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Welcome to SEIEE

The school of Electronic, Information and Electrical Engineering (SEIEE) at Shanghai Jiao Tong University (SJTU) was established in December 2001. It can be traced back to Department of Electrical Engineering a century ago and was crowned as the “cradle” of Electrical Engineer in China. The School is composed of Departments of Electrical Engineering, Automation, Computer Science and Engineering, Electronic Engineering, Instrument Science and Engineering, and Electrical and Electronic Experimental Teaching Center.
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Faculty

Xiao Dengming

Professor
1.Gas Discharge and Gas Insulation
I have studied the influence of transmission property of additional gas on discharge character of SF6 gas mixtures. The avalanche growth processes in SF6/ N2, SF6/CO2, SF6/He, SF6/Ne, SF6/Ar, SF6/Kr, and SF6/Xe gas mixtures have been studied by the Pulse Townsend (PT) method. The discharge mechanism of the avalanche in these gases have been analyzed. The variation patterns of their effective ionization coefficient, electron drift velocity and diffusion coefficient have been given. The collisional processes and transport properties of these gases have been compared, and their dielectric strengths have been determined also.
It is urgent to find new substitute dielectric gases to pure SF6 for possible immediate or future use in existing or modified electrical equipment due to its high Global Warming Potential (GWP). The insulation characteristics of c-C4F8 gas mixtures was investigated By me and my team. The insulation gas breakdown process in uniform filed have be obtained by Monte Carlo simulation, Boltzmann equation analysis method and Steady State Townsend (SST) experiment method. GWP and liquefaction temperature (Tb ) of pure c-C4F8 and its mixtures were analyzed quantitatively synchronously for the first time.
2.On-line Monitoring and Fault Diagnosis in Power Equipment
I am concerned with the chromatography on-line monitoring and fault diagnosis system, which detects the key gases of H2, CO, CH4, C2H6, C2H4, and C2H2 dissolved in oil timely and accurately, then make diagnoses on the power equipment.
The traditional insulation fault in transformer is only diagnosed by transacting the data of DGA test through 2D/3D visualization procession. I integrated fuzzy diagnosis technology with 2D/3D visualization procession to diagnose synthetically.
I have developed a set of overall on-line monitoring systems constructed to control and monitor the condition of SF6 circuit breaker with advanced sensors and microcomputer based data acquisition and procession system, which provides overall information about the conditions of each part of SF6 circuit breaker to diagnosis the incoming faults and potential defects on circuit breaker in time. A genetic programming based polynomial networks model (GPPNM) is presented by me, which promote the diagnostic performance of incipient insulation fault of power transformers and breaker. The proposed model has been applied on the actual fault records and compared with conventional method, artificial neural networks method and self-organizing polynomial networks (SOPN) method. The numeric test testifies that the GPPNM requires less prior knowledge in the process of construction of diagnosis model and has better performance than other methods.
3. Effect of Electromagnetic Field on Biology
I have investigated the effects of 20mT, 50Hz sinusoidal electromagnetic field(EMF) on cell proliferation, metabolism，cell cycle phase distribution, apoptosis and other characteristics in two human cancer cell lines (HL-60 and SK-Hep-1) and Human Mesenchymal Stem Cells (hMSCs). A theoretical analysis of the mechanism for the action of low frequency oscillating magnetic field on cell ions was discussion. I suggested that the amplitude of the forced-vibration does not change with the magnetic field frequency, which is found in electric field
I have concerned on the dielectric behavior and inactivation of avian corona virus in the electric field, which can inactivate the virus by making it attain maximum dielectric relaxation absorption. The method can be used in the adjuvant therapy of disease that is induced by the corona virus. I mentioned for the first time that the virus can be regarded as a dipole, and the rotate or sway model of the virus in the electric field, and gived a new physical model of inactivation of virus in athermotic biologic effect. This model will also serve as a valuable reference in the inactivation of other virus such as SARS (Severe Acute Respiratory Syndrome) or HIV (human immunodeficiency virus).

Luo Yuan

Professor
His research interests include Information Theory (especially Shannon Channel Capacity and Network Coding), Coding Theory (especially Hamming Distance, Constant Composition and Constant Weight Code, Periodic Sequence) and Computer Security (especially Virtual Machine Security).
In 2006, his cooperative IT paper "On constant composition codes over Zq" was cited and listed by a cutting-edge review on powerline communication in the Triennial Issue ‘Mathematics and physics' (Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences), see ``Powerline communication and the 36 officers problem", vol.364, pp. 3199-3214, 2006. In 2008, his cooperative paper "The relative generalized Hamming weight of linear q-ary codes and their subcodes" (published in Designs, Codes and Cryptography, vol.48, no.2, pp.111-123) was listed firstly in a memorial issue for IEEE Fellow T. Kl?ve.

Yuan Bo

Professor
Understanding the biological circuits that perform computations within the cell is a central problem in computational and systems biology. From the point of view of informatics and systemics, biology offer the challenge of understanding the complex behaviors of interacting molecules evolved to operate with both remarkable precision and robustness in the context of genes, environments and their complex interactions. The theme of our research is stochasticity, central to properly capture both the stability and the multiple sources of uncertainties needed for modeling biosystems in a realistic way. We are developing analytical and computational frameworks to model such complex and stochastic behaviors using a combined discrete (Markov Chain) and continuous (Stochastic Differentials) approach, starting from bi-stable switches, limited cycles to feed-forward loops as well as their coupling. Our goal is to adequately describe observed stochasticity, variations and heterogeneity in biological systems for multiple scales of biological organizations.

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