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Halfway through my year research career working on program synthesis—the task of automatically constructing a program that satisfies a given high-level specification—I had a series of epiphanies that profoundly changed the way I approach research. Yes, I had a good and rising publication list, h-index, and awards.
Yes, I had a nice car and could take the occasional exotic vacation. Yet, the meaning, the legacy, and the sense of purpose were missing. On a flight home from a prestigious conference, I sat next to a woman who asked me to help her with an Excel problem, which I sheepishly admit that I was unable to solve.
However, that moment opened up a door for me: Could I approach research from a different value system than the one that academia had trained Personal research to?
This encounter propelled me to develop a research approach that I call the Four Big Bets. In the new paradigm, my goal is to solve real problems that real people are experiencing. In fact, I wanted to figure out the simplest problems that would yield the biggest benefits. So inspired by the woman I met on the airplane, I spent time on spreadsheet help forums and identified potential problems that program synthesis could solve.
While mining those forums, I discovered a clear problem: What if they could give an example of the output they are looking for Personal research the tool would figure out the script automatically?
In program synthesis, the goal is to create a computer program based on some high-level logical or programmatic specification. This has been a consistent challenge for a long time, with some recent breakthroughs.
Personal research instance, today program synthesis technologies are being used to discover new algorithms that would take humans months to discover, or for superoptimizing code that can be faster than the human-optimized code by several factors.
However, that instance is a program synthesis tool aimed at algorithm designers or performance experts. To help the 99 percent of people who want to automate their tasks and who are non-programmers, you have to start by listening to them.
When I started listening, I was looking for the simplest problem I could solve by using program synthesis and that would empower the most people to achieve more. I observed that these people struggled with simple spreadsheet transformations but were able to express their intent using input-output examples.
This led me to invent a programming-by-example synthesizer, now known as Flash Fillthat Excel really needed, and I wrote a research paper about solving that problem. By solving this problem, I met both of my goals: I became addicted to that success and started to apply that big bet — connect with customers — to other domains.
Big Bet Two The second big bet was to develop a framework to facilitate creating such synthesizers for different task domains or application areas. Instead of creating one implementation, and then another from scratch for each new domain, I wanted to do something bigger and better: The demand for program synthesis is fueled by two business needs: Both of these numbers would come way down if we could develop example-based synthesizers for the various domains of repetitive tasks that arise in these application areas.
These, in turn, can be facilitated by a general-purpose synthesis framework that would make it easy to create synthesizers for specific domains.
To develop such a framework, we had to modularize and generalize the key ideas behind the various domain-specific program synthesizers that we had already developed. We made multiple attempts, many of which failed, but some of which took us slowly and steadily to the ultimate insight that lay hidden behind all our synthesizers—which turned out to be a simple and powerful theory of inverse computations to guide the search backwards from input-output examples to programs.
This framework has since served as the foundation for designing and developing new domain-specific synthesis algorithms and implementations, yielding an order-of-magnitude improvement in our effectiveness to provide solutions for different verticals.
I want to point out that this approach to research takes a village. It takes interns, engineers, researchers and funders. Every time you re-implement an algorithm to a more general version, it takes time, money and skills. To make it production-ready requires even more effort, as I learned with the Excel team.
Big Bet Three Everything works better when research and engineering skills come together as part of one team committed to a single mission. Part of this learning came from my two years working with the Excel team to implement Flash Fill. Brilliant researchers without engineering skills may create one implementation; a lesser researcher with more engineering skills can try out multiple implementations in the same time, perhaps achieving a better result.
Research is about embracing uncertainty: Engineering is about removing uncertainty: These somewhat opposing values, when put together, lead to faster innovation. The other part of this learning happened from my years of experience leading multiple disconnected projects, each with a flux of contributors, creating high ramp-up costs for new participants.Personal Research Resources that are published by individuals who are sharing their own personal research with others online.
These presentations of personal research can include web sites, blogs, some wikis, Facebook pages, eBooks, family trees stored on commercial services, etc. The PRF can be used to assess normal adult personality in selection or counseling contexts, conduct research requiring comprehensive coverage of personality traits, assist with guidance and career counseling, and develop greater self-awareness and understanding of human behavior and motivation.
Personal research paper citations "in this essay i plan to prove that my belief is right because the book says so if you look at this one sentence without context.". Undergraduate Research and Graduate Opportunity website menu The personal statement can mean the difference between rejection and acceptance.
Personal Statements for Graduate School (Humanities) Everything that follows is an elaboration of this one main issue: graduate school is specific career training and apprenticeship for . Research is a systematic inquiry to describe, explain, predict and control the observed phenomenon. Research involves inductive and deductive methods (Babbie, ).
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