Courses: Computational Tools and Enterprise Systems Engineering Duties include: • Delivering lectures, • Evaluation and grading • Maintaining student records • Assisting students in their academic endeavors
Doctoral Student @SUNY Binghamton. A Researcher, Coder, Coffee Drinker and Dreamer........ in reverse order.
"Sriniwas has a wonderful rapport with people of all ages, especially students. He is extremely organized and reliable. He can work independently and is able to follow through to ensure that the job gets done. He is a dependable, mature, and great supporter." -Dr Sraban Kr Mohanty (Former Supervisor and Professor)
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I have experience in Software development, Research and Academia.
Courses: Computational Tools and Enterprise Systems Engineering Duties include: • Delivering lectures, • Evaluation and grading • Maintaining student records • Assisting students in their academic endeavors
Courses: Operating Systems, Database management Duties include: • Preparing and delivering lectures • Conducting exams and seminars • Project Supervision • In-charge of Computer Science department laboratories
Worked in the domain of Wikipedia mining and data analytics • Worked as Teaching Assistant for courses Data Mining & Introduction to programming
• Application of High-performance computing tools like (openMP, CUDA, MPI) in data mining. • Applied openMP constructs in Wikipedia mining.
• Java application development using J2EE techniques like Java-Spring and Hibernate. • Application development for android platform for an insurance organization
Objective: Form clusters of demographic areas according to the mortality rate and various diseases.
Technology: Principal Component Analysis and Clustering
Outcome: Clusters of counties based on mortality rate and disease that can be used to form policies
Objective: Find interesting patterns in Indian languages Wikipedia edition edit histories.
Technology: Hadoop - MapReduce with Java.
Outcome: Identified some interesting editor behavior patterns for Hindi, Marathi, Telugu Wikipedia editions
Objective: Adapt the existing algorithms for large data without changing the core functionality and methodology of the algorithms.
Technology: External Memory model, C++, STXXL
Outcome: Designed a clustering algorithm for large datasets.
Objective: Design a new effective clustering algorithm with least restrictions on the shape, size, density and type of data.
Technology: Python, Random walk model
Outcome: Developed a new algorithm that combines concept of random walk with shared near neighbor technique.
Pandey S., Pankaj Kumar Y., Samal M., Sraban Kumar M. (2019) Nearest Neighbor-Based Clustering Algorithm for Large Data Sets. Advances in Computer Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 760. Springer, Singapore
Pandey S., Samal M., Mohanty S.K. (2020) An SNN-DBSCAN Based Clustering Algorithm for Big Data. In: Pati B., Panigrahi C., Buyya R., Li KC. (eds) Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 1082. Springer, Singapore.