Zitong Wang is a 3rd-year Ph.D. student in Industrial Engineering and Operations Research (IEOR) department in Columbia. His current research interest focuses on uncertainty quantification for randomized algorithms. He received his Bachelor's and Master's degree in Mathematics at the Chinese University of Hong Kong (CUHK) in 2020.
Zhenyuan Liu joined the IEOR department in 2019. He received his bachelor's degree in Financial Mathematics from Peking University in 2019. His current research interests include distributionally robust optimization, input uncertainty quantification, bootstrap and rare event estimation.
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.
Yunhao is a research scientist at Google DeepMind London. His research generally revolves around reinforcement learning, with a focus on developing scalable algorithms and their applications. Previously, Yunhao spent two internships as a research scientist intern at Google DeepMind Paris. Yunhao completed his PhD study under the guidance of Prof. Shipra Agrawal at Columbia University. He also holds a Bachelor degree in Physics from Fudan University and a Master of science degree in Financial Engineering from Columbia University.
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.
Yuanzhe joined the IEOR department in Fall 2021 as a PhD student after completing his dual MS in Statistics and Mathematics from Georgia Tech, where he worked on projects related to random matrix theory and the transient analysis of stochastic systems. Prior to that, he was working in a Fintech startup in China and obtained an undergraduate degree in economics from East China Normal University while working full-time. His research interest lies in the intersection of applied probability and optimization theory with applications to data science. For example, he is interested in non-convex optimization theory and robust analysis of stochastic systems.
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 stochastic simulation under supervision of Professor Henry Lam.
Yuan is a 5th-year PhD student in Operations Research (IEOR) at Columbia University. Before that, he graduated from National University of Singapore with a Bachelor’s Degree in Applied Mathematics. Yuan's research focuses on optimization models and methods in the context of game theory, market design, and machine learning. Motivated by real-world applications such as Internet ad auctions and fair resource allocation, Yuan has proposed new models of competitive markets that capture the large-scale or continuous nature of these settings, and developed efficient online and offline optimization methods for computing their respective equilibria. Concurrently with this work, Yuan has also contributed new algorithmic techniques and convergence results for first-order methods in convex optimization.
Yilie Huang joined the IEOR Department at Columbia in September 2019. He also received his Master of Science degree at Columbia IEOR in 2018. Prior to Columbia, he earned a Bachelor of Science degree in Mathematics and Applied Mathematics at Zhejiang University. His research focuses on reinforcement learning and machine learning. Currently, he is working with Prof. Xunyu Zhou on solving asset allocation and option pricing problems from continuous-time 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 will join the Operations, Planning, Accounting & Control (OPAC) group at Eindhoven University of Technology as an Assistant Professor in Fall 2021. Her research centers on simple and flexible strategies in supply chain management and service operations. In her doctoral research, she mainly focuses on two topics: (1) a new notion of flexibility that has emerged in online platforms, and (2) simple-to-implement strategies for complex operations problems. During her time at Columbia, Yeqing was advised by Professor Adam Elmachtoub. Yeqing obtained her B.S. in Mathematics from Fudan University in 2014 and her M.S. and Ph.D. in Operations Research from Columbia IEOR in 2016 and 2021.
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.
Xujia Liu is a Ph.D. student in the Industrial Engineering and Operations Research (IEOR) department at Columbia University. He received his B.Eng. in Systems Engineering and Engineering Management from The Chinese University of Hong Kong (CUHK) in 2013, and M.Sc. in Financial Engineering from IEOR in 2017. He is currently working with Professor Garud Iyengar on applications of optimization and dynamic programming, such as portfolio optimization and inventory management.
Xuan is currently working at Facebook as a postdoctoral research scientist in the core data science group. She is broadly interested in algorithms and mechanism designs for networked marketplaces and, more generally, in the interplay between economics, optimization, and computer science. She obtained her B.A. in Mathematics from Cornell University in 2014, and her Ph.D. in Industrial Engineering and Operations Research from Columbia University in 2021.
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.
Xingyu Zhang completed his PhD in 2021 and is working at Amazon as a Research Scientist. His primary interests are in discrete optimization and his thesis work is in optimal stopping and matching problems. His PhD advisors were Jay Sethuraman and Shipra Agrawal, and has also worked closely with Yuri Faenza. Before Columbia, he completed a B.S. in Mathematics and Penn State.
Xiaopeng Li is a second-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 non-convex optimization and deep learning theory.
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 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.
Vladlena is a researcher specializing in optimization problems. She applies her expertise in algorithm development, data science and modeling to solve industry problems, for example, assortment optimization, pricing models, inventory visualization and placement. Her PhD thesis under advisement of Yuri Faenza covers discrete optimization problems in matchings and scheduling.
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 third-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 differential privacy, algorithm design and machine learning.
Tianyu Wang is a second-year Ph.D. student in Industrial Engineering and Operations Research (IEOR) department at Columbia University. He received his Bachelor's degree in Information Systems and Mathematics at Tsinghua University in 2021. His current interests lie broadly in data-driven optimization and statistical machine learning.
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 fifth-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.
Randy started his PhD in the IEOR department in the Fall of 2015. His research interests lie in optimization and machine learning. His advisor was Professor Shipra Agrawal, and worked on algorithms for reinforcement learning and inventory management.
Raghav Singal completed his PhD in 2020 and would be joining the Tuck School of Business (Dartmouth College) as an Assistant Professor in 2021, after spending a year at Amazon. Raghav's primary research interest is in the area of analytics. He likes to build models that help businesses understand complex systems and make better decisions. During his time at Columbia, Raghav was advised by Professors Omar Besbes, Vineet Goyal, and Garud Iyengar.
Rachitesh has been a PhD student in the IEOR department since 2019, where he is advised by Christian Kroer and Santiago Balseiro. Prior to joining the department, he received his Bachelor's degree in Mathematics from Indian Institute of Science. His primary research interests are game theory and data-driven optimization, with a focus on applications in online advertising and revenue management.
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.
Research interests: Algorithmic Game Theory, Combinatorial optimization
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.
Madhu is a Ph.D student in the IEOR Department working with Garud Iyengar. 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 Causality, Optimization and Probabilistic Modeling.
Luofeng Liao is a Ph.D. student in the Industrial Engineering and Operations Research department at Columbia University. He received his B.S. in Computer Science from Fudan University, China, and M.S. in Statistics from the University of Chicago. His interests include auction market statistical inference, machine learning for causal inference and econometrics, theoretical reinforcement learning and adversarial optimization.
Luc is a 4th 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 game theory. He is currently working with Prof. Daniel Lacker on the theory mean field games and large interacting particles systems.
Lingyi Zhang is currently a fifth 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 advised by Professor Yuri Faenza, working on discrete optimization problems.
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. His research interest lies in nonconvex optimization, semi-algebraic geometry, and low-rank matrix recovery. Prior to Columbia, he received a Bachelor of Science in Mathematics from the University of Hong Kong.
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-Clément is an assistant professor in the Information Systems and Operations Management Department at HEC Paris. He completed his Ph.D. from the IEOR Department at Columbia University in 2021, and his M.Sc. from Ecole polytechnique (Paris) in 2016. His research interests broadly lie at the intersection of sequential decision-making for healthcare and data-driven optimization algorithms. His latest collaborations include robust allocations of beds in intensive care units with hospitals in California and interpretable ventilator allocations guidelines with hospitals in New York City. His research articles have appeared in leading academic journals, medical and artificial intelligence conferences.
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 an Assistant Professor at the Economics Department of Renmin University of China. Her research interests lie at the intersection of data science and optimization, with a focus on designing and analyzing optimization algorithms for solving decision problems in information-rich and highly dynamic environments. Specific applications of her research include designing personalized pricing or recommendation strategies for online service platforms, and allocating resources of limited inventory under the healthcare setting. Jingtong received both her PhD in Operations Research and BS in Financial Engineering from Columbia University.
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 fifth-year Ph.D. student in the IEOR department. He was born and raised in Salt Lake City, Utah and earned his B.A. with High Honors in Math and Operations Research at UC Berkeley.
At Columbia, Jacob is co-advised by Professors Karl Sigman and Adam Elmachtoub and works on problems in queueing theory.
Jacob is also involved in a variety of leadership roles at Columbia, serving as a Senior Lead Teaching Fellow at the Columbia Center for Teaching and Learning and as a Department Representative for the IEOR department in the Engineering Graduate Student Council.
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.
Hyemi Kim is a second-year Ph.D. student in the Department of Industrial Engineering and Operations Research at Columbia University. Her research interest lies in data-driven decision-making and revenue management for social good. Prior to joining Columbia, she graduated from Korea Advanced Institute of Science and Technology with an M.S. and B.S. in Industrial and Systems Engineering.
Humoud Alsabah received his B.S. degree in 2012 from Kuwait University, and his M.S. and Ph.D degrees in 2016 and 2020, respectively, from Columbia University. He is currently an Assistant Professor in Kuwait University. His current research interests include commodity pricing and financial technology.
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.
Haoxian has been a Ph.D. student in the IEOR Department at Columbia since Fall 2021. Before that, he completed his master's degree in Operations Research at Columbia and bachelor's degree in Applied Mathematics at UCLA. His research interests include stochastic analysis, optimization, and machine learning.
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 was a 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. After graduating from IEOR, Enrique will stay in New York and will be joining the Quantitative Analytics team at Barclays.
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 Chang joined the department in 2020. Prior to that, he received his MS in ECE from UT Austin and his BS in EE, minoring in Physics, from NTU, Taipei, Taiwan.
His research interest lies in sequential decision making under uncertainty.
He is now working on approximating large scale Markov decision processes, with applications on healthcare and revenue management.
Chengyue received his master's degree in Operations Research from IEOR and started the PhD program in 2021. Prior to Columbia, he earned a bachelor's degree in Mathematics from Zhejiang University in 2019. Chengyue is fortunate to be co-advised by Yuri Faenza and Jay Sethuraman. His research interests include combinatorial optimization, discrete mathematics, algorithmic game theory and matching markets.
Chengpiao Huang is a first-year PhD student in the IEOR department. He is interested in designing efficient algorithms for nonconvex optimization problems. Prior to joining Columbia, he received a Bachelor's degree in Mathematics and Applied Mathematics from The Chinese University of Hong Kong, Shenzhen.
Camilo is a Cheung-Kong innovation fellow and a PhD student in the IEOR Department at Columbia University. Camilo works with Prof. Dylan Possamaï on developing theoretical models at the intersection between behavioral economics and contract theory. Camilo research interests are in stochastic time-inconsistent control, financial mathematics, backward stochastic differential equations, stochastic analysis and convex optimization.
Ayoub started his PhD in September 2020. His research interests include Assortment optimization, online learning and matching markets. Before joining Columbia, Ayoub graduated from Ecole Polytechnique (Paris) with an MS and BS in Applied Mathematics.
Arindam is a Ph.D. student at the IEOR Department, Columbia University. Before joining Columbia, he completed a B.Stat (Hons.) and M.Stat from Indian Statistical Institute, Kolkata, India. He also worked at Capital One for one year.
Apurv is a final year PhD candidate. His primary research interests lies in network science, optimization and machine learning.
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 working with Prof. Yuri Faenza. 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 beyond the academic setting.