Development of method to extract information/underlying dynamics using physical or statistical principles from the data analysis will always lead to research degree/Ph.D.

So incorporation of such developed method with Big data in cloud environment to solve a problem with good inference would certainly lead to a Ph.D.

Development of algorithm or program mayn't lead to research publications/patents hence methodology development only helps get scientific outcome whereby analyzing data for extracting information by clustering, correlation and bring intelligence to machine by applying learning techniques and making scientific inference is of great value to the society those using the data in real life. Many physiological, bioinformatics problems are yet unsolved to work on this theme. Hope it helps.

Not in every research field the Big data collections are precise enough to extract from them the hidden knowledge. But in thermophysical databases now the level of precision is high enough to overcome the barrier of the inverse problem.

I have developed effective methods to extract hidden knowledge from extra precise databases and came to very important and no obvious discoveries, which may be put into basis of many PhD research works. These methods can be used in every field of knowledge, where the precision of collected experimental data is high enough.

I am looking for talented followers to develop further this novel direction of scientific research.

Conference Paper B Sedunov - The Physics of Clusters in Real Gases ATINER's C...

Conference Paper The Molecular Physics of Chain Clusters

I think we are free to use any kind of methods in doing the research, included the PhD research. The most important is whether research has fulfilled the characteristics of scientific terms. Until now, no one can limit our methods to do the research. One thing that we think is our method should answer the problems of our research.

I have started my research as bigdata analytics in bioinformatics. Bioinformatics is field that deals with large amount of data. big data can be used in this field for prediction mechanism. eg: Disease prediction,personalized health care, drug discovery,virtual screening,protein docking etc. 

Development of method to extract information/underlying dynamics using physical or statistical principles from the data analysis will always lead to research degree/Ph.D.

So incorporation of such developed method with Big data in cloud environment to solve a problem with good inference would certainly lead to a Ph.D.

Development of algorithm or program mayn't lead to research publications/patents hence methodology development only helps get scientific outcome whereby analyzing data for extracting information by clustering, correlation and bring intelligence to machine by applying learning techniques and making scientific inference is of great value to the society those using the data in real life. Many physiological, bioinformatics problems are yet unsolved to work on this theme. Hope it helps.

Dear Mayukha Pal, I agree with you that the content of research and new discoveries may be easier put into PhD thesis than the computational methods. But I managed to create and use the Hybrid Intellect system that provides an effective cooperation of the researcher and computer in analyzing the big data. The computer returns intermediate results of the analysis in a form of diagrams and the researcher can improve his data processing algorithms, thus coming to new discoveries.

Book Discovering the Cluster World

Article Review: Discovering the Cluster World. Clusters’ Hidden Para...

Dear Prof. Boris, Appreciate for enlightening your technique and research work on thermophysical system data analytics. Do you have a research paper that showcase the method that I could refer to in detail. Otherhand, I was thinking some of the semi & fully supervised machine learning techniques could make the feedback loop automatic there by finding % error for closeness check to the forecasted result and auto-improvisation by continual learning to make system/machine adoptive & intelligent system for big data analytics. Do you think any of this could be applied in your method for future scope of research.

I was referring to your comment: I am looking for talented followers to develop further this novel direction of scientific research.

Let's discuss in details thru email if this is of any interest.

Regards,

Dr. Mayukha Pal

[email protected]

Dear Mayukha Pal, thanks for your interest to my research methods and results. I sometimes think about expanding the processing power of computers, used for my analysis. I suppose, it will be needed, when the basic algorithms are finally worked out. Then, the realization of these algorithms on a powerful computer may give a noticeable effect.

The super-power may be needed, if we try to join the molecular dynamics simulation with the big data analysis. My analysis provides guide lights for molecular dynamics simulations. Without these guides the simulation leads to results, staying far from reality.

But now I am in a state of these algorithms development, testing and improvement. For different substances and temperature-density ranges are needed different algorithms. For this task I need in computer-helper, which can immediately show me intermediate results in a form of diagrams just I could make needed corrections in raw algorithms. I do not believe that computer can substitute the researcher in discovering new physical phenomena. The main task is to organize an effective researcher-computer cooperation to discover new phenomena, hidden in the big data collections.

On this way I came to many new discoveries, because behind any working algorithm of the data processing stays some unknown before physical mechanism. But to discover new physical phenomenon you should understand the basic physics and chemistry of the studied substances. Here it is important to escape from traps, left by some scientists in a form of wrong statements.

The main motivation for me to analyze the experimental thermophysical data were contradictions in different statements spread over many manuals. So, with the big data analysis I fight against wrong statements in the physics-chemical literature. 

If you are interested in this direction of research, I can try to find for you a direction that will be based on your potential and will bring new valuable results. Please, inform me about your scientific interests and your personal experience just I could formulate an introductory task for you.

Best regards,

Professor Boris Sedunov

Dear Mayukha Pal, I can suggest you a purely mathematical problem. I understand that it takes much time to study physics and chemistry on professional level. But in the big data analysis there are problems, connected with errors in experimental data. Even if the data are smoothed, there are still left slowly changing errors. To suppress these errors we should develop a special mathematical method, but respecting physical laws. For example, regular, almost linear functions, can be curved at small arguments. It is unphysical and we should build a theory of physically correct functions. This theory may be used in many fields of knowledge and may be presented as a PhD dissertation.

Best regards,

Professor Boris Sedunov

Wow, I am Inspired by the answers of all researchers. they provided a very detailed and clear ideas about research. as in my opinion... YES we can use Big Data Analytics to Analyze & Derive New Areas for PhD Research. for doing this we will only need the data of top journals for a domain (e.g Computer Science, Applied Sciences, Engineering etc.) If we get that data then Data science can be used to extract features of documents, these features can be taken as the areas of research of that document. which can be further statistically analysed to get the percentage of different research areas in that journal, same can be applied to all journals to get the final result.

thanks!

Dear Muhammad Aamir, I advice your PhD students to use the NIST Database  for Thermophysical Properties of Fluids. I managed to extract from this Database many discoveries. And I am sure, much more will be discovered in future. The method of these data analysis can be transfered to other precise sources of big data.

Dear Prof. Boris, Thank you for  your suggestion. i will follow it. as i used NIST test suites for my colleagues encryption algorithms testing. and as m also a PhD student. so i will go through NIST database for getting some useful data. i am also thinking about using crawler for getting data from google scholar and ieee.

Dear Muhammad, if you meet a difficulty in the work with the NIST Database of Thermophysical Properties, do not hesitate and ask me to help you.