I am a Medical Student at the College of Medicine of the University of the Philippines Manila - Philippine General Hospital. My academic background as written on my CV is mainly related to medicine & molecular biology, but in my idle recent past, I have worked on and delved into:
☞ the art of market price trends, patterns, & forecast methods
☞ the legalese of science & biotech patents
☞ the social network analysis and bibliometrics in scientific collaboration

Financial markets
As a previous day trader, technical analysis (TA) of Wall Street prices was my bread and butter. I lived, ate, and breathed such market jargon as volatility, momentum, relative strength, support, and resistance on a day-to-day basis. These are just some of the basic prediction tools of a market technician handling an NYSE (New York Stock Exchange) portfolio. Our office also had a very short, but insightful, experience handling shares from LSE (London Stock Exchange). TA augments fundamental analysis - i.e., the things you read on annual company reports and hear every day on CNBC and Bloomberg - to be able to make solid investment decisions.

Now that I am currently pursuing medical training, I am tempted to do some research in neurofinance and biopsychology. There are only a few labs in the world that focus on how the network of neurons in the central nervous system affect financial decisions and their outcomes.

Particularly, are traders' emotions a particular function of certain somatic hormones? Are these hormones the fundamental bridge between distinct neural control and episodes of autonomic dysfunctions, like palpitations on the trading floor? Does the exhiliration felt during extremely volatile days such as during the earnings season much like an overdose of dopamine or norepinephrine in anxiety or manic disorders?

More importantly, wouldn't it be great to imagine a future when all traders are more rational? Intraday traders are often told to practice emotion-free trading: to leave our feelings at the doorstep before we enter the trading floor. If someday we'd learn to manage our emotions during stressful trading hours, either by pharmacologic or behavioral means such as popping a miracle anti-stress pill or doing a groundbreaking yoga breathing technique of sorts, then maybe we wouldn't have those crazy days again when the DJIA & SP500 will dip so low after traders get panic attacks & lose their minds.

Network sociology
I had an opportunity to learn the methods of social network analysis, an intricate interdisciplinary study of micro- and macro-perspectives derived from relationships, e.g., colleague relations, online friendships, and patterns of connection. I have worked with social network analysis tools when I was previously affiliated with a local government agency that oversees a WHO-funded project. The venture has since moved on to another stage, but the amount of publication records proved to be a great source for network data, which was why I wrote a couple of personal papers on the applications of SNA & bibliometric tools (unfortunately, the process of peer review did not pan out).

In the future, of which I am uncertain, I believe that network sociology can play a big role in determining the impact of sociology on health and illness, inasmuchas Facebook and Twitter were never original in the tech industry; they are just technically the more successful reincarnations of Friendster and Multiply. Think of how infectious diseases are transmitted from person-to-person or how non-pharmacologic therapy (smoking cessation, diet maintenance, exercise regimens) are affected by the people that surround a patient suffering from lifestyle diseases. It's a huge topic for exploration, and a very timely health advocacy for our modern society.

Dynamic modeling
Now that I think about it, I think all of those seemingly disparate fields are tied to one common denominator: the constant need for dynamic modeling. Dynamic models strive to reflect the changes whether in real-time or as a simulation, foremost by taking into account that individual elements in a model are ever-changing as a result of past conditions or current influences. Market forecasting and network sociology are only two small examples of dynamic mathemical systems in the vastness of human experience. Dynamic modeling has a huge array of applications: infectious diseases, epidemiology, pharmacology, ecology, chemistry, economics, and geography to name a few.

I'm currently doing some personal practices on disease vector modeling, and I hope to do good at it, along with medical school, of course.

So, if I am the one you are looking for, simply drop me a note here --> mail [at] schubertmalbas [dot] net. Random friendly introductions are also welcome. Cheers!