Sriniwas Pandey

Sriniwas Pandey

Doctoral Student



ABOUT ME

"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)

I see my self as an inquisitive person and a quick learner. I am adaptable, ebullient, calm, empathetic and prudent. I define myself, "a leader as a team player".

I, currently pursuing doctoral studies in the department of the Industrial and System Engineering, have a Masters and a Bachelors degree in Computer Science. Machine Learning, Algorithm Analysis, Data Analytics and Complex Networks are some of research areas, I am primarily interested. My experiences include working in industry, research and academia. Working in the acedemia, I am enhancing my mentoring and organization skills. I also worked as a research fellow for one of the prestigious institutes in India and a software developer in the IT industry.

Do not hesitate to contact me for more details and further discussions.

EDUCATION

Aug 2018 - Present

State University of New York at Binghamton, New York
Ph.D, Industrial & Systems Engineering, CGPA 4/4

Jul 2013 - Jul 2015

IIIT DM, Jabalpur India
M.Tech, Computer Science & Engineering, CGPA 9.4/10

Jul 2007 - Jun 2011

Uttarakhand Technical University, India
B.Tech, Computer Science & Engineering, 70/100

EXPERIENCE

Aug 2018 - Present

Binghamton University, NY, USA
Teaching Assistant: Computational Tools and Enterprise Systems Engineering

  • Delivering lectures
  • Evaluation and grading
  • Maintaining student records
  • Assisting students in their academic endeavors

Dec 2017 - Aug 2018

NPSEI Uttarakhand Technical University India
Assistant Professor (Computer Science department)

  • Preparing and delivering lectures
  • Conducting exams and seminars
  • In-charge of Computer Science department laboratories

Jul 2015 - Dec 2016

IIT Guwahati, India
Research Fellow

  • Worked in the domain of Wikipedia mining and data analytics
  • Worked as Teaching Assistant for courses Data Mining & Introduction to programming

Summer 2016

(C-DAC) (a premier R&D organization of Govt. of India)
Research Intern

  • Application of High-performance computing tools like (openMP, CUDA, MPI) in data mining.
  • Applied openMP constructs in Wikipedia mining

Feb 2012 - Jul 2013

Infosys Limited, India
Systems Engineer

  • Java application development using J2EE techniques like Java-Spring and Hibernate.
  • Application development for android platform for an insurance organization

SKILLS

Tools 7amp; technologies

  • SPSS
  • SAS
  • SIMIO
  • MATLAB
  • Hadoop - MapReduce
  • Weka

Languages

  • Python
  • R
  • Java/J2EE
  • C/C++/C#
  • PHP
  • JavaScript

WORKS

  • Mortality Rate Analysis in USA
    Sep 2018- Dec 2018

    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

  • Mining interesting patterns in Indian Language Wikipedia's edit histories
    July 2015 - December 2016

    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

  • Scalable Efficient Clustering methods for Large Data
    Jul 2013 - Jun 2015

    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.

  • Shared Near Neighbour Clustering algorithm based on Random walk model
    Jul 2013 - Jun 2015

    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.

PUBLICATION(S)

  • 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
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