Specialization – Mathematics: Dr.K.Kavita was born on January 1 st ,1979 in Andhra Pradesh, India. She obtained PhD from Sri Venkateswara University,Tirupathi,India, 2013. Dr.K.Kavitha is presently working as an Associate.Professor in the department of Mathematics in BVRIT Hyderabad College of Engineering for Women , Bachupally,Hyderabad,India.She has 18 years of experience. Read More Dr.k.kavitha, Associate .Prof at BVRIT Hyderabad College of Engineering for Girls. She obtained the degree of Doctor of Philosophy in the field of “Fluid Mechanics “from S.V.University in 2013 after graduating with Masters from dept of Mathematics, S.K.University. Has published one Book in the field of fluid mechanics, publishing another book in the month of December -2019 & 23 refereed Journals & Conferences. Has 18 years experience in teaching .Has an interest in Theology and deeply interested in spiritual traditions, knowledge & Philosophy and also interested in musical traditions of both east and west. Learnt classical dance and Life member of many associations like APSMS, ISCI and so on. Had the privilege of teaching a great many students in my career who made teaching a wonderful learning experience for students. It would be impossible to name all of them. Her autobiography was included in “Asia who’s is who and “Famous India who’s who in the world in 2018 , completed “10 tips for writing a truly terrible review “ , “10 reasons to get and use –an ORCID iD“ online certified Module courses in December 2017 ,March -2018 from ELSEVIER. Completed Data base Design , Data base Programming with SQL Certified courses from ORACLE Academy in 20 th March ,2017.She completed online certifications ,Mentorship certification courses from IIT’s ,Stanford University…with Elite, 90 percentage as grade .She visited two countries Zambia and Malaysia for presenting International conferences. She received two awards from International bodies. She invited as keynote speaker for International conference in Zambia. She received best paper award in International conference in Zambia. She delivers lectures in National and International Organizations , Universities like Zambia DMI University ,JNTU H for the students (M.TECH, B.TECH, M.Sc) as Guest Faculty. She maintains a very vibrant academic atmosphere through various academic initiatives in the class and department. Actively contributes to the academic vibrancy in the dept by arranging various activities like Regular seminars, Case studies, charts, Google class Room, Flipped classes room and so on .I made significant research/Models contributions to Science, Engineering& Humanities fields which empowers the next generation of students with a world class education. She has been teaching the Engineering Mathematics, Operational Research, Quantitative techniques for Managerial Decisions, Statistics for Managers,RMSA,FLAT,Computer Applications for Business for B.Tech,M.Tech,MBA,M.Sc,PhD students in her teaching and research career. She recently appointed as reviewer for Elsevier Journal Articles. She also serves as R &D Cell coordinator ,Psychology Coordinator ,subject expert, Evaluator, Website coordinator, Student counselor, Wall Magazine coordinator, Mentor for I st B.Tech Students, Cultural coordinator, Result Analysis for improvement of pass percentage coordinator, Asst.Convener for Cybernatics-07 A National level Paper presentation contest, Member in Grievance and Redressal cell, Coordinator for AICTE,JNTU related works, Fortnight Attendance coordinator , Designed Magazine &Brochure of the college in AITS , Organized Mathematics day events from 2005 to till date.

Summary The global "Mathematics Software" analysis offers in-depth perceptions of the size of the market by product type, application, and end-user. Based on their expenses, gross margins, revenue, market share, income, goods, and other firm information, the top rivals in the global "Mathematics Software" market research are evaluated. The research offers a thorough analysis of the supply chain, global marketing, opportunities, risks, and demand variables in order to accurately predict the global "Mathematics Software" category. Additionally, a number of strategies—including expansion, collaborations, mergers and acquisitions, production base, key player analysis, and key player sales—have all been carefully looked at in this study. This study includes a thorough description of significant industry developments, requirements, and regulations as well as the micro and macroeconomic metrics used in this study. The primary market driving factors, difficulties, and dangers that have an impact on growth patterns are also tracked in the global market overview section of this market report. The market was investigated in light of expected customer demand. The reader may find this research data useful in understanding the quantitative growth elements of the global "Mathematics Software" market. The "Mathematics Software" market research also offers detailed segmentation of the global market overview and a thorough traction analysis of the entire "Mathematics Software" market globally. The global market report provides verified market research to assess the leading vendors by integrating all necessary goods and services to pinpoint the positions of the key industry participants in the "Mathematics Software" market. Similar to this, the global "Mathematics Software" market offers a thorough analysis of cutting-edge competitor research as well as emerging market trends with market drivers, constraints, challenges, and lucrative opportunities to provide accurate insights and the most recent information for well-informed decisions. By examining the competitive landscape of the leading players and supporting businesses in securing their share by being aware of the various growth plans, the global "Mathematics Software" market report also offers a comprehensive view of the global market. Free Sample Report + All Related Graphs & Charts @ https://www.adroitmarketresearch.com/contacts/request-sample/2147 Different market sizes have been forecasted for all categories and sub-segments using a bottom-up methodology based on previous and expected patterns. This study provides an overview of the industry, sales data from the past and the future, a growth analysis, statistics on costs, production, and demand, and a business prediction. The "Mathematics Software" research study examines the important industry dynamics and significant sub-segments. Likewise, from a market standpoint, the 'Mathematics Software' research includes each top supplier in the global market's share and production capabilities. Purchase the report at https://www.adroitmarketresearch.com/researchreport/purchase/2147 Key Points Covered in the Report: A thorough analysis of value and volume at the worldwide, sector, and regional levels is included in the global 'Mathematics Software' market report. The study offers a full business size 'Mathematics Software' from a global point of view through a review of past facts and possible scenarios. Geographically, the Mathematics Software of market analysis includes the number of regions and their contrast of revenue. The The market analysis focuses on ex-factory costs, output volume, market share & sales for every manufacturer on a company level basis. Key Reasons to Purchase this Report: A comprehensive study of market size, share and dynamics is a global 'Mathematics Software' market research report and a thorough survey of developments in the field. It offers an in-depth overview of revenue growth and an analysis of the total business benefits. In addition to the strategic landscape for commodity pricing and marketing, the 'Mathematics Software' industry research also provides key players. This is a new post covering the latest impact on the target market. The research report addresses the rapidly evolving market climate as well as the initial and future impact assessment. ABOUT US: Adroit Market Research is an India-based business analytics and consulting company. Our target audience is a wide range of corporations, manufacturing companies, product/technology development institutions and industry associations that require understanding of a market’s size, key trends, participants and future outlook of an industry. We intend to become our clients’ knowledge partner and provide them with valuable market insights to help create opportunities that increase their revenues. We follow a code– Explore, Learn and Transform. At our core, we are curious people who love to identify and understand industry patterns, create an insightful study around our findings and churn out money-making roadmaps. CONTACT US: Ryan Johnson Account Manager Global 3131 McKinney Ave Ste 600, Dallas, TX 75204, U.S.A Phone No.: USA: +1 9726644514/ +91 9665341414

This is my personalized collection of mathematical resources with applications in quant finance, engineering and computing in general

My structured journey learning Python for mathematics, data science and quantitative applications.

Comparing predicted options prices using Black-Scholes and the Heston model to market-observed prices. Application of Mathematical Methods for Quantitative Finance

A Quantitative Finance project implementing Value-at-Risk (VaR) models. This repository demonstrates the application of Actuarial Mathematics to Market Risk management using SQL for data engineering and Python for statistical modeling.

Quant-Lab is a dedicated space for implementing and bench-marking core quantitative finance algorithms. This repository serves as a technical portfolio, showcasing the application of mathematical theory to financial engineering problems.

Quant Technical Indicator Lab is a research-oriented Streamlit application for systematic market analysis. All technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands) are implemented from scratch with full parameter control, transparent mathematics, and signal generation designed for quantitative research workflows.

Lesson 4: Three-State Economy, where we extend financial modeling beyond simple two-state scenarios to more realistic multi-state environments. This lesson bridges advanced mathematical concepts with practical financial applications through Python programming, preparing students for real-world quantitative finance challenges.

Important Note: Apply only if you have valid work authorization in the United States. The Client will not provide any visa sponsorship. Opportunity: One of our Major Banking clients in the United States is looking for a “Quantitative Analytics Senior Associate” for a full-time opportunity with 100% remote work possible Job description: Position: Quantitative Analytics Senior Associate - Financial Crimes Consultant Position Type: Fulltime role Location: Cleveland, OH (100% remote possible) Under Quantitative Analytics Sr. Manager’s supervision, the Quantitative Analytics Sr. Associate is primarily responsible for conducting quantitative modeling and analytics of financial crimes. Leveraging both current and emerging technologies and applications, this role covers all key aspects of model development and analytics, i.e. data identification and gathering, methodology/technique selection, performance assessment, documentation, and ongoing monitoring. Essential job functions • Under Quantitative Analytics Sr. Manager’s oversight, perform a broad range of quantitative works, including model development and ad hoc analytics to address financial crime compliance needs in AML/BSA/OFAC • Research, compile and evaluate large sets of data to assess quality and determine suitability for model building • Develop/maintain internal models and test/configure vendor solutions to ensure conceptually sound design, proper implementation, and acceptable model performance • Document model development process and outcomes properly and support model validation and review • Employ innovative techniques to drive continuous improvements in model effectiveness and efficiency, e.g. reducing false positives • Proactively develop and build technical skills and business knowledge; and effectively collaborate with compliance, technology, and risk partners Required Qualifications • Master’s degree (or its equivalent) in statistics, mathematics, economics, computer science, data sciences, predictive modeling, or other quantitative disciplines and at least 3 years of relevant experience, preferred in AML/BSA, OFAC, or fraud modeling/analytics • Solid expertise with both traditional and Machine Learning (ML)/Artificial Intelligence (AI) modeling practice and solutions • Hands-on work experience with statistical coding in SAS and/or Python • Knowledge of and ability to leverage traditional databases, cloud-based computing, and distribution computing • Knowledge of financial crime regulatory requirements, technology, and data analysis best practices • Excellent verbal, written and visual communication skills; ability to translate technical observations to a non-technical audience