Biology re­search in­ter­ests.

This is part of the ar­ti­cles col­lec­tion.


Based on my re­search ex­pe­ri­ence and my un­der­grad­u­ate stud­ies, my re­search in­ter­ests are:

Enchanced Sampling

Recent ad­vances in rare event sim­u­la­tions have yet to bear fruit in bi­o­log­i­cal sci­ences. Although rare events are ex­em­pli­fied by pro­tein fold­ing, newer sim­u­la­tion method­olo­gies (eg. FRESHS) have not been im­ple­mented or an­a­lyzed. Much of the ex­ist­ing lit­er­a­ture uses var­i­ous forms of REMD (replica ex­change mol­e­c­u­lar dy­nam­ics) and meta­dy­nam­ics, which mask cer­tain sys­tem fea­tures.

The analy­sis of (relatively) long timescale dy­nam­ics, such as, those found in bi­o­log­i­cal sys­tems are a nat­ural out­growth of my work on soft mat­ter and mol­e­c­u­lar dy­nam­ics.

Cognitive Simulations

Also of in­ter­est to me are the cog­ni­tive as­pects of the hu­man brain and the use of sto­chas­tic prob­a­bil­i­ties to sim­u­late neural ac­tiv­ity. There have only been the­o­ret­i­cal de­scrip­tions of such work till date.


(Quantum Studies & Simulations)

Quantum me­chan­i­cal analy­sis of sev­eral highly en­er­getic sys­tems will also be ben­e­fi­cial for sim­u­la­tion the­o­ries. Although sim­u­la­tions are clas­si­cal, coarse-grain­ing al­lows for ac­cu­rate the­o­ries to arise from clas­si­cal sys­tems.

Specifically, the re­sponse of com­pu­ta­tion­ally coarse-grained bac­te­ria to light sources is of in­ter­est to me on longer timescales (e.g., rare events, struc­tural changes). Such a model could also be gain­fully com­pared to a mul­ti­level quan­tum heat en­gine .

Big Data

Simulations aside, big data analy­sis is also of in­ter­est to me and I be­lieve that there are many in­sights to be gained by re­for­mu­la­tion and re-analy­sis of older data sets, es­pe­cially when these are com­bined with ma­chine learn­ing and newer sta­tis­ti­cal test­ing meth­ods.