Aniruddh Nathani is a data scientist with experience in Python, SQL, Java, R, NLP, and machine learning algorithms. He has a Master's in Information Management from the University of Washington and a Bachelor's in IT from Shri G.S. Institute of Technology and Science in India. His past work includes developing predictive models for stock movements and natural language processing applications for data cleaning and classification. He is proficient in tools like Tableau, SQL Server, and Jupyter notebooks.
Progressive system engineer with 8 years of hands-on experience developing and implementing innovative software
products and solutions that significantly increase productivity and profitability. Adept at delivering high-quality products
while establishing solid analytical and problem solving abilities. Skilled using Core Java, PHP, OOP, Design Patterns,
SOA, Data Structure / Algorithms, JavaScript, jQuery, CSS, XML, HTML, JSON, MySQL, Oracle, and Informix while
leading comprehensive software development. Experienced in implementing application through entire Software
Development Life Cycle.
Worked as a Salesforce Certified Developer. My responsibilities at Cognizant included intensive programming in Apex programming language. It is just like JAVA, using an object-oriented concept including some portions of JavaScript. I took elaborate video conferences from onsite counterparts and assisted them with flexible yet pragmatic plans of development. I also completed a minor project with Python 3.6.2 in Jupyter Notebook.With regard to my ability to meet the specific requirements of this job, these are few of my past roles:
•Project: Omni Channel
Using Salesforce, I configured the service cloud platform where agents and customers can chat for any online help. This whole setup is known as ‘live agent configuration’ which is eventually used to make business more effective and efficient at communicating
•Project : SNAP Invalid Email Enhancements
Completed the business requirement of providing back-end logic for valid Email extensions so that no invalid or spam Email can be provided. This in turn provided more authenticity to the website and its usage
•Project: ORACLE CPQ CLOUD Enhancements
Single-handedly created the style sheets and co-ordinated with onsite counterparts to enhance the User Interface for the new version of ORACLE.
• Worked with the cloud-based software Salesforce.com that helps multi-level organizations such as GE and Symantec to generate prices and quotes for complex and configurable products.
• Created new marketing ideas for an online-delivery solution for international retail prospects with unique coding methods for each product.
• Implemented a live agent-based customized page through APEX language where client and agent can share their queries and get easy solutions.
• Developed web services using JSON format and sent the datasets to other data clients for domestic and international customers through online cloud products.
Certificate of completion for learning Data Analytics, Data Visualization, Python for Data Analytics, Introduction to Artificial Intelligence and Machine Learning.
Progressive system engineer with 8 years of hands-on experience developing and implementing innovative software
products and solutions that significantly increase productivity and profitability. Adept at delivering high-quality products
while establishing solid analytical and problem solving abilities. Skilled using Core Java, PHP, OOP, Design Patterns,
SOA, Data Structure / Algorithms, JavaScript, jQuery, CSS, XML, HTML, JSON, MySQL, Oracle, and Informix while
leading comprehensive software development. Experienced in implementing application through entire Software
Development Life Cycle.
Worked as a Salesforce Certified Developer. My responsibilities at Cognizant included intensive programming in Apex programming language. It is just like JAVA, using an object-oriented concept including some portions of JavaScript. I took elaborate video conferences from onsite counterparts and assisted them with flexible yet pragmatic plans of development. I also completed a minor project with Python 3.6.2 in Jupyter Notebook.With regard to my ability to meet the specific requirements of this job, these are few of my past roles:
•Project: Omni Channel
Using Salesforce, I configured the service cloud platform where agents and customers can chat for any online help. This whole setup is known as ‘live agent configuration’ which is eventually used to make business more effective and efficient at communicating
•Project : SNAP Invalid Email Enhancements
Completed the business requirement of providing back-end logic for valid Email extensions so that no invalid or spam Email can be provided. This in turn provided more authenticity to the website and its usage
•Project: ORACLE CPQ CLOUD Enhancements
Single-handedly created the style sheets and co-ordinated with onsite counterparts to enhance the User Interface for the new version of ORACLE.
• Worked with the cloud-based software Salesforce.com that helps multi-level organizations such as GE and Symantec to generate prices and quotes for complex and configurable products.
• Created new marketing ideas for an online-delivery solution for international retail prospects with unique coding methods for each product.
• Implemented a live agent-based customized page through APEX language where client and agent can share their queries and get easy solutions.
• Developed web services using JSON format and sent the datasets to other data clients for domestic and international customers through online cloud products.
Certificate of completion for learning Data Analytics, Data Visualization, Python for Data Analytics, Introduction to Artificial Intelligence and Machine Learning.
Masters of Computer Science Candidate with around 3 years of work experience in Java EE, Spring MVC, Hibernate, JavaScript, JQuery, Back End Software Development. Looking for an opportunity as a Full Stack Developer
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
1. Aniruddh Nathani
+1 (206)-267-8052 anathani@uw.edu linkedin.com/in/aniruddhnathani Seattle WA, 98105
Platforms Worked
Programming Skills: Python, SQL, Java, R, NLP, Android, PHP, HTML, CSS
Packages : NumPy, Pandas, Scikit-Learn, Matplotlib, Seaborn
Software Skills: SSMS, SSIS, Tableau, Netbeans, Android Studio, Firebase, Github, Jupyter, Microsoft-Excel, R-studio, MySQL.
Education
University of Washington, Seattle, WA
Master of Science in Information Management
Sept 2019- Jun 2021
Specialization – Data Science, Business Intelligence.
Shri G.S. Institute of Technology and Science, Indore, India
Bachelor of Engineering in Information Technology( GPA- 3.85/4)
Aug 2015- May 2019
Coursework- Software Engineering, Database Management System, Data Warehousing and Data Mining, Design and Analysis of
Algorithms, Computer Networking, Computer Architecture, Operating Systems.
Work Experience
Data Scientist - Xoriant Solutions Pvt. Ltd., Pune, India (Github) May 2018- June 2018
●Generated a Python script which could correct one-digit and two-digit errors in data set, scanned incorrectly by the Optical Reader.
●Applied Natural Language Processing and text Analytics for data cleaning, eliminated inflectional endings using Porter-Stemmer.
●Replaced them in a required Excel file using OpenPyxl in Python working on RegEx Python.
●Bagged best intern award for giving best company gains using the Python script.
Technical Projects (All projects: Github)
Project Lead - “Intelligent Question Bank” Jan 2019 – Mar 2019
●Developed software for the University portal which aimed at improving students subject knowledge using Machine Learning.
●Developed Adaptive learning module using KPI indexing to record student’s performance and present the next set of questions.
●Analysed student performance by applying Neural Network Algorithm and using a MEAN stack application.
●Recommended specified modules which increased student performance by 80%.
Project Lead - “Towards Ensemble Methods for Predicting of Stock Movement using Google Trends Data” Feb 2018 - Sept 2018
●Predicted stocks using Machine Learning by combining traditional Time Series Data, Technical Indicators and Google Trends Data.
●Acquired data using API of Alpha-Vantage website for accrued technical indicators values using Python.
●Employed Bagging (RandomForest) & Boosting (AdaBoost Classifier) techniques for the Ensemble model.
●Predicted stock with an accuracy of 84% based on 7 parameters.
Data Scientist - “Gender Prediction and Movie Reviews Classifiers” April 2018
●Developed Movie Reviews and Gender prediction applications using NaiveBayesClassifier.
●Tested and Trained datasets obtained from the NLTK corpus, Python Libraries.
●Achieved prediction accuracy of 90% with both the applications.
Android Developer - “Class Poll” March 2018-May 2018
●Allowed users to create, join and review on-going polls.
●Connected application with Firebase Database for instant updates.
Additional Roles
● Teacher: Taught Mathematics to students and English to GRE/TOEFL students at Swati Jain Academy, Indore. Oct’18- Aug 2019
● Co-Founder- Founded the official technical club “#Include” of the IT department at SGSITS, Indore. Sep ‘18- Aug 2019
● Content Editor- Edited annual magazines for SGSITS, as the head content editor. Jan ‘16 - May 2019
● Team Leader- Represented RGPV University at the Swimming Nationals Competitions held at Chandigarh. August 2016
● Top Ranker- Awarded “Dewang Mehta Excellence Award” for being the branch topper for two years. 2015 & 2016
