HITESHRI PATEL

Address:-*** S Olds Blvd, Phone No:- 267-***-**** Apt:- B 31 Email:-adnaix@r.postjobfree.com

Fairless Hills, Resident status:-Permanent

PA:19030

Objective:-

Computer science graduate having 6 plus month experience in software development using HTML, CSS and MY SQL.

Computer science post graduate having 6 month experience in research skill using python, machine learning.

To strong knowledge and experience in working with relational database, such as My SQL, function, android development and IOT.

Strong knowledge of OOP’s concept and also ability to learn the code in multiple languages such as C, C++,java, python, etc.

I will start my career with a company to learn, grow and also gain best experience. Education:-

Master of engineering(2017-2019) in software engineering G. H. Patel college of engineering & technology with 8.03CGPA at anand, Gujarat.

Research

Paper

No.

Title of paper Journal Name Publication Status

1 “Crop Yield

Prediction Using

Supervised

Learning

Techniques”

International

Conference on

Intelligent Computing

Control

Systems(ICICCS

2019)

IEEE Xplore Accepted

Bachelor of engineering(2013-1017) in computer engineering Madhuben and Bhanubhai Patel Institute of technology with 8.44CGPA at anand, Gujarat. Work Experience:-

ARVI (Software engineer):

Worked on a CSS Background, CSS text, CSS border, CSS Margin, CSS Padding, CSS Table and CSS elements in CSS.

Create and maintain software documentation.

Performed front end and backward server side coding.

Strong experience in IOT hardware as well as software.

Test the I/O devices in farm system.

Based the client feedback maintenance in hardware and software system.

Hands on experience with constrained devices such as Arduino, Raspberry-pi. Assistant Professor:

Spec College, Anand

Only 6 month experience to assist the student individually and groups.

Handled undergraduate course classes.

Maintained and active research program and motivated active participation.

Provided depth support in research activities and document findings

Attend the regular conference, training and professional seminars.

Monitored the student progress and provided appropriate feed-backs. Skills:-

Technology:-

Programming languages: C,C++ and java,Python,Sql and R. Web Designing and scripting languages:-Html,CSS,java script,PHP,XML, Ms Office (Ms Power point, MS Excel and MS Word)

Database:-My sql server(2000/05/08)

Operating System:- Windows,linux

Standard Framework:-Servlet,json,JDBC.

Knowledge About Android Studio and Eclipse and .Anaconda. Personal:-

Attended seminar on “Game Development” organized in college.

Attended seminar on “Android Development” organized in college.

Attended seminar on “IOT” organized in college.

Attended Virtual Reality Seminar in GCET College.

Participated in co-curricular activities held at college(technical/non technical)..

Flexibility and Adaptability to work in any environment.

Good at event management.

Can work individually or in a team as well.

Curriculum project:-

1)Helpful application used for farmer (IOT).

There will be several sensors for make farming easier and faster. soil moisture sensor which is measure the water quantity. If water is required for plant then message will be sent to the farmer. if plants needed water then farmer can on the water supply automatically by pressing key ON in mobile phone and sufficient water is given to plant then farmer can stop water supply by switching OFF on mobile phone.

Utilized:- Android studio 2.1.2,XML, Android API s, Hardware Tolls such as Soil moisture senor, rain sensor, humidity sensor, Temperature sensor, Arduino micro controller and Node MCU, Esp 8266.

2)Crop Yield Prediction(Machine learning)

Data collected from United States in 2013 year which have total 26 features. Aim is to Deciding which features are more effective for increasing the crop growth using feature engineering to reduce the features without affecting the decreasing crop yield is of vital importance. The problem of predicting the crop yield is formalized as a prediction rule, where Multi Linear Regression(MLR), Polynomial Regression(PR), Support Vector Regression(SVR), Decision Tree Regression(DTR), Random Forest Regression(RFR) will be used. Utilized:-Anaconda, Heat Map, feature Extraction, Feature Selection and different kinds of error such as a MSE, MAE, R2

and RMSE.

Declaration:

I, Hiteshri Patel, hereby declare that the information given above is true to the best of my knowledge. I have all my documents ready with me which I can show you upon request. Hiteshri Patel

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