Zitong Wang is a first-year Ph.D. student in Industrial Engineering and Operations Research (IEOR) department in Columbia. He received his Bachelor's and Master's degree in Mathematics at the Chinese University of Hong Kong (CUHK) in 2020.
Zhenyuan Liu is now the second year PhD student in IEOR department. He graduated from Department of Financial Mathematics, School of Mathematical Sciences, Peking University in 2019. His current research interests include rare event estimation and data-driven robust and stochastic optimization.
Yunjie is currently working as a senior data science analyst at Tripadvisor. He holds a Ph.D. in operations research from Columbia University and a BS in industrial engineering from Georgia Institute of Technology. His research interests are in pricing and revenue management, data-driven operations management, and their application.
Yunfan is a Ph.D. student in the IEOR department. His research interest lies in optimization. Prior to joining Columbia, he completed his Bachelor’s and Master’s in Applied Mathematics and Statistics at Johns Hopkins University, where he worked on graph theory and discrete optimization.
Yuanlu Bai joined the IEOR department in September, 2018. She graduated from Peking University (Beijing, China) with a B.S. in Statistics and a B.Ec. in Economics in July, 2018. She is conducting research on rare-event analysis and stochastic simulation under supervision of Professor Henry Lam.
Yuan is a fourth year PhD student in IEOR. Before coming to Columbia University, He studied at National University of Singapore, where he obtained a B.Sc. with Honors in Applied Mathematics with a Second Major in Statistics. His research focuses on developing optimization formulations and efficient algorithms for large-scale problems in game theory and machine learning. In his spare time, he studies traditional Chinese music, (Western) classical music and the philosophy of Buddhism.
Yilie Huang is a second-year Ph.D. student at Industrial Engineering and Operations Research Department, Columbia University, where he is working with Prof. Xunyu Zhou. He also received his Master of Science degree at Columbia IEOR in 2018. Before that, he earned a Bachelor of Science degree in Mathematics and Applied Mathematics at Zhejiang University. His research focuses on stochastic control, machine learning and reinforcement learning. Additionally, he is also interested in applying the theories into financial markets. Currently, he is working on stochastic control problems from reinforcement learning aspect.
Yibo is a first-year Ph.D. student in the IEOR department. Prior to joining Columbia, he received his Bachelor's degree in Mathematics from Fudan University.
Yi Ren started his PhD program at Columbia in the Fall of 2017. Before coming to Columbia University, he attended Fudan University in China where he received a B.Sc. in Mathematics. He is now working on problems in optimization and machine learning with Prof. Donald Goldfarb.
Yeqing Zhou is a fourth-year PhD student in the Industrial Engineering and Operations Research department at Columbia University. She is interested in the theory and practice of operations management, supply chain management and business analytics. Her advisor is Professor Adam Elmachtoub. She received her B.S. degree in Mathematics from Fudan University in 2014, and her M.S. degree in Operations Research from Columbia University in 2016.
Yan Chen is a second-year Ph.D. student at Industrial Engineering and Operations Research Department, Columbia University, where he is working with Prof. Ward Whitt and Prof. Jing Dong. Before that, he earned a bachelor degree in Mathematics from Tongji University and a master degree in Operations Research from Columbia University. His primary research focuses on the intersection of queueing theory, optimization and applied probability, explores the extreme performance of complex queueing systems. Additionally, He is interested in designing and analyzing stochastic models for service operations. He is currently working on exploring extremal single server queues and multi-server queues given moment conditions.
Xuan joined the IEOR department in 2016. She completed her bachelor's degree in Mathematics from Cornell University in 2014. She is currently working with the guidance of Prof. Yuri Faenza on discrete optimization.
Xu is an Assistant Professor in Data Analytics and Applied Operations Research in the Department of Industrial and Systems Engineering at the University of Florida. He works in areas such as performance analysis and optimization of stochastic service systems, the theory of stochastic-process limits, systemic risking modeling, and network design and control of sustainable urban transport systems. A common theme of his research is to develop tractable process-level approximations for the dynamics of the underlying physical system and then use such formal approximations to gain insights into the system performance and/or obtain provably asymptotically optimal control policies for the original system.
He was a finalist of the Best Student Paper Competition in Informs Finance Section in 2017, a recent recipient of the 2018 Institute for Mathematics and its Applications Travel Award and the 2017 Engineering Graduate Student Council Professional Development Scholarship.
Xinyu Zhang is a Ph.D. student in the Department of Industrial Engineering and Operations Research at Columbia University, advised by Henry Lam. His research interests lie in stochastic optimization and extreme event analysis. He obtained his bachelor's degree in the University of Michigan in 2016, majoring in physics and applied mathematics.
Xiaopeng Li is a first-year Ph.D. student in Industrial Engineering and Operations Research (IEOR) department in Columbia. He received his Bachelor's degree in Applied Mathematics at the Chinese University of Hong Kong, Shenzhen (CUHKSZ) in 2020. His current interests lie in mathematical programming with uncertainties, non-convex optimization, and distributive algorithms.
Xiaopei Zhang graduated from the IEOR department in 2019. Before that, he got a M.A. degree in statistics from Columbia and a B.S. degree in Mathematics from Peking University. During his Ph.D. life, his research was about queueing theory and stochastic modeling with data.
Xiao Xu is a Ph.D. student in the Department of Industrial Engineering and Operations Research. His main research focus is graph analytics in economics and finance. Xiao studies interrelations between companies through the supply chain, partnerships, and market price correlations, utilizing graphical analytics tools and machine learning techniques.
He has been responsible for building and maintaining a backtesting platform on AWS to test the performance of portfolio selection strategies for various research projects. He is also broadly interested and actively involved in projects on the application of natural language processing and deep learning in finance. Xiao graduated magna cum laude in 2016 from Columbia University with a bachelor's degree in financial engineering.
Xiao Lei is a third-year PhD student in the IEOR department at Columbia University. He is fortunate to be advised by Prof. Adam Elmachtoub. His research interests lie in revenue management and business analytics. He received his master degree in operations research at Columbia University, and his bachelor degree in financial engineering at University of International Business and Economics, China.
Weilong joined the IEOR department in 2017. He received his bachelor's degree in Statistics from Peking University. He is currently working with Prof. Ali Hirsa on financial engineering.
Wei You is completed his PhD in Operations Research from Columbia University, advised by Professor Ward Whitt. His primary research focus is on queueing theory, applied probability, and their applications to the performance analysis and design of service systems. He was born in Nanjing, Jiangsu, China. He received the B.S. degree in Mathematics (2014) from Nanjing University, China.
He will join the Department of Industrial Engineering and Decision Analytics at Hong Kong University of Science and Technology.
Tyler is a first-year doctoral student interested in problems at the intersection of theoretical computer science and economics. He intends to work with Dr. Christian Kroer on problems in stochastic matching. Tyler’s undergraduate degrees are in computational mathematics and statistics from Michigan State University, where he was named 1 of 6 University Distinguished Scholars. As an undergrad, Tyler spent his summers engaging in research at a start-up in his hometown of Buffalo, at UCLA, and at the University of Maryland. When he’s not optimizing things, Tyler enjoys cooking, watching MSU basketball, and long walks on the beach at sunset.
Tugce is a forth-year PhD student in IEOR Department at Columbia University. She received her B.S. and M.S. degrees from Industrial Engineering Department at Bogaziçi University, Turkey. She is currently working with Prof. Ali Hirsa on machine learning and deep learning applications in finance specifically asset management.
Tingting is a first-year Ph.D. student in the IEOR department at Columbia. Prior to joining Columbia, she received her B.S. degree in applied mathematics & statistics, computer science and pure mathematics from Johns Hopkins University. Additionally, she completed the combined bachelor's master's program and received a M.S.E. degree in applied mathematics & statistics at Johns Hopkins University. She is broadly interested in algorithms, machine learning and optimization.
Sudeep Raja is a Doctoral student in the IEOR Department at Columbia University. His research interests are in theoretical machine learning and optimization, with a specific focus on online learning, multi-armed bandits and reinforcement learning. His goal is to design efficient algorithms with provable guarantees for online decision making. Sudeep holds a Master of Science in Computer Science from the University of Massachusetts Amherst, where he was awarded the Sudha Mishra and Rajesh Jha Scholarship. He also holds a Bachelor of Technology in Computer Science and Engineering from the Indian Institute of Technology Kharagpur. In addition, he has worked at industrial research labs such as Microsoft Research, Xerox Research and IBM Research in India.
Steven is a fourth year PhD student. He is interested in online learning, reinforcement learning, and mechanism design. He graduated from UCLA with a B.S. in Electrical Engineering in 2017.
Mr. Shuoguang Yang joined the Department of Industrial Engineering & Operations Research (IEOR), Columbia University in September 2015. He received B.S. degree in mathematics from National University of Singapore (NUS). He is interested in the optimization problems with real life applications, especially with the combination of online learning.
Shengyi He joined the IEOR department in 2019. Before joining Columbia, he received his B.S. degree with a major in Statistics from Peking University.
Shatian is a fourth-year doctoral student in the IEOR department. She received her BA in Mathematics and Computer Science from Carleton College in 2017.
Mali is a fourth-year Ph.D student in the IEOR Department. He completed his M.Math in Combinatorics and Optimization at University of Waterloo, Canada, where he worked on continuous optimization and data science. Before that, he got his B.Tech at Indian Institute of Technology-Madras, India.
Apart from theoretical research, he is interested in problems with real world impact. He currently works with Prof. Cliff Stein on large-scale scheduling problems and online convex optimization.
Mali is also involved in a variety of leadership roles at Columbia- he is an Ambassador to the IEOR department and until recently, was President of the Engineering Graduate Student Council, representing 4000 students in Columbia Engineering.
Ruizhe Jia is a Ph.D. student in the Industrial Engineering and Operations Research department at Columbia University. He received his B.S. and M.A. in Mathematics from the University of California, Los Angeles (UCLA) in 2018. His interests include market microstructure and systemic risk. He is currently working with Professor Capponi on developing game theoretical models for the analysis of financial stability.
Raghav Singal is a PhD candidate in Operations Research at Columbia University. His research focuses on data-driven analytics, where he uses tools from a mix of fields including machine learning, optimization, and stochastic modeling to solve application-driven problems in the data rich digital and sharing economy. His academic advisors are Professors Omar Besbes, Vineet Goyal, and Garud Iyengar.
Raghav completed his Bachelor of Applied Science in Industrial Engineering at the University of Toronto, where he was advised by Professor Timothy Chan for his undergraduate thesis.
Raghav is on the academic job market for 2019-20.
Oussama started his PhD in September 2017. His research interests include Combinatorial Optimization, Matchings, Algorithm Design and Machine Learning. Before coming to Columbia, Oussama completed his Bachelor in Applied Mathematics at Ecole Polytechnique (Paris, France).
He works with Prof. Cliff Stein on combinatorial optimization problems, especially in matching and scheduling.
Omar is currently a Visiting Assistant Professor at Cornell Tech in Operations Research and Information Engineering. His research revolves around decision-making under uncertainty where he aims to design robust and efficient algorithms for a wide-range of dynamic optimization problems with applications in revenue management and matching platforms. Omar spent few internships as a research and data scientist at Amazon and Uber where he contributed to the design and implementation of data-driven optimization models for matching and retailing platforms. Omar holds a Bachelor degree in Applied Mathematics from Ecole Polytechnique (France) and a Master of Science and a PhD in Operations Research from Columbia University.
Noemie is a Phd student at IEOR department since September 2019. Her research interests include optimization and online learning. She is currently working with Vineet Goyal on dynamic pricing and multi-armed bandits problems. Prior to joining Columbia, she graduated from Ecole Polytechnique, Paris with a B.S and M.S degree in Applied Mathematics.
Ni is currently working as a research scientist in the AI group at Bloomberg L.P. She received her PhD degree from IEOR department in 2018. Her research concentration is on queueing theory and she has been working with Prof. Whitt. Previously she received a Bachelor's degree in Economics and Finance from the University of Hong Kong and she also did a Master in Statistics from the University of Hong Kong and a Master in Financial Engineering from Columbia University.
Min-hwan is a Ph.D. candidate in Operations Research with Data Science specialization at Columbia University. He is advised by Prof. Garud Iyengar and co-advised by Prof. Assaf Zeevi. His primary research interests are in sequential decision making under uncertainty, reinforcement learning, bandit algorithms, and their applications.
Michael Hamilton works on both the theory and practice of revenue management, with a particular emphasis on pricing. His research demonstrates the effectiveness of novel pricing strategies in emerging e-commerce markets. He will be joining the University of Pittsburgh, Katz School of Business as an Assistant Professor in the Business Analytics and Operations area.
Matías is a first year PhD student in the IEOR Department. His research interests are algebraic methods to study discrete structures, such as polyhedra that arise from discrete optimization problems. He is broadly interested in the works of Prof. Faenza on polyhedral combinatorics, and in the works of Prof. Bienstock and Prof. Josz on polynomial optimization.
Prior to joining Columbia, he earned his master's degree in mathematics from Pontificia Universidad Católica de Chile (PUC) in 2020. Additionally, in 2016 he completed a MS and BS in economics from PUC. From 2016 until 2020 he was an instructor of economics at PUC and Universidad Adolfo Ibáñez in Santiago de Chile.
Mathieu Kubik received his Bachelor and engineer's degree in applied maths from Ecole Polytechnique in Paris in 2020, and joined IEOR in september 2020.
Madhu is a first year Ph.D student in the IEOR Department. Previously, she received her bachelors degree from Princeton in 2020, majoring in Operations Research and Financial Engineering and obtaining a certificate in Statistics and Machine Learning. She is interested in algorithms for Sequential Decision Making under Uncertainty.
Luc is a 2nd year PhD student at the IEOR Department. He graduated in 2018 from Ecole Polytechnique (Paris, France) with a major in Applied Mathematics. Luc's interests include applied probability, stochastic control and interacting particle systems. He is currently working with Prof. Daniel Lacker on the theory mean field games and graph-based interaction systems.
Lingyi Zhang is currently a third year PhD student in Operations Research at Columbia. Prior to joining Columbia, she received her B.A. degree in mathematics, economics, and applied mathematics and statistics from Johns Hopkins University. She is currently working with Professor Yuri Faenza on combinatorial optimization.
Lin Chen, who has a BS in mathematics from Nanjing University and a Ph.D. in Industrial Engineering from Columbia University, is interested in financial engineering, in particular the modeling of financial markets. He is investigating Nobel Laureate Markowitz’s model of portfolio theory and working on its continuous-time and distributionally robust counterparts. His long-term agenda is to combine distributionally robust optimization formulation with behavioral finance models to better explain agents’ behavior in financial markets and to yield more robust portfolios and strategies for better performance. He is working under the guidance of Xunyu Zhou, Liu Family Professor of Financial Engineering, who established the FDT Center for Intelligent Asset Management at Columbia Engineering.
Lexiao Lai joined the IEOR Department at Columbia in September 2019. He graduated from The University of Hong Kong with a B.Sc. in Mathematics in 2019. His current research interests lie in nonconvex optimization, data science and low-rank matrix recovery.
Lane Chun Yeung is a second-year IEOR PhD student at Columbia University. His research interests lie in applied probability and stochastic processes. He is currently working with Prof. Ioannis Karatzas and Prof. Daniel Lacker on interacting particle systems, optimal transport and large deviations. He received a B.S. degree in Mathematics from the Chinese University of Hong Kong and a M.S. degree in Operations Research from Columbia University.
Goutam started working at Amazon as a Research Scientist from Aug 2020. He graduated from the department in July 2020. His primary research interests include revenue management, choice modeling and assortment optimization. He is also interested in finance, statistics and machine learning. Before his PhD, he graduated from IIT Bombay, India with a major in Electrical Engineering and a minor in Math in 2014. He has also worked as a Research Scientist at SAS Institute, Pune for a year.
Julien Grand-Clement is a fifth-year PhD candidate who graduated from Ecole Polytechnique (Paris, France) in Optimization and Algorithms in 2016. He works with Pr. Vineet Goyal and Pr. Carri W. Chan from Columbia Business school on robust control of Markov chains and related applications in healthcare and hospital maintenance
Jinsheng joined the IEOR Department as a PhD student in September 2017. Before coming to Columbia University, he attended the University of Cambridge and graduated with a B.A. in Mathematics in 2016. His current research interests lie in applied probability and stochastic processes.
Jingtong Zhao is a Ph.D. student at Columbia IEOR Department. She received her B.S. in Operations Research: Financial Engineering from Columbia University in 2016. She is advised by Professor Van-Anh Truong.
Jing graduated from Peking University with a bachelor's degree in Engineering in 2019. He joined IEOR in 2019 fall.
Jalaj is a PhD student in Operations Research at Columbia University, working with Prof. Daniel Russo. His thesis work explores foundations of modern Reinforcement Learning (RL) algorithms using ideas from optimization theory. In the past, he has also done research work on Bayesian Machine learning methods, specifically in designing computationally efficient Markov Chain Monte Carlo (MCMC) algorithms for posterior sampling. He is excited about applying RL and machine learning methods to problems of practical interest, for example in the areas of healthcare, neuroscience, autonomous systems, personalized Ads and more.
Prior to Columbia, Jalaj graduated from India Institute of Technology (IIT), Delhi in 2012 with a B.Tech in Industrial Engineering and Operations Research.
Jacob is a first-year PhD student in the IEOR department. He received his Bachelor's degree in Pure Mathematics and Operations Research & Management Science from UC Berkeley. His interests are primarily in stochastics and using stochastic models for practical ends.
Irene is currently a postdoctoral fellow in the Economics department at Stanford University, and will join the department of Management Science & Engineering at Stanford University as an assistant professor in Fall 2019. She conducts research on how to design matching markets and assignment processes to improve market outcomes, with a focus on public sector and socially responsible operations research. She is also interested in mechanism design for social good, graph theory, and games on networks. Irene obtained her A.B. in Mathematics from Princeton University in 2013, and her Ph.D. in Industrial Engineering and Operations Research from Columbia University in 2018.
Huajie Qian is currently working as a senior algorithm engineer at Alibaba DAMO Academy. He obtained his Ph.D. in Operations Research from Columbia University, advised by Henry Lam. His research borrows tools from statistics and machine learning to develop data-driven methodologies for stochastic simulation and optimization that can deal with uncertainties from data in an efficient and principled way. He received his M.S. degree in Applied and Interdisciplinary Mathematics from University of Michigan, and B.S. degree in Mathematics from Fudan University.
Harsh is a third year PhD student in the IEOR Department. He received his Bachelor's degree in Mechanical Engineering from the Indian Institute of Technology, Bombay. Harsh is co-advised by Professors Adam Elmachtoub and Vineet Goyal. He works on problems in revenue management and assortment optimization.
Haofeng Zhang is a Ph.D. student in the Department of Industrial Engineering and Operations Research at Columbia University. He started his PhD program in 2018. His primary research interests include developing reliable and robust machine/deep learning systems, uncertainty quantification and Monte Carlo methods.
Hao-Ting Wei's research focuses on algorithm design and analysis and combinatorial optimization.
He received his B.S. and M.S. degree in the Department of Industrial Engineering and Engineering Management from National Tsing Hua University.
Hal Cooper is a Senior Machine Learning Engineer at SimpleBet, Inc., where he designs predictive models for events (such as sporting or political contests) and takes them all the way to production. During Hal's doctoral studies under Professor Iyengar, Hal focused on interpretable machine learning models, especially those with network and graph-based structure.
During his PhD, Francois's research focused on efficient MCMC inference methods and stable optimization for large scale machine learning problems. Two of his summers were spent interning at Bloomberg and one at Amazon. Since graduating in 2018 he has been working at Facebook on applied machine learning problems in teams across Facebook and Instagram.
Fengpei Li is a Fourth-year Ph.D student in the IEOR Department. He completed his B.S. in Mathematics at University of California, San Diego.
His research interests includes Monte Carlo methods in Stochastic Modeling, Stochastic Optimization, Uncertainty Quantification and Reinforcement Learning.
Enrique Lelo de Larrea has been a PhD student in the IEOR Department since the spring of 2017. He graduated from ITAM (Mexico) with a double major in Applied Mathematics and Actuarial Science. After working for two years as a credit risk analyst at BBVA, he joined IEOR and earned his master's degree in Operations Research in 2017.
Enrique works on applying simulation methods and other mathematical tools to solve complex problems, such as sampling graphs with partial information or modeling emergency medical services systems. His interests include Monte Carlo Simulation, Applied Probability, and Financial Engineering.
Elioth is a PhD Candidate in the IEOR Department at Columbia University.
He is primarily interested in the interplay between simulation, machine learning and optimization from a probabilistic point of view. As well as their applications in healthcare to improve patients outcomes.
Chia-Hao joined the IEOR department in 2020. Prior to that, he received his M.S. in ECE from the University of Texas at Austin. Before that, he completed his B.S. in EE, minoring in physics, from National Taiwan University, Taipei, Taiwan.
His research interests largely fall into sequential decision making under uncertainty and stochastic control. For example, he is interested in online decision making problems and stochastic dynamic programming.d
Camilo is a Cheung-Kong innovation fellow and a PhD student in the IEOR department since the fall of 2016. Prior to joining Columbia, he attended Universidad de los Andes in Bogotá, Colombia, from which he holds a M.Sc. degree in Mathematics and B.Sc. degrees in both Mathematics and Economics.
Camilo works with Prof. Dylan Possamaï on developing theoretical models at the intersection between behavioral economics and contract theory. In particular, his research focuses on stochastic time-inconsistent control, backward stochastic differential equations and stochastic analysis.
Ayoub is a first year Ph.D student in the IEOR Department. He is mainly interested in optimization and algorithm design. Prior to joining Columbia, he graduated from Ecole Polytechnique (Paris) with an MS and BS in Applied Mathematics.
Apurv Shukla completed his undergraduate studies from Indian Institute of Technology Kharagpur, India. He is interested in problems in revenue management and marketplace analytics.
Antoine is an Assistant professor of Technology and Operations Management at INSEAD. His research applies mathematical modeling and analytics to operations management problems with an aim to: (1) quantify fundamental tradeoffs, and (2) design efficient data-driven algorithms to support operational decisions. More precisely, he focuses on revenue management and choice modeling with applications such as online advertising. He was an MSOM student paper finalist in 2014 and 2017 and a Nicholson student paper finalist in 2014 and 2015. After graduation, he spent a year as a post doctoral researcher at Google NYC.
Agathe is a PhD candidate at the IEOR Department since September 2017. She graduated in 2017 from Ecole Polytechnique (Paris, France) with a major in Applied Mathematics. Agathe's interests include applied probability, stochastic control and financial mathematics. She is currently working with Daniel Lacker on the theory and applications of mean field games.
Achraf started his Ph.D. in September 2018. His research interests include Stochastic and Adaptive optimization for Machine learning and Deep learning, Data-driven decision-making, Value of information and Mechanism design in low informational environments.
Prior to joining Columbia, I graduated from Ecole Polytechnique, Paris with a B.S and M.S degree in Applied Mathematics.
Abdellah is a Phd student at IEOR department since September 2020. His research interests include optimization and online learning. Prior to joining Columbia, he graduated from Ecole Polytechnique, Paris with a B.S and M.S degree in Applied Mathematics.
Aapeli is a doctoral student at the IEOR department. Prior to joining Columbia, he received a B.Math in pure mathematics from the University of Queensland, followed by a M.Sc in probability and statistics from the University of Melbourne. He has worked extensively in industry and is interested in working on research with wide-reaching impact that permeates beyond the academic setting.