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About Me
As a Machine Learning Engineer and Data Scientist, I bring 5 years of specialized experience in developing and deploying production-ready solutions in the banking industry. My expertise lies in transforming complex data into actionable insights, particularly in areas like Forecasting, Risk Management, and Personalized Recommendations. With a robust technical stack that includes Python, TensorFlow, PyTorch, and big data technologies like Data Bricks and PySpark, I have successfully implemented scalable solutions that drive significant business impact. My proficiency extends to cloud services, where I have leveraged both AWS (S3, Kinesis, SageMaker, and more) and Google Cloud (AutoML, BigQuery, Vertex AI) to build and optimize machine learning pipelines.
I hold a Master’s degree in Computer Science, specializing in Intelligent Systems and Data Science, from the University of Texas at Arlington, where I graduated with a perfect 4.0 GPA. Additionally, I earned Graduate Diplomas in Deep Learning and Big Data, both with a 4.0 GPA, and was awarded a 50% Tuition Waiver Scholarship for three semesters. During my time at the university, I also contributed to student academic success by serving as a Graduate Teaching Assistant. In this role, I helped students understand complex course topics, conducted exams, graded assignments, and supported courses such as Design and Analysis of Algorithms, Distributed Systems, and Theoretical Concepts in Computer Science and Engineering.
Driven by a passion for innovation and a commitment to excellence, I am eager to bring my skills and experience to new challenges, continually pushing the boundaries of what’s possible with data and machine learning.
Strong background in AI and ML, open to contributing. To hire, reach out via email or LinkedIn.
Education
- Master of Science. in Computer Science, University of Texas at Arlington
- Key Courses: Advanced Machine Learning, Data Structures & Algorithms, Big Data, AI, Cloud Computing, Neural Networks.
- Graduate Diploma in Deep Learning, University of Texas at Arlington
- Highlights: Neural Networks, Computer Vision, Data Analysis & Modeling Techniques.
- B.Tech in Electronics & Communication Engineering, K L University
Professional Experience
- Software Engineer - Machine Learning,Trustt
- Data Scientist, Tracxn
- Applied AI/ML Analyst, Charles Schwab
- Machine Learning Research Intern, Qutrix Solutions.
- Machine Learning Intern, Electronics Corporation of India Limited (ECIL).
Research Papers
- A Bidirectional People Counting Algorithm in Crowded Areas Arxiv Paper
- Proposed and implemented a new algorithm to count the people in crowded areas and achieved an accuracy of 96%.
- A Deep Learning Approach to Video Anomaly Detection using Convolutional Autoencoders Arxiv Paper
- Proposed an algorithm for detecting anomalies in videos using convolutional autoencoders and decoders on the UCSD dataset(99%).
Teaching
Teaching Assistant for the following courses at UTA:
- CSE5311: Design and Analysis of Algorithms
- CSE3313: Theory of Computation
- CSE5306: Distributed Systems
Certifications
Skills
Blog Posts
- 06/09/2023: Introduction to Convolutional Neural Networks Paper Review
- 10/15/2022: Built the academic lease system at University of Texas At Austin.
- 10/01/2022: Built the class room attendance at University of Texas At Arlington
- View All Blog Posts