Dr Ali Aouad's research revolves around the design and analysis of algorithms, with applications to operations management. He is broadly interested in choice modelling, revenue management and matching platforms. His work ranges from analyzing the fundamental properties of algorithms to driving their implementation in the practice.
He holds a PhD in Operations Research from Massachusetts Institute of Technology (MIT) and an MS and BS in Applied Mathematics from Ecole Polytechnique (Paris). He has research articles published in Management Science, Operations Research, Mathematics of Operations Research and Mathematical Programming. Dr Aouad was awarded the Best Student Paper Prize by the Operations Research Center at MIT in 2015, and was a finalist in the INFORMS Nicholson Prize competition in 2016.
Alongside academia, Dr Aouad has worked and consulted for various technology firms. Before joining LBS, he spent a year at Uber’s Marketplace Data Science (San Francisco), where he contributed to the design and implementation of new algorithms that improved the efficiency of the matching platform.
Dr. George Chen’s research focuses on the design of pricing strategies and mechanisms under both non-strategic uncertainty and strategic interactions, with applications in revenue management and pricing analytics, and strategic sourcing and supply chain management. For example, his past research has examined the design and optimisation of effective large-scale dynamic pricing controls in various service industries.
George’s work has been published in Management Science, Manufacturing & Service Operations Management, and Mathematics of Operations Research. He has presented his work at major conferences and leading academic institutions worldwide.
Before joining in London Business School, George taught courses at the undergraduate and graduate levels at the University of Michigan and the University of Texas at Dallas, and was involved in consulting projects with firms in hospitality, automobile, and energy industries.
He holds a PhD in Business Administration from the University of Michigan, and a B.Eng in Automation from Tsinghua University, China.
Professor Derek W Bunn is the author of over 200 research papers and 10 books in the areas of forecasting, decision analysis and energy economics. As Professor of Decision Sciences at London Business School, he has been the recipient of several professional and industry awards, including the Goodeve Medal, from the UK Operational Research Society. His work has been extensively cited, and translated into more than six languages.
Professor Bunn read Natural Sciences at Trinity College, Cambridge University; received a PhD from London Business School; and was subsequently elected CEGB Fellow in Engineering at Oxford University. He has also been a visiting professor at Stanford University in California.
He was an elected council member of The Institute of Management Sciences (1992-1994), representing international interests in the merger executive with ORSA to create INFORMS.
More recently he has served as council member of the British Institute of Energy Economists. He has been chief editor of the Journal of Forecasting since 1984, and was formerly chief editor of Energy Economics. He is also the founding editor of the Journal of Energy Markets and has served on the editorial boards of 11 other journals, including Management Science.
He is currently chairman of the UK Government Panel of Technical Experts for the Electricity Market and he also serves as an independent member of the industry panel that oversees the wholesale electricity trading. He has acted as a special advisor to the House of Commons Select Committee on Energy and Climate Change, consultant to the UK Competition Commission on Electricity Market Abuse, Expert Advisor to the National Audit Office (in their review of the electricity industry reforms), peer reviewer on modelling work for DECC and Ofgem, and Expert Witness in several litigation cases before the High Court and at international Tribunals. He has been a regular keynote speaker and chair at many international research and practitioner conferences.
Professor Victor DeMiguel’s main research interest is portfolio optimization and asset pricing in the presence of parameter uncertainty and trading costs. More generally, he is interested in applications of optimization in finance and management.
He teaches MBA courses on Business Analytics and Financial Analytics as well as the Advanced Development Programme of Executive Education. He is the recipient of the Junior Faculty Teaching Award for 2003/2004 and the Outstanding Core Course Teaching Award for 2008/2009 at London Business School.
Professor DeMiguel’s papers have been published in most of the top journals of his field, including Management Science and Operations Research. One of his most popular papers received the Best Paper Award from the Institute for Quantitative Investment Research and was published in The Review of Financial Studies.
Professor DeMiguel is a regular speaker at academic and practitioner conferences on quantitative investment management and he has consulted for several financial institutions. He is a member of the editorial boards of Operations Research and Management Science.
Professor Gallien’s research focuses on pushing the frontier of supply chain management and global health delivery through collaborations with leading firms and organisations. He has published, consulted and taught extensively in the areas of operations and supply chain management and serves on the editorial boards of the journals Management Science, Operations Research and Manufacturing & Service Operations Management.
He is a native of France but has lived in the United States and the United Kingdom since 1996. Professor Gallien holds a PhD in Operations Research from the Massachusetts Institute of Technology and an Engineering Degree from the École des Mines de Paris.
Please note that all applications to the PhD Programme in Management Science and Operations should be addressed directly to the LBS PhD Programme instead of individual faculty members, and that Pr. Gallien's research group will only consider visiting researcher positions for periods longer than 6 months
Nitish holds a PhD in Management Science from INSEAD. His research interests focus on global supply chains, and on the use of big data and empirical methods to improve supply chain management. His work has appeared in Management Science, and Operations Research and won prestigious student paper competitions. Before joining the PhD programme at INSEAD, Nitish worked at a real estate firm and in the technology industries. Nitish has an MBA degree from the Indian School of Business and Bachelors and Masters Degrees in Mathematics and Computing from Indian Institute of Technology, Delhi, India.
Kamalini’s main research interest is in identifying radical service delivery innovations that expand access to essential life-improving services and finding ways to increase their adoption, especially in underprivileged populations. Her current research examines new ways to create value through business model innovation in healthcare and information and communication technologies.
She has served as co-principal investigator on a $1.2M grant to model and implement profitable cardiac preventive care via delivery innovation through shared medical appointments. She has also examined delivery innovation in an array of service industries supported by a grant from the UK Economic and Social Research Council.
Kamalini’s work has been published in Management Science, Manufacturing & Service Operations Management, New England Journal of Medicine, Nature Medicine, Lancet Digital Health, Harvard Business Review and other journals. She is a Departmental Editor at Manufacturing & Service Operations Management, currently in the Operational Innovation Department and previously in the Manufacturing Department. She has served as a Departmental Editor in the Entrepreneurship & Innovation Department at Management Science.
Kamalini’s expertise has seen her consult on innovation and operations management in a variety of industries, including healthcare, telecoms, consumer packaged goods and assembled products.
Her teaching areas include Business Model Innovation, Entrepreneurship, Healthcare, Operations Management, Data Science and Econometrics. She has taught at the University of Virginia, the University of Texas at Austin, The Wharton School, and the Indian School of Business, Hyderabad.
Kamalini served as President of the Manufacturing & Service Operations Management Society in 2019-20 and received the society’s Distinguished Service Award in 2022.
Kamalini Serves as a Fellow at LocalGlobe VC. She has presented her research at venues including TEDx London Business School and the World Economic Forum, Davos.
Professor Savva’s current research focuses on hospital operations and healthcare management. His research has appeared in leading journals such as Management Science, M&SOM, Production & Operations Management, and Nature Biotechnology. He is an Associate Editor of Management Science, M&SOM and senior editor of Production & Operations Management. He holds an honorary appointment at Guy’s and St Thomas’ NHS Foundation trust, a large hospital system based in London, and has acted as a consultant to hospitals, biotech companies, high-tech start-ups, retail firms and a hedge fund. He has also taught at The Wharton School, Columbia GSB, and at Judge Business School, University of Cambridge.
He holds a PhD in Management Science, an MPhil in Finance (Financial Engineering) and a BA in Physics, all from the University of Cambridge.
Alex’s main area of expertise is supply chain and trade finance, FinTech, and the interactions of operations, finance and technology. His recent work focuses on innovations in platform governance and operations. His research has appeared in top management and finance academic journals, including Management Science, Manufacturing & Service Operations Management, and the Journal of Financial Economics. He also holds editorial positions at several prestigious international academic journals.
Beyond academic research, Alex regularly shares his views in popular media. His perspectives have been featured in major news outlets, including Bloomberg, The Economist, Financial Times, Forbes, and The Washington Post. He has also been interviewed and quoted by the BBC, CNBC, and The New York Times, among others.
Alex teaches a wide range of classes in MBA, EMBA and executive programs, both in English and Chinese. His teaching expertise covers business analytics, digital technology, supply chain/value chain management, business resilience, supply chain finance and FinTech. He is the recipient of multiple teaching awards, including the 2021 EMBA Best Teacher Award at London Business School.
Alex has consulted for and collaborated with companies including United Airlines, Citadel Investment Group, Didi Chuxing, and Alibaba Group. He has also served as an international consultant at Asian Development Bank, specializing in trade finance and FinTech. He is currently working with companies in the areas of supply chain finance, FinTech, platform governance, and business analytics.
This course provides an introduction to an industrial sector of worldwide importance, and one in which there are now many business challenges through market restructuring and the development of low carbon technologies.
In today's information age, managers increasingly rely on quantitative models to make financial decisions that have a profound impact on the performance of their organizations. Often business analysts produce the quantitative models that top management use to support their decision making, but top management must also understand the strengths and weaknesses of the models if they are to use them effectively to support their decisions. The objective of this course is to equip you with the frameworks, tools, and methodologies necessary to build and/or be an educated user of quantitative models for financial decision making. The course is suitable for students seeking a career in finance, but also for students with broader interests who wish to strengthen their general modelling skills, and it does not require any quantitative background other than what is covered in the MBA core courses.
With increased demand and pressure to reduce costs, healthcare delivery systems across the globe are under pressure to find ways to increase quality and widen access, while simultaneously reducing cost. The aim of the course is to explore the challenges these competing goals create and to throw light on how they can be best managed. In so doing the course seeks to identify opportunities in health care for managers, entrepreneurs and policy makers. This course draws substantially from the research and consulting expertise of the team of instructors teaching it.
This elective focusses on the business of sport and entertainment. The aim is to develop understanding and skills in the strategic, operational and marketing management of these two related and converging sectors. It is designed to foster strategic and operational thinking in a rapidly professionalizing area and one that is key to future economic growth.
This course covers the emerging field of business analytics (BA) or data mining and expands and develops the students' analytical tool kit in analyzing massive data sets. Using case studies and hands-on data sets, students will learn advanced data query techniques, data cleaning and organization, explore various machine learning techniques including supervised and unsupervised classification schemes, text classification, clustering techniques as well as predictive analytics. Students will gain hands-on experience with a variety of software tools, including Tableau and XLMiner.
To meet the challenges of the globalised and rapidly changing business environment, companies are increasingly adopting flat, flexible and matrix-oriented organisation structures in which work is structured around cross-functional business processes and projects. The success of such companies crucially depends on effective project management. The key dimensions of projects are people, time, costs, and resources. This course introduces methodologies and practical tools that facilitate and support the management of these dimensions, throughout the project design, planning and implementation phases.
The modern economy is characterized by reduced legal and technological obstacles to global trading. As a result, the success of modern enterprises is increasingly driven not only by their products, people and internal processes, but also by the performance of their supply chain as a whole. In this context, the goal of this course is twofold:
Innovating Business Models, Products & Services is a fast-paced,hands-on, experiential and interdisciplinary class where students will identify and develop new business models, products and services, in a multi-tiered innovation tournament context.
This is a practical course developed to extend statistical capabilities and critical understanding in the analysis of time series data. The main emphasis will be upon analysing financial and commodity data, mostly high frequency. Although various advanced regression-based methods are reviewed, the course will not be mathematically demanding and students who were comfortable with the pre-programme, or first term, statistics course will be able to move on to this material without difficulty. Students should, however, have an interest in model-based analysis. The course material will be developed intuitively, rather than theoretically, through the exploration of many examples and practical workshops. The course will start with the fundamental basics of time series analysis and lead to a look at recent techniques for algorithmic forecasting and value-at-risk. Two of the later sessions will be led by Dr Peter Bolland, who was formerly head of electronic market making at Morgan Stanley.
The primary objective of this course is to enhance the participants’ ability to use analytics to develop insights in a wide range of business situations. We will work on five in-depth real-world case studies developed by the instructor. For each case, we will start with breaking down what seems to be a complex and ill-structured problem to simpler subproblems that are amenable to analysis. Through a mixture of lectures and workshops, we will use data analysis (visualization, regression) and modelling techniques (Monte-Carlo simulation, decision-tree analysis, optimization) to build progressively more sophisticated models that allow us to evaluate possible alternatives, make sensible recommendations, and serve as the basis for communicating findings and influencing decisions. After each session, participants will have the opportunity to further refine the models developed in class and prepare a presentation for the management of the company featured in the case study.
"Attending the Accelerated Development Programme is a unique opportunity for participants to learn not only from our world-class faculty but from their fellow participants. Consequently, the way the programme is designed encourages you to get to know as many people as possible and to form a life-long network of culturally diverse peers".
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