Under the efforts of Dr. Cheng and his research team in the National Taiwan University Hospital, they have developed several strategies in the research of cancer vaccine and immunotherapy. The main feature of these therapies is that it could eliminate cancer cells not only in local parts of the body, but also over the whole body. Besides, it has the distinct advantage of attacking only cancer cells without damaging normal cells.

   Dr. Cheng mostly based on these advanced kinds of cancer vaccine and immunotherapy to develop cervical cancer vaccine and immunotherapy. Because cervical cancer cells always present specific antigens of HPV, Dr. Cheng used molecular techniques to construct DNA vectors carrying the HPV E6 or E7 gene, and then an auxiliary molecule preceding and following the E6 or E7. These E6 or E7 chimeric molecules can enhance the numbers of E6 or E7-specific cytotoxic T cells which can recognize cervical cancer cells presenting antigens of E6 or E7 and eliminate these cancer cells. During the two years of research at The John Hopkins University, Dr. Cheng demonstrated that these integral DNA vaccines effectively eliminate all the cervical cancer cells which present E7 antigen in the animal experiments.

   Professor Chen Ming-syan first devoted himself to the exploration of the modes of web-log mining, and subsequently developed the incremental mining method, which refers to a sectional mining method when there is only partial change in the data base. This new method can be expanded into a new technology for data stream mining, has valued both in theory and in practice, and is considered to be conducive to the mining of internet data in the future.

  In addition, Professor Chen Ming-syan analyzes the developing trend of the data mining field as a whole, and discussed in concrete details the technologies, applications, and efficiencies of various types of data mining methods. His research article is considered to have long lasting and positive influence on the development of data mining in the days ahead, and is one of the most often quoted article in the filed of information technology in Taiwan.

   Professor Chen Ming-syan also has abundant achievements in the area of query processing. Traditionally, dispersed query processing adopts the so-called "semijoin" method in order to reduce the amount of data transmitted through the internet and the amount of data needed to be processed. Professor Chen Ming-syan proposed the innovative concept of scheduling by alternating the semijoins and joins method.

  His proposed concept is useful in increasing query processing speed to a large extent, an achievement which is very useful in this day and age when internet applications are so popular. In view of the rapid development of internet technology, Professor Chen Ming-syan also involves himself in the mining of data streams, using hardware computing to assist data mining, and developing the techniques for processing internet data.