution time by 40%.

Designed a dynamic interface with grievance tracking and admin escalation features using HTML, CSS, ReactJS, and Firebase.

Achieved 100+ registrations within a month of deployment, with over 90% user satisfaction during beta testing.

Achievements

• Published 43 articles on the Geeksforgeeks portal on SQL and related topics. Link

• Participated in 5 rounds of Google Kick Start 2020 and secured the best global rank of 1858.

• Stood 4th in the FY’24 Internship Project Presentation at Cloudera.

• Was a finalist of IEEE event Impulse in 2019.

• Contributed to Open Source through Hacktoberfest and GWOC(Girlscript Winter of Contribution).

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