Kai Gong received his Bachelor's degree from Tsinghua University and a Ph.D. in Chemical Engineering from Rice University. While at Rice, he was interested in developing a molecular theory to describe the structure of complex molecules at nanoscale, and later published several papers in a top-tier journal of physical chemistry. He also developed solid mathematical programming skills with Fortran and Matlab. He then received the Chinese Government Award for outstanding self-financed students abroad. He interned in Schlumberger and later worked in Sinopec in oil recovery, where he became interested in large commodity trading. He has passed CFA level I exam. Kai joined the Berkeley MFE program to obtain a systematical training in quantitative finance. In his free time, he likes climbing mountains, swimming and playing poker.
Zongyi Gong earned a Ph.D. in Physics from the University of Virginia (UVa) in 2013. He worked as a research scientist and visiting assistant professor at UVa prior to joining the Berkeley MFE program. His work focused on developing statistical-based image processing and reconstruction algorithms for cancer imaging systems (e.g. CT, Single-photon emission computed tomography). He published two first-author papers on Medical Physics, licensed one patent to Dilon Diagnostics and served as co-principal investigator for several research projects funded by National Institute of Health and Wallace H. Coulter Foundation. In December 2014, he was awarded the Trainee Research Price from the Radiology Society of North America. Zongyi has a long-term interest in economics and finance. He passed CFA level I. Through his studies at the Berkeley MFE Program, Zongyi expects to develop in-depth understanding of the market as well as apply his research intuition and quantitative skills in the field of trading and investment. In his spare time, he enjoys listening to musicals, playing tennis and snowboarding.
Gautam Gowda earned a Bachelor's degree in Computer Science from the Birla Institute of Technology and Science (BITS, Pilani)-Goa. He previously worked as a Quant with the Global Equity Derivatives team at Deutsche Bank Group, where he focused on pricing and booking support for various structured products including Autocallables and Reverse Convertibles. Prior to joining Deutsche Bank, Gautam worked for Credit Suisse in Global Arbitrage Trading. As a Desk Quant, he provided support for the desk's daily tasks and worked on its Proprietary Trading Application and Risk Management System. He was also involved in development, back testing and deployment of algorithmic trading strategies. Later he worked with the Head of the Arbitrage Desk in US market analysis and generated ideas for event based trading. Gautam has also cleared CFA level II and intends to complete the full CFA program soon. Gautam joined the Berkeley MFE program to enhance his understanding of complex models and its practical use. He looks forward to an exciting and challenging career in a front office role where he can use his skills for a buy side firm. Gautam has played football at a semi-professional level, and in his spare time enjoys teaching mathematics to kids, playing poker, reading and travelling.
Jonathan Humphrys graduated from the University of Cape Town with a Bachelor of Business Science degree in Actuarial Science, with a specialization in Quantitative Finance. The rigorous program trained him in statistics, finance, mathematics and stochastic calculus. In his final year, Jonathan completed a thesis on the pricing of convertible bonds using a range of methods under the supervision of a fixed income analyst at Kagiso asset management. After graduating, he interned at Kagiso, where he worked in the Fixed Income and Real Estate department. He used the Black- Litterman model to look at strategic asset allocation between the firm's asset classes and conducted research for a mid-cap equity proposal which was presented to a team of analysts. Jonathan joined the Berkeley MFE program to further develop his quantitative finance skills. In his spare time, he enjoys Ju-Jitsu, running and reading.
Kritsana Janchidfar graduated with a Bachelor's degree in Computer Engineering with First-Class Honors from Chulalongkorn University in 2015. He interned as an IT security at the Stock Exchange of Thailand under the IT department, where he excelled in his programming skills and grew interests in the finance field. As part of his Machine Learning class project, he constructed a machine-learning classifier using neural network to determine if the stock is speculative. In his final project, he formed a team to build a program visualizing stock performance and developed the stock price forecasting model using the modified Elliott wave principle. After graduation, he joined the Independent Financial Consulting Group in Thailand as a financial advisor, where he had a chance to give advices and provide assistance to clients regarding investment/retirement portfolio management. He passed the CFA level I in December 2015. Through the Berkeley MFE program, Kritsana believes he will further enhance his quantitative skills and be instilled with an insightful practical experience in the financial industry. In his spare time, he enjoys cooking, reading, hiking, skiing, traveling, and swimming.
Aman Kesarwani received his Bachelor's degree in Mathematics and Computing from the Indian Institute of Technology, Guwahati. Upon graduation, he joined a private equity firm as an intern, where he worked on live deals in transport and energy sectors and developed a tool to manage their deal database. He later joined the market risk management group at Credit Suisse, where he worked in the fixed income division of the emerging markets, with a primary focus on the structured products portfolio and financing. During this time, he also provided programming support for the development of the scenario tools. He also worked as a paid contract writer for the third edition of book Principles of Financial Engineering by Salih Neftci, where he assumed the responsibility of creating VBA and MATLAB exercises based on hedging and pricing financial products. Aman has passed the CFA Level I and plans to complete the full CFA charter. He volunteered in NGO providing support for the children at shelter homes. In his spare time, Aman enjoys running, travelling, and exploring new cuisines.
Walter Kissling graduated Magna Cum Laude from Tulane University with a degree in Finance. During his undergraduate studies, he completed several internships in investment banks and private equity funds in Colombia, Costa Rica, and New York. He then went on to complete a Master's of Management in Energy at Tulane University, where he developed machine learning models to trade natural gas futures. During his time at Tulane he was also part of a student-managed fund that had control over a portion of the university's endowment. During his final year at Tulane, he co-founded a quantitative family office, where he is currently Chief Investment Officer, focusing on trading equities, ETFs and commodities. He is in charge of strategy research, development, and trading. His work is focused on using machine learning models to trade stocks and commodities, and running tactical risk parity asset allocation models. Walter joined the Berkeley MFE program to improve his quantitative and computational abilities. In his spare time, he enjoys working out, skiing and watching football.
Chelsea Knipper graduated with a B.S. in Physics and minor in Mathematics from Pennsylvania State University in 2012. As a part of the undergraduate program, she completed an internship at Los Alamos National Laboratory, where she worked to optimize radioactivity scanning devices in the Nuclear Non-Proliferation division. In 2012, she pursued a Master's degree program at the University of Texas at Austin in the area of High Energy Particle Physics. At UT Austin, she researched neutrino physics by characterizing photo detection devices for the upcoming underwater Cherenkov detector project, CHIPS. In preparation for the Berkeley MFE program, she has taken coursework in derivatives, statistics, programming and advanced mathematics. At the Berkeley MFE, she looks forward to strengthening her knowledge of mathematical methods in finance, as well as applying problem solving strategies and programming methods in the financial industry. In her free time, Chelsea plays tennis.
Jules Le Pen attended Ecole Centrale Paris, where he studied Applied Mathematics, Engineering and Physics. He will officially receive his Master's degree upon completion of the Berkeley MFE program. Prior to joining MFE, Jules worked for six months at Rivage Investment, a French hedge fund located in Paris, before leaving to study for one year in Brisbane, Australia. Loving challenges, he decided to join the Berkeley MFE program to enhance his financial and quantitative skills. Jules looks forward to deepening his understanding of financial markets and applying quantitative methods to solve real industry's problems. He is also fond of sports and regularly enjoys playing soccer, running and swimming. In his spare time, he enjoys travelling.
Hao Li graduated from Tsinghua University in 2015 with a Bachelor of Science degree in Automation and a Bachelor of Arts degree in Economics. During his undergraduate studies, he built a solid foundation in both mathematics and computer programming. After graduation, Hao interned in I-kuan River Fund as a quantitative strategy researcher, where he gained experience about program trading. Hao later worked in the derivative department at Grand Resources Group Co., LTD, where he tried market trading models for over-the-counter options, combing theoretical knowledge with the real market. Hao passed the CFA level 1 in 2015. Through the Berkeley MFE program, Hao hopes to strengthen his quantitative skills and deepen his understanding of the developed financial market. In his spare time, Hao enjoys playing chess. His title is chess master and Chinese National Second Grade Sportsman. His hobbies also include table tennis and badminton.
Jianxiong Li graduated with a B.S. in Mathematics from Shanghai University in 2014 and went on to study analytical finance at Lehigh University. While in college, in addition to developing sound analytical and quantitative skills, he took an increasing interest in mathematical finance through the study of optimization and empirical statistics. During his Master's study at Lehigh, he dug deeper and devoted much of his effort into fundamental quantitative finance, including fabricating MBS pass-through models and cascade structure with tranches, implementing numerical methods and simulation models for option pricing and applying modern mean-variance and Black- Litterman models on portfolio optimization. While interning at CapTrust Financial Advisors, he developed VBA codes to monitor the portfolio risk factors and assisted with rebalancing and performance calculation. He is a CFA Level III candidate and has passed all 2 levels of FRM exams. He enjoys investigating real-life predictive modelling problems on the internet and playing soccer.
Linshan (Nathan) Li received his Bachelor of Mathematics degree from the University of Waterloo in 2015, and earned the Dean's Honors Distinction with a major in Mathematical Finance and minors in Pure Mathematics and Statistics. While pursuing his degree, Nathan participated in a co-operative program where he completed five internships. As an intern at Scotiabank's credit risk analytics team, he analyzed a new Retail Credit Economic Capital model and a new Expected Default Frequency methodology. In addition, he completed a project reconciling two important risk measurements and presented the result to the department. Nathan has also interned in the Canadian Industry Bank of Commerce's (CIBC) Risk Management department, where he engaged in the development of the Advanced Measurement Approach Model for the evaluation of Operational Risk under the Basel II regulations. During this time, he worked with models in Matlab and performed data analytics. Nathan also worked as a Co-op Tax Analyst at LS Travel Retail and was an Actuarial Intern at SCOR Global Life. He later worked as an Undergraduate Research Assistant at the University of Waterloo, where he researched drawdown risk in portfolio optimization and implemented numerical methods for solving Partial Differential Equations. Nathan has always been strongly passionate about mathematics, and discovered the fascinating world of financial markets during his studies at university. Nathan is also a CFA level II Candidate. Nathan joined the Berkeley MFE program to apply his mathematical skills to the field of quantitative finance. Nathan served as a VP in the University of Waterloo Math Finance Student Association. In his spare time, he enjoys playing soccer.
Yihui (Victoria) Li received Bachelor's degrees in both Applied Math and Statistics from the University of California Berkeley in 2015. She developed solid mathematical foundation and statistical analysis skills during her undergraduate studies. Prior to joining the Berkeley MFE program, Victoria developed her quantitative skills through internships at various IT companies. She refined her data analyzing skills through working at one of the largest Facebook media buyer companies Brand Networks. She also worked in startups in San Francisco, where she served as data science team leader and helped design various essential algorithms. She has passed the first two actuarial exams (P, FM). By joining the Berkeley MFE program, she hopes to broaden her financial knowledge and apply the quantitative methods she learned into financial practice. Victoria enjoys travelling, cooking and reading novels in her spare time.
Guanghua Lian received a Ph.D. in Applied Mathematics at the University of Wollongong Australia, after obtaining a Bachelor of Science in Mathematics with a minor in Computer Software. Guanghua conducted doctoral research in exotic derivative pricing, implied volatility construction, and statistic modeling of realized volatility. He specializes in analytically or numerically solving partial differential equations and stochastic differential equations, and his research has been published in top mathematical journals and finance journals. Guanghua has more than ten years of programming experience using Matlab, and C++. He has previously worked as a C++ programmer, an assistant professor of quantitative finance, and a quantitative developer at TRV trading Company. He interned at Algorithmic Trading Group in Hong Kong, where he developed trading strategies with C# programming. Guanghua has passed CFA level II, and is a student of the online program of Master of Computer Science (with specialization in machine learning) at Georgia Institute of Technology. Guanghua joined the Berkeley MFE program to further advance his career in quantitative finance. During his free time, Guanghua enjoys playing football, table tennis, hiking and piano.
Kai Liu received his Master of Science degree from the University of Texas at Austin, where he studied computational electromagnetics. Prior to that, he earned his Bachelor of Engineering from Beihang University, China, majoring in electronic information engineering. Before joining the Berkeley MFE program, he worked as an algorithm research engineer at China Telecom for more than 5 years. Kai has high-performance coding experience in MoM and FDTD. He also has theoretical knowledge in FEM. During his graduate studies, he modified an EFIE surface-integral electromagnetic MoM solver into an iterating, CFIE, volume-integral MoM solver to explore the inverse scattering problem in electromagnetic wave propagation. Kai's work experience at China Telecom involves the development of online-training-enabled mobile augmented reality and wireless signal-based indoor positioning algorithm. Kai hopes to gain from the Berkeley MFE a solid understanding of the quantitative foundations of financial phenomena, plus how numerical methods can help in this context. Kai enjoys reading, swimming, playing tennis and cooking in his spare time. He is also a flight simulator enthusiast.