I am currently enrolled in Computer Science and Information Systems program for the Fall 2015 term. I am writing to apply for ‘Internship’ position. I am interested and excited about the position at your company because it offers an ideal opportunity to expand my knowledge. I am currently working as a “Grader” under Dr.Kraft and also at Events and Building Services.
For nearly a year and half as a software professional, I have built an array of valuable skills in the professional world. During this time, my experiences have contributed significantly to my professional growth. I played an important role in organizing annual Google cooperate celebration. Involved in social campaigns organized at Swami Vivekanandha Matt. I took part in conducting college level fests and annual day celebrations.
Pursued Masters in Software Engineering (MTECH-SE) which increased my subject knowledge immensely. During my under graduation, I have presented various papers in national level technical symposiums and the noted one among them which secured first place was a paper on ‘Haptic Computing’.
I enjoy using computers and have extensive experience with application software. As can be seen through my academic and professional record, I love to be challenged, to work hard, and to excel. Through these experiences, I have been able to enhance my analytical abilities and express my creativity. In both academics and employment, I am self-motivated and dedicated. I work not only until the job is done, but also until it is done well. These experiences demonstrate my organizational and management skills and ability to work well as part of a team.
As a proactive and dependable individual, I believe my experiences and track record make me an excellent fit for this opportunity. If you have any questions or require any additional information, please contact me on my email address or mobile number mentioned in the heading. Thank you for reviewing my credentials for this position. I look forward to hearing from you.
| : Windows, Linux | |
| : C,C++, Java | |
| : MySQL,DB2,Oracle | |
| : HTML, JavaScript | |
| : Assembling, Troubleshooting |
| M-TECH in Software Engineering JNTU, Hyderabad – School of Information Technology | 2012 – 2014 73.5% |
| B.Tech-Computer Science Engineering VMIT,JNTU, Hyderabad | 2008 - 2012 79.7% |
| Higher Secondary - BIE – Maths, Physics, Chemistry Sri Chaitanya Junior College | 2008 79.6% |
| High School – SSC St Mary’s High school, Hyderabad | 2006 81.1% |
For studying issues such as prognostication of vehicle traffic and spread of contagious diseases, investigating human movement behavior is important. The telecom’s mobility management is an ideal mechanism for studying human movement issues, since mobile telecom network can efficiently monitor the movement of mobile users. The problem can be abstracted as follows: What is the probability after T hours that a person at location A will move to location B. The answer is not possible to obtain directly because commercial telecom networks do not exactly trace the movement history of every mobile user. In this paper, how to use the standard outputs (call arrival rates, handover rates, call traffic and call holding time) measured in a mobile telecom network and how to derive the answer for this problem is shown.
Our solution is the first work that can statistically answer this question by effectively utilizing the statistics collected from millions of mobile users. A wireless sensor network technology is utilized to obtain high-resolution data of close proximity interactions which cause the spread of most contagious diseases. However, this method needs extra effort to distribute the senor network motes, and is constrained in a small area. The observed time difference of arrival (OTDOA) method utilizes trilateration to determine the mobile user’s position. At least three concurrent downlink signals from different cells are measured by the mobile phone. The time differences among the signal arrivals are calculated to form hyperbolic curves. This model is to predict how people spread from one location to another after a period of time.
This information is very useful to investigate issues such as prediction of vehicle traffic and spread of contagious diseases. The standard statistics provided by a commercial mobile telecom network are used as inputs of our prediction model. Experiments indicate that if the measured time slot is smaller than the expected cell residence time, and is not close to the expected call holding time, then good accuracy of the prediction model can be expected.
2) SAT: A Security Architecture Achieving Anonymity and Traceability in WMN’sAnonymity provides protection for users to enjoy network services without being traced. On the other hand, the network authority requires conditional anonymity such that misbehaving entities in the network remain traceable. SAT is a security architecture to ensure unconditional anonymity for honest users and traceability of misbehaving users for network authorities in WMNs. Our system borrows the blind signature technique from payment systems, and hence, can achieve the anonymity of unlinking user identities from activities, as well as the traceability of misbehaving users.