A Short Biography
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(Recently the Charleston Post and Courier ran a
High Profile story about
my views of learning and the Internet. It captures the essence of what
I am all about.)
I grew up in Greensboro, N.C. in our home that backed onto an old forest filled
with ponds, creeks, an old cabin and lots of places to explore. With
my friends, we explored everywhere, brought little pond creatures back
and made aquariums to watch tadpoles change to frogs. I was full of
curiosity and my parents gave me freedom to chase my curiosity (as long
as I came home at dinner time).
I discovered the fun of engineering
from my dad - probably when I was 5 or 6 years old.
He taught me three wonderful lessons:
- Always open: He never met anyone he could not learn something from
- Anticipation: Good helpers knew what to do before their bosses knew what to do
- Brain food: Be curious
These lessons have proved to be long term tools in my life. Realizing that
everyone I met had something to teach me kept my mind open and curious
- sort of
viewing the world as one big open source community - long before open source
was even dreamed of.
The second lesson
exposed me to analytical thinking and anticipating multiple outcomes.
Many weekends he would take me on short trips to repair elevators.
My brother and I went together, but this was like oil and water - so
we traded these weekend aventures. When I went, I was his helper.
Early in my helping
career, I simply got in the way and demanded to be micromanaged. He
quickly pointed out to me that if he had to tell me everything to do - then
he was slower than if he did everything. Being a stubborn child, I simply
sat and watched, often falling to sleep. Soon I learned that watching was more
boring than helping so I started to learn about helping without supervision.
He impressed on me the fact that
I had to understand enough of what was going on so that I could anticipate
which tool he would need next. I learned that if I limited my anticipation
to a single path - then I was often wrong. If I expanded my anticipation
to multiple paths, then I could usually give him the tool he needed.
This became a game - could I walk through an entire elevator-repair episode
with a perfect next tool record? I never won this competition, but
I learned a lot about motor generator sets, AC drive motors, relay sequences,
leveling devices etc.
The art of accurate anticipation was predicated on my understanding the problem
we were solving. I discovered that often I did not know what I did not know so
it became necessary to develop skill in overtly identifying gaps in my
knowledge. I also realized that if I could not articulate the problem, then
I could not anticipate next tool needs.
If I could articulate the problem, and then asked
a few questions to fill gaps in my understanding, then I could
accurately anticipate. This skill proved essential
for everything I did - whether signal processing, medical databases,
software engineering, drug-ion channel interactions or arrhythmogenesis.
It was predicated on a lively curiosity, and a willingness to expose my
ignorance and his willingness to reward my curiosity and not punish my
lack of knowledge.
Now this skill continues to be an important part of my life and is
an essential skill for exploring my current chase of Internet-centric
learning and how to avoid the
My formal education was through the Greensboro public school system.
My geometry teacher, Mrs. Burnside, further improved my skill in
analytical thinking and anticipation. Mr. Johnson (Jabbo) was my physics
teacher and was an expert in igniting curiosity. These times, where
these teachers made education fun, gave me a hunger for problem solving
and new learning. My great teachers were balanced by some bad experiences.
The head librarian, where I worked part time, told me on several ocassions
that I would amount to nothing because I tried to turn everything into something
fun. Looking back, this comment forced me to critically assess whether
she was correct - or whether I had something special. Jabbo convinced me
I had something special.
I continued my education in electrical engineering at Duke.
I received the B.S. and M.S. degree in Electrical Engineering from
Duke University in 1963 and 1965 and my master's thesis was about
current distribution in the heart associated with external stimulation
(defibrillation and inducing fibrillation).
my Ph.D. degree in Biomedical Engineering and Biomathematics
from the University of North Carolina in 1968 (I was the first graduate
of the UNC program). During the last weeks before my final oral
presentation, Jim Grizzle and I worked out the Categorical General
Linear Model - possibly the most important work I did (other than my
I came to the Eugene Stead's Department of Medicine as an Associate
in 1966 and became an Assistant Professor of Medicine (computer science)
in 1968. I was one of the three founding members of the Duke Computer
Science department in 1971 and was promoted to Associate Professor of
Computer Science. In 1978 I was promoted to Professor of Computer Science
and Associate Professor of Medicine. In 1990, Joe Greenfield managed to
promote me to Professor
of Experimental Medicine in the Division of Cardiology. This joint
relationship between medicine and computer science has been a continuing
source of surprises (some even pleasant) and has provided a foundation for
attacking important problems in both the clinical and basic science
From 1993-1994, I was visiting professor of Biomedical
Engineering at the Indian Institute of Technology, and paid as an Indian
national (Rs 8500/month). Living as an Indian for a year was an unforgettable
In 1997, I retired from Duke and spend the fall as Fulbright
Scholar at the University of Patras. Then in January 1998, I joined the
faculty at the Medical University of South Carolina as Associate Provost
for Information Technology and Professor of Biometry/Epidemiology
and Professor of Medicine (Cardiology).
One can only be impressed with differences between elements used to
computational systems and those used to build biological computational
systems. Physical systems communicate with speeds approaching that of
light (.3 meter/nanosecond) while biological systems communicate
at a snail's pace:
10 meters/sec. Physical systems are built from switching elements that
enjoy a high degree of noise immunity while biological systems are composed
of switching elements that frequently fail and have a poor signal to noise
ratio. For me, it is interesting to probe biological systems in order to
develop an understanding of how biological systems can compute, recognize
patterns and "think" with such "poor" computing equipment, yet perform
these computations at speeds that shame "physical" computers.
With these physical components, biological systems operate efficiently,
robustly and perform a wide range of functions. In the brain, three
of these functions are learning concepts and facts (memorizing), remembering
and thinking. Learning is
the process of absorbing information and forming patterns in the brain.
Remembering is the process of recalling these patterns and creating
mental images of what we remember.
Thinking consists of taking these structures and creating new structures
reflecting something "new", a new concept or a new fact.
Today, computer memory is much more
reliable then human memory while computer thinking is worse. So its
interesting to consider a new educational paradigm where we
shift the emphasis
from memorizing-remembering to thinking,
relying on search engines and the internet for the
memory as opposed to traditional learning, i.e. content mastery via
the memorization route. The brain is highly complex and only now
are we beginning to understand the basics of memory. Understanding
to be quite a way in the future. But both are based on the interaction
between cells. Because the heart has a simplier cellular organization,
I started my research career there - exploring excitability of
cardiac cells, propagation and disturbances of excitability and
propagation associated with ion channel blockade, ischemia and
My research interests focus on two broad areas:
1: education and the two neural components: learning and thinking;
and 2: computational biology with a particular
emphasis on cardiac electrophysiology. My educational ideas,
specifically that of evolving an internet-centric
learning and working paradigm is described below. The electrophysiology
emphasis is described here.
Cardiac cells are arranged in a
more or less orderly manner and the nature of "cardiac computation" is
rather less complex than that associated with neuronal tissue. Consequently
cardiac "computation" hopefully reflects behavior of simpler and perhaps
generic mechanisms in comparison with neuronal networks and will be
easier to understand. My assumption is that if I can understand the
nature of "cardiac computation", i.e. initiation and control of cardiac
electrical excitation, then I can approach problems in more complex "nets"
of excitable cells, i.e. neural nets. This has been adequately demonstrated
by observing that properties of the biologically unrealistic FitzHugh-Nagumo
excitable cell reveals many generic properties that cannot be suppressed
with more complex and more realistic models of excitable cells. These
generic properties include: threshold of excitability, stable and
unstable (spontaneous oscillation) behavior, a refractory period,
wave motion and vulnerability.
Work at Duke, 1965-1997: Computational Biology:
Cardiac Electrophysiology and Teaching in Disguise
As an engineer in a Gene Stead's clinical department, I had free run
of the Dept of Medicine, with, of course, Gene's nudging me in a variety of
interesting directions. One of the most innovative pushes was to encourage me
to continue my relationship with Jim Grizzle at the UNC Dept of Biostatistics.
From 1968 until 1980, I designed and implemented an interactive, multiuser
computer system and database for monitoring physiologic parameters and
tracking patients with coronary artery disease. As
part of this work, I developed with J.E. Grizzle and G.G. Koch
at UNC, the
first non-iterative estimation procedure for categorical linear
models which became the foundation for testing many biomedical
hypotheses involving discrete (in contrast to continuous) data.
Today, the cardiology database is
the world's largest repository of data on patients with coronary artery
disease and is the basis of many research projects focused on clinical
decision support systems and cost/benefit analysis. Also the paper
with Jim is one of the most cited papers in biostatistics - establishing
new chapters in Statistics textbooks on analysis of categorical data
models. At MUSC I began to
explore ways to adapt the concepts learned with the Cardiac Database to
an institutional setting and realized that the move toward
compliance driven record keeping. By linking financial and clinical
data streams, it would be possible to build a financially feasible
clinical record based on the costs associated with maintaining a compliant
In 1980, Joe Greenfield took over as Chief of Cardiology and
"suggested" that I shift my
attention to cellular communication with emphasis on how drugs control
the communication between excitable (either cardiac or neuronal) cells.
Thus began a long and continuous relationship with Gus Grant and
Harold Strauss. Together we addressed a number of problems dealing
with drug-ion channel interactions and developed the guarded receptor
model of drug-channel chemistry.
By this time, it was clear that international collaboration would
greatly facilitate our attack on important clinical problems.
Members of the All Union Institute of Experimental and Clinical
Cardiology in Moscow approached us about working jointly to better
understand the side effects of drugs being developed in the then USSR.
This was the beginning of the development of a "Laboratory without walls"
that was linked by the Internet for continuous collaboration.
Our laboratory was the second (lost the race by 3 months)
to characterize the single channel behavior
of the cardiac sodium channel. In addition, we were
the first to develop a mathematical model and statistical
estimation procedure for characterizing drugs that interact with membrane
ionic channels. In 1987 we extended our laboratory to include
the Institute of Theoretical and Experimental Biophysics in Pushchino
Russia in Prof. V. I. Krinsky's autowave laboratory. Prof. Krinsky is
an authority on wavefront formation in excitable medium and together we
developed a model of reentrant cardiac arrhythmias that has proved useful
in evaluating drugs used to control heart rhythm disturbances in patients.
As a result of our theoretical studies of ion channel blockade, we developed
a clinical procedure for reversing the cardio-toxic effects of drugs that
influence cardiac and neuronal cells. Many abused substances including
tri-cyclic antidepressants, cocaine and synthetic opiate analgesics block
cardiac and neuronal sodium channels, and our procedure has been
found effective in reversing some of the cardiac consequences of drug overdose.
Currently, our laboratory is involved in cellular and tissue studies of
cardiac rhythms and mechanisms that initiate rhythm disturbances. We are
actively involved in developing efficient algorithms for
analysis of single channel and voltage clamp data from studies of
single cardiac cells, solution of
non-linear parabolic partial differential equations and exploring
of wave formation in non-linear excitable media. We are actively involved
in utilizing numerical studies to probe observations obtained during
cellular and patient studies. Our laboratory is tightly coupled with
the clinical cardiac electrophysiology service where patients provide another
source of challenging research questions. A good example is
our recent paper linking serveral inherited cardiac arrhythmias to
a single mutation and our numerical studies of how
mutant Na channels and
the cardiac vulnerable period.
1997 - 2006: A transition to the University of Patras and the
Medical University of South Carolina
1997 marked the start of a new era for me. I was awarded a Fulbright
Scholar teaching/research award and spent from July - January '98 as a visiting
professor of Medical Physics at the University of Patras in Greece.
It gave me the time to explore ideas in learning and education that
I had learned while at Duke. I managed to become adopted by the
community of Romanian students at the Univ. of Patras and they
proved very willing participants in our educational experiments. By
the end of my time, I could speak passable Greek, take underwater
photographs, ride a bicycle downhill into a 50 km/hr head wind and
facilitate learning with my Greek, Romanian and Bulgarian students. In
September (mid stream), I retired from Duke as Professor Emeritus of
Computer Science. In January, after returning from Patras, I accepted
a new challenge at the Medical University of South Carolina as Vice
Provost for Information Technology. Here, I tested many ideas about
education as well as continue my research with Xiaobai Sun, Gus Grant
and Maddy Spach and our international laboratory.
Applying ideas developed at Duke about problem solving and thinking:
The MUSC IT Lab
At MUSC, I have been quite active in applying all that I had learned
about learning, thinking and problem solving at Duke to
the MUSC setting. I started by adapting the MUSC environment
the "tool-based" problem solving
paradigm that Gus and I developed for his lab. The basic idea was to
follow the original UNIX paradigm of Dennis Richie, Brian Kernighan, and
Ken Thompson - i.e. to identify a primitive set of "filters" that could
be strung together to accomplish some goal - using the notion of a pipe.
(For a great survey of the early UNIX ideas, look at the ATT
Bell Lab Technical Journal vol 57, No. 6, Part 2, July-August 1978 and
vol 63, No. 8, Part 2, October 1984. The
IT Lab was the nucleus of
our tool-based revolution - a group of 6 of the friendliest guys you'll
The unstated idea in my strategy
is that we must build an infrastructure based
on commodity computing and global connectivity (internet) that would
foster building internet-centric learning and problem solving paradigms.
Why problem-solving? Because our economy has shifted to a service
economy which is predicated on problem solving (the service that is provided).
Our computing and communication infrastructure will provide for
individuals, the possibility to assembly a multidimensional workspace
of tools (one tool / dimension) that are matched to the problem environment.
The worker/learner then transports data from a variety of resources,
manipulates these data into new constructs and solves problems.
This strategy is not unlike that of thinking. Consider the brain -
its capable of three activities, learning, remembering and thinking.
Time spent learning and remembering,
that is memorizing and recalling patterns, cannot be spent thinking, that of
constructing new and interesting patterns from stored structures. With
commodity computing and global connectivity,
human memory becomes a liability - i.e. less
reliable than a computer's memory. On the other hand, human thinking
continues to be far superior to any machine-thinking models. So, our
goal is to create a workspace that capitalizes on machine memory and
shifts the emphasis of daily work from a dependence on human memory to
a dependence on internet accessible resources. (A criticism is that how
can you trust internet-accessible information? - and the answer is by
the same tool we use to judge any information - that of applying critical
analysis to the data. So we must start teaching analytical and critical
thinking at a more widespread level). Our workspace is focused on
solving problems, and because problem solving requires thinking and
accessing applicable information and insights, we automatically create
an environment for continuous learning. Problem solving in this
environment depends on chasing one's curiosity. To emphasize this
I would give every member of our community of learners
the following name tag:
Frank: Curiosity@Work or Mary: Curiosity@Work.
To press forward with this strategy,
we have already developed some useful tools for facilitating movement of data
around the campus and ultimately into various databases. We have tried to
be as standard's based as possible. The underlying notion is to capture
data via a web browser and move it around the institution in a way that
mimics paper flow. The underlying data capture device is a PDF or HTll form.
From input data,
we package the information into a portable format (tab delimited records, XML
objects etc) and move it into a database, often, mySQL.
The entire process of submitting and approving (or managing) data
is referred to as a
workflow manager. More recently Christopher Zorn has generalized
the concept of the workflow manager to base it on and XML message
switching system, jabber.
The back end
of the tool box, analysis and report generation is under active development,
We have some examples using XSL and LaTEK and a filter that converts
reports to PDF format. Our progress can be monitored at our web site:
The MUSC IT Lab.
To facilitate analysis and report generation, we have developed a number
of tools for importing and
MySiteMaker is a wonderful tool for building a web frontent to a
database, and reporting data back as either an HTML object, an XML
object, and MS Excel object or as a text file.
MyGrants is an example of
this interface to our Grant's database.
Most recently we have been exploring ways to establish our tools
as web services, and Christopher has taken ispell, the unix spell
checking utility and established
a spell check web service . The idea is to invoke a server side
utility via a GET or PUT that then makes a SOAP call to the ispell
utility. As implemented, the utility can be incorporated as a
bookmarklet so that just about any browser-displayed text can be
spell checked, independent of the application that generated the display.
2006 - Present: Duke-NUS Graduate Medical School Singapore
Exploring Problem solving, Problem-based learning and
an Internet-centric workspace: Current activities
More recently we have been focusing on a 21st century learning paradigm -
founded on an internet-centric workspace for learners at GMS
(i.e. faculty and students and staff). The obvious strategy is to bring
to the desktop a variety of proprietary and open source tools that
facilitate access to information and problem solving. The not so obvious
strategy is to actually develop a way of thinking that integrates the
Internet and Internet resources into virtually every action we take.
When I am awake, I am either thinking, doing, learning or remembering. All
of the mental energy that I have is divided between these four activities.
For the first time in my life, I have realized that the Internet and
Google give me the freedom to retarget mental energy - shifting it away
from remembering and toward either thinking, learning or doing. It seems
obvious to me that this is a no brainer - but few understand the rationale.
I have been surprised how few faculty can accurately articulate the basis of
the learning curve and the
forgetting curve are. I know that I can
remember almost nothing unless I repeat what I want to remember. There
is sufficient evidence from the neurobiology community to state that
repetition is the first law of learning. Similarly, lack of repetition of
learned material will lead to forgetting (as described in the above link).
Since I know I am not going to remember infrequently used information,
why not substitute Google and Internet resources for some of my remembering?
The major objection is that Internet material is unreviewed. I never had
any difficulty with this concept because I know that much reviewed material
is simply wrong. What is missing is a skill in analytical or critical
The time is right to recognize what search engines and Internet connectivity
bring to both the learning process and our daily work. Work, based on
using our Internet memory is continuous learning - something that is a
byproduct of retargeting remembering energy to learning/thinking or doing.
I assert that global connectivity
provided by the internet levels the "access to information" playing field,
and am confident that we can shift effort from learning/remembering to
thinking in such a manner that the traditional boundary between
learning and working is blurred. Rather everyone is solving a problem in
a manner that gaining access to new ideas and insights is part of problem
solving. In other words, lifelong learning is now indistinguishable from
problem solving (work).
To facilitate bringing these tools to the desktop,
we have built
The Duke-NUS learner's portal that can
be customized by the end user. Our goal is to enable folks to chase
their curiosity without getting bogged down in the mechanics of chasing.
So, someone with some artistic talent, but with little skill in actual
painting might use photography, GIMP and some artistic filters to create
impressionistic rendering of interesting photos. Photography captures
an interesting scene, GIMP takes care of the
mechanics of distorting this image in order to create some interesting
artistic expression of an idea,
while the internet and a browser provide entrance to art of others (examples).
You are left with only the task of investing your own energy, enabling
you to chase your curiosity.
Gene Stead's Web Site and Web Logs
In March, Josh and I visited Gene at the lake and over the next several
months, built a small web site
John Williams became my surrogate at the lake. The web site was a struggle
and Gene managed to delete email and other small things that cast a shadow
on our work. Then we hit on the idea of a web log
that seemed to provide a more robust tool for communication with his
friends, colleagues and former house officers. The web log did not
work out as spammers continued to clutter it up. The web site has
grown to include some of his essays, and now a section for essays
This has been a very interesting challenge - and I am certain there will
be new challenges and surprises.
Distractions - large and small
In Singapore, wall-to-wall people get to me. So I have found escapes. I
can escape to South India, Thailand, Malaysia, Indonesia and China. Within
Singapore, I explore the lives and behavior of small insects - mostly
spiders. In Charleston, I discovered
Singapore, there is a cousin,
. Recently I found
that there exist kleptoparasitic spiders, specificaly
. These little orange spiders eat the web of
host spiders as well as steal their captured insects. Sharing this with my
grandkids produced a web site: