Students
Current Students || Ph.D. Alumni || Master's Alumni || Undergraduate Honors Thesis Alumni || Post-Docs
B.S. in Computer Science, Stevens Institute of Technology, 2008
Research Interests: ad hoc teams and reinforcement learning
Website: [ www.cs.utexas.edu/~sbarrett ]
[ First-authored publications from UT ]
Sam, an NDSEG fellow, is researching ad hoc teams and reinforcement learning. His work focuses on how to cooperate with unknown teammates to accomplish a shared task. As part of Robocup's Standard Platform League, he worked on creating and selecting actions for robot soccer. He has also worked at MIT Lincoln Laboratory, applying machine learning to detect terrorist threats. Outside work, Sam enjoys ultimate frisbee, racquetball, and playing flute.
M.Sc. in Computer Science, Tel Aviv University, 2004
B.Sc. in Computer Science and Mathematics, Tel Aviv University, 2002
Research Interests: machine learning and autonomous agents
Website: [ www.cs.utexas.edu/~urieli ]
[ First-authored publications from UT ]
Daniel is researching machine learning and autonomous multiagent systems. His current work focuses on autonomous ship navigation. As a part of Robocup's 3D Simulation League, he worked on different aspects of a robotic soccer player, including localization, machine learning algorithms for skills acquisition, and game strategy. Outside work, Daniel enjoys literature, theatre, hiking and biking.
B.S. in Computer Science, Georgia Institute of Technology, 2009
Research Interests: ad hoc teams and intelligent agents
Website: [ www.cs.utexas.edu/~katie ]
Katie is researching ad hoc teams, where she is currently focusing on designing algorithms for ad hoc teamwork in role-based settings. As part of the UT Austin Villa RoboCup Standard Platform League team, she has worked on designing effective strategies for the RoboCup technical challenges, in which we gathered first and second place finishes in 2010. In her free time, Katie enjoys hiking, playing golf, traveling, and following Georgia Tech sports.
B.S. in Computer Science, Emory University, 2009
Research Interests: feature induction, autonomous intersection management
Website: [ www.cs.utexas.edu/~mhauskn ]
[ First-authored publications from UT ]
Matthew seeks to rethink the fundamental components of today's learning agents with hopes of creating the algorithmic machinery needed for agents to tackle more challenging, opening-ended domains. His research involves feature induction for agents with low level sensory input, model based reinforcement learning, and unsupervised exploration. Matthew also moonlights as a traffic engineer (highwayman?), investigating novel extensions of the Autonomous Intersections Management (AIM) project. In his spare time he enjoys guitar, weightlifting, foosball, bridge, and yoga.
M.E.E. in Electrical and Computer Engineering, Rice University, 2005
B.S. in Electrical and Computer Engineering, Rice University, 2004
Research Interests: multiagent systems, machine learning, humanoid robotics
Website: [ www.cs.utexas.edu/~patmac ]
[ First-authored publications from UT ]
Patrick is researching autonomous multiagent systems and machine learning. His current focus is on using reinforcement learning to develop locomotion skills and strategy for the for the UT Austin Villa RoboCup 3D Simulation League team. Before coming to UT, Patrick worked as a software engineer at Green Hills Software and Acelot, Inc. in Santa Barbara, California. Outside of his research, Patrick enjoys playing soccer, traveling, and following college football.
B.Tech. in Computer Science and Engineering, Indian Institute of Technology Roorkee, 2009
Research Interests: autonomous robotics, multi-robot systems
Website: [ www.cs.utexas.edu/~piyushk ]
[ First-authored publications from UT ]
Piyush is interested in the practical application of artificial intelligence techniques in the domain of robotics. He has taken up the perception challenge for the RoboCup Standard Platform League. His research has also led him to autonomous vehicles, and he currently teaches an FRI class on this subject. He is planning on continuing his research on multi-robot systems. In his spare time he enjoys playing racquetball, biking, and following politics.
B.A. in Pure Mathematics, Whitman College, 2007
Research Interests: machine learning, computer vision, multiagent systems
Website: [ www.cs.utexas.edu/~jmenashe ]
Jacob is interested in machine learning and computer vision, particularly in in applying real-time implementations for robotics systems. He has a background in theoretical mathematics and software development, and is currently focused on his research with multi-robot systems and the robot soccer team. Jacob is an active runner and biker, and enjoys a nice game of Magic: The Gathering.
M.Sc. in Computer Science, Tel Aviv University, 2012
B.Sc. in Computer Science and Music Composition, Tel Aviv University, 2010
Research Interests: machine learning, multiagent systems, computational musicology
Website: [ www.cs.utexas.edu/~eladlieb ]
Elad is interested in machine learning and its application in autonomous multiagent settings, as well as the emergent field of computational musicology. His current work focuses on learning musical preferences and modeling the effect of musical stimuli on human decision making. In his free time, Elad enjoys music in every way and form (listening to it, playing the piano and the guitar, and writing his own), reading (anything from classic literature and philosophy to the sports section), cooking, and playing racquetball.
"TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains"
[ Thesis code repository and annotated slides available from AI lab thesis page. ] Website: [ www.cs.utexas.edu/~todd ]
[ First-authored publications from UT ]
Job after graduation: Research Educator, Freshman Research Initiative, UT Austin
Currently: Algorithms Engineer, Nest.com
Todd's dissertation focussed on reinforcement learning and robotics, specifically looking at the exploration versus exploitation problem in reinforcement learning and working to apply it to large domains. Before coming to UT, Todd worked in the Motion Analysis Laboratory at Spaulding Rehabiliation Hospital, Motorola, Sun Microsystems, and the Air Force Research Laboratory. Outside of his research, Todd enjoys ultimate frisbee and foosball and is a dedicated New England Patriots fan.
Representative publication from UT:
"Learning from Human-Generated Reward"
[ Thesis defense presentation and slides ]
Website: [ www.cs.utexas.edu/~bradknox ]
[ First-authored publications from UT ]
Job after graduation: Postdoctoral Fellow, MIT
Currently: Same
Brad, an NSF Graduate Research Fellow, is researching how to design agents that can be taught interactively by human reward—somewhat like animal training. The TAMER framework is the result of his efforts. After giving a lot of demos of a trainable Tetris agent, he keeps getting called "The Tetris Guy." Brad spent the summer of 2011 collaborating at the MIT Media Lab with with Cynthia Breazeal, where he implemented TAMER on the social robot Nexi and began a postdoc in late 2012. In his free time, Brad runs in "barefoot" sandals, eats tasty trailer food, and tries out his robot training techniques on his dog.
Representative publication from UT:
"Sample Efficient Multiagent Learning in the Presence of Markovian Agents"
Website: [ www.cs.utexas.edu/~chakrado ]
[ First-authored publications from UT ]
Job after graduation: Research Engineer, Microsoft
Currently: Same
Doran's research is on agent modeling in multiagent systems. His main interest lies in modeling opponents in multiagent settings such as repeated and sequential games. He also has a parallel interest in model-based reinforcement learning and its overlap with multiagent modeling. He is also a member of the team that won the first Trading Agent Ad Auction competition held at IJCAI, 2009. Between his years in schools, he has worked as a software architect for a couple of years for Sybase and Johnson & Johnson. He is one of the developers of the open source software project perf4j: a statistical logging framework. Outside work, he is a soccer geek and loves following all kinds of soccer leagues around Europe.
Representative publications from UT:
"Learning Methods for Sequential Decision making with Imperfect Representations"
Website: [ www.cs.utexas.edu/~shivaram ]
[ First-authored publications from UT ]
Job after graduation: Scientist, Yahoo! Labs Bangalore
Currently: Same
Shivaram is fascinated by the question of how intelligence can be programmed, and in particular how systems can learn from experience. His dissertation examines the relationship between representations and learning methods in the context of sequential decision making. With an emphasis on practical applications, Shivaram has extensively used robot soccer as a test domain in his research. His other interests include multi-agent systems, humanoid robotics, and bandit problems. Shivaram's return to his home country, India, upon graduation is motivated by the desire to apply his expertise as a computer scientist to problems there of social relevance.
Representative publications from UT:
"Robust Color-based Vision for Mobile Robots"
Website: [ www.cs.utexas.edu/~impjdi ]
[ First-authored publications from UT ]
Job after graduation: Software Engineer, Google
Currently: Same
Juhyun's dissertation was on robust color-based vision for autonomous mobile robots. Specifically, he employed concepts and techniques from 3D computer graphics and exploited the robot's motion and observation capabilities to achieve that goal. As a member of the UT Austin Villa team, he contributed to the RoboCup @Home league 2007 and RoboCup Standard Platform League 2010, which finished in 2nd and 3rd places, respectively. Before joining UTCS, he obtained his B.S. in Computer Science from Seoul National University and worked at Ebay Korea. In his free time, Juhyun enjoys playing the electric guitar, snowboarding, and videogaming.
Representative publication from UT:
"Adaptive Trading Agent Strategies Using Market Experience "
Website: [ www.cs.utexas.edu/~TacTex/dpardoe ]
[ First-authored publications from UT ]
Job after graduation: Scientist, Yahoo! Labs
Currently: Software Engineer, Google
David's research focuses on applications of machine learning in e-commerce settings. This research was motivated by his participation in the Trading Agent Competition, where he designed winning agents in supply chain management and ad auction scenarios. His dissertation explored methods by which agents in such settings can adapt to the behavior of other agents, with a particular focus on the use of transfer learning to learn quickly from limited interaction with these agents.
Representative publications from UT:
- TacTex09: A Champion Bidding Agent for Ad Auctions (AAMAS, 2010)
- Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge (INFORMS Journal on Computing, 2010)
"Structured Exploration for Reinforcement Learning"
[ Thesis code repository and annotated slides ]
[ First-authored publications from UT ]
Job after graduation: Software Engineer, Apple
Currently: Same
Nick's dissertation examined the interplay between exploration and generalization in reinforcement learning, in particular the effects of structural assumptions and knowledge. To this end, his research integrates ideas in function approximation, hierarchical decomposition, and model-based learning. He has also worked at the IBM Watson Research Laboratory, applying ideas from reinforcement learning to challenging problems in the field of autonomic computing.
Representative publication from UT:
- Compositional Models for Reinforcement Learning (ECML, 2009)
"Automated Domain Analysis for General Game Playing"
Website: [ www.cs.utexas.edu/~kuhlmann ]
[ First-authored publications from UT ]
Job after graduation: Senior Research Scientist, 21st Century Technologies
Currently: Data Mining Scientist, Apple
Greg's dissertation explored the benefits of domain analysis and transfer learning to the general game playing problem. Earlier in his graduate career, he was also a contributing member of the UT Austin Villa robot soccer team in both the standard platform and simulated coach leagues. At 21st Century Technologies, Greg applied machine learning and intelligent agent techniques to unmanned systems and data mining problems.
Representative publication from UT:
"Autonomous Intersection Management"
Website: [ www.cs.utexas.edu/~kdresner ]
[ First-authored publications from UT ]
Job after graduation: Software Engineer, Google
Currently: same
Kurt's dissertation was on Autonomous Intersection Management, the project he helped start in his second year. He currently is employed at Google, where he employs mind-boggling amounts of data to make the World Wide Web a better place. Outside of his academic interests, Kurt enjoys playing the guitar, listening to music, playing board games, and photography.
Representative publication from UT:
"Autonomous Inter-Task Transfer in Reinforcement Learning Domains"
Website: [ http://www.cs.lafayette.edu/~taylorm/ ]
[ First-authored publications from UT ]
Job after graduation: Postdoctoral Research Associate with Milind Tambe at The University of Southern California
Currently: Assistant Professor, Department of Computer Science, Washington State University
Matt's Ph.D. dissertation focused on transfer learning, a novel method for speeding up reinforcement learning through knowledge reuse. His dissertation received an honorable mention in the competition for the IFAAMAS-08 Victor Lesser Distinguished Dissertation Award. After UT, Matt moved to The University of Southern California to work with Milind Tambe as a post-doc, pursuing his interests in multi-agent systems.
Representative publications from UT:
"Autonomous Sensor and Action Model Learning for Mobile Robots"
[ First-authored publications from UT ]
Job after graduation: Credit Derivatives Strategist at Morgan Stanley
Currently: same
Dan's dissertation presented algorithms enabling an autonomous mobile robot to learn about the effects of its actions and the meanings of its sensations. These action and sensor models are learned without the robot starting with an accurate estimate of either model. These algorithms were implemented and tested on two robotic platforms: a Sony AIBO ERS-7 and an autonomous car. After graduating, Dan joined Morgan Stanley as a trading strategist to model the behavior of illiquid credit derivatives.
Representative publication from UT:
"Adaptive Representations for Reinforcement Learning"
Website: [ staff.science.uva.nl/~whiteson ]
[ First-authored publications from UT ]
Job after graduation: Assistant Professor in the Informatics Institute at the University of Amsterdam
Currently: same
Shimon's research is primarily focused on single- and multi-agent decision-theoretic planning and learning, especially reinforcement learning, though he is also interested in stochastic optimization methods such as neuroevolution. Current research efforts include comparing disparate approaches to reinforcement learning, developing more rigorous frameworks for empirical evaluations, improving the scalability of multiagent planning, and applying learning methods to traffic management, helicopter control, and data filtering in high energy physics.
Representative publications from UT:
"Robust Structure-Based Autonomous Color Learning on a Mobile Robot"
Website: [ www.cs.ttu.edu/~smohan/ ]
[ First-authored publications from UT ]
Job after graduation: Research Fellow at University of Birmingham (UK) with Jeremy Wyatt, Aaron Sloman and Richard Dearden, on the EU-funded Cognitive Systems (CoSy) project. August 2007 -- October 2008.
Currently: Assistant Professor in the Department of Computer Science at Texas Tech University.
Mohan's Ph.D. dissertation focused on enabling a mobile robot to autonomously plan its actions to learn models of color distributions in its world, and to use the learned models to detect and adapt to illumination changes. His post-doctoral work on using hierarchical POMDPs for visual processing management won a distinguished paper award at ICAPS-08. His current research interests include robot vision, probabilistic planning, statistical learning and multiagent systems.
Representative publications from UT:
- Structure Based Color Learning on a Mobile Robot under Changing Illumination (Autonomous Robots, 2007)
- Color Learning and Illumination Invariance on Mobile Robots: A Survey (Robotics and Autonomous Systems, 2009)
"Learning in Simulation for Real Robots"
Website: [ www.cs.utexas.edu/~afarchy ]
Job after graduation: Microsoft - Windows Phone Kernel Team
Currently: Same
For his Master's thesis, Alon studied several approaches to use simulation learning to improve the walk speeds of the real Aldabaran Nao robots. Though difficult, by constraining the simulation and iteratively guiding the simulation's learning routine, the task proved to be feasible, and an improvement of about 30% walking speed was achieved. Alon previously worked at Nvidia for two internships, working to bring up the the Android operating system to the company's Tegra processors.
"A Delayed Response Policy for Autonomous Intersection Management"
Website: [ www.cs.utexas.edu/~neda ]
Job after graduation: Neuroscience Research Assistant, The University of Texas at Austin Currently: Same
Neda did her Master's thesis on a delayed response policy for Autonomous Intersection Manager (AIM) as well as physical visualization of AIM using Eco-be robots. Before that she had worked on obstacle avoidance for 4-legged robots. Starting in 2010, she has been conducting research in the field of Neuroscience in the Center for Perceptual Systems at UT Austin.
"News Mining Agent for Automated Stock Trading"
Job after graduation: Amazon.com
Currently: Shutterfly.com
For his Master's thesis, Guru worked with Prof. Peter Stone and Prof. Maytal Tsechansky to study the correlation between stock market movement and internet news stories, using text mining techniques. After graduation, Guru joined Amazon.com. He worked with multiple organizations at Amazon including the world wide supply chain and retail systems. At Shutterfly.com, he is the Sr. Director and General Manager of the Phoenix Engineering Center. He is responsible for engineering and product strategy for their Photobooks business (a $100 Million revenue business unit). Guru holds multiple patents pending in ecommerce. Prior to joining Amazon, Guru held research intern positions at IIT Delhi, IBM Research Center at Almaden, CA and the University of Joensuu in Finland. Reach him at gurushyam@gmail.com.
"Evolutionary Algorithms in Optimization of Technical Rules for Automated Stock Trading"
Job after UT: Murex, North America Inc.
Currently: MBA Candidate at Kellogg School of Management
Harish worked with Prof. Peter Stone and Prof. Ben Kuipers to study automated stock trading strategies using intelligent combinations of simple, intuitive ``technical'' trading rules. Since he graduated from UT, Harish has worked in the financial software industry, mostly recently at Murex, which develops derivatives trading platforms and risk management software. He is currently pursuing an MBA at Kellogg School of Management, Northwestern University; where his areas of focus are Entrepreneurship & Innovation and Finance. His current interests are in product commercialization and new venture financing. He can be reached at harish.subramanian@gmail.com.
" Inverse Kinematics Kicking in the Humanoid RoboCup Simulation League"
Job after graduation: Programmer White Whale Games
Currently: same
Adrian's undergraduate honors thesis focused on the kicking system used in UT Austin Villa's winning entry to the 2011 and 2012 RoboCup 3D Simulation League competitions. He is currently the programmer for a small video game startup company, White Whale Games, working on a mobile game called God of Blades. Adrian completed two REU's at Trinity University and has interned at Starmount Systems and Microsoft.
"Transformation of Robot Model to Facilitate Optimization of Locomotion"
Job after graduation: TBD
Currently: same
Nick's undergraduate honors thesis studies how to enable a simulated humanoid robot to stand up from a fallen position, and how to generalize such a skill to robots with different physical chacteristics. Nick has interned at at HP, Qualcomm, and Facebook.
"Constructing Drivability Maps Using Laser Range Finders for Autonomous Vehicles"
Job after graduation: Masters student at UT Austin
Currently: Ph.D. student at Cornell
Chau's undergraduate honors thesis aims at using data from a 3D laser range sensor on an autonomous vehicle to improve the vehicle's capability to recognize drivable road segments. Chau interned at IBM, Cisco, and Facebook.
"Exploiting Human Motor Skills for Training Bipedal Robots"
Website: [ www.adamsetapen.com ]
Job after graduation: Masters student at UT Austin
Currently: Ph.D. student at MIT Media Lab
Adam is a Ph.D. student researching human-robotic interaction, specifically investigating ways to exploit the ability of a human to quickly train robots. Adam has interned at TRACLabs, Amazon.com, and the University of Virginia Medical Center. In his free time, he enjoys biking, racquetball, and playing cello and guitar.
"Building an Autonomous Ground Traffic System"
Website: [ www.mutualmobile.com ]
Job After Graduation: Co-Founder of SparkPhone in Austin, TX
Currently: Chief Operating Officer of Mutual Mobile in Austin, TX
Tarun's undergraduate thesis detailed his contributions to obstacle tracking in UT's entry to the DARPA Urban Grand Challenge and the Autonomous Intersection Management project. He is now working on launching SparkPhone - an application that provides users with 80-90% cheaper international calls versus directly dialing through your carrier. Additionally, unlike VOIP services, SparkPhone does not require that you have a WiFi or data connection when making phone calls because all SparkPhone calls go through the cell network. Over the past year Tarun has built several iPhone apps - one of which (HangTime) was just named by PC World as the dumbest iPhone app of all time.
"Creating a High-Level Control Module for an Autonomous Mobile Robot Operating in an Urban Environment"
Job after graduation: Software/Systems Engineer at USAA in San Antonio, TX
Currently: US Air Force officer
Ryan's undergraduate honors thesis detailed his contribution to UT's entry in the 2007 DARPA Urban Challenge competition. His work mostly centered on the high-level control and decision-making aspects of an autonomous vehicle as it navigates through city streets. After graduating, Ryan took a position as a software engineer at USAA, where he has designed and implemented significant enhancements to the authentication and content capture components of usaa.com. Even so, his passion for robotics still continues today. Ryan is currently pursuing an MBA in Finance from UTSA.
"An Analysis of the 2005 TAC SCM Finals"
MSc in Computer Science, University of British Columbia, 2008
Website: [ optemo.com/team ]
Job after graduation: Graduate student at University of British Columbia Currently: Co-founder of start-up company "Optemo"
Jan's thesis analyzed the 2005 TAC SCM Finals. This was part of the preparatory work that led the TacTex team to win the 2006 TAC SCM Championship. At UBC Jan became interested in natural language processing and wrote a dissertation titled "Supervised Machine Learning for Email Thread Summarization". Subsequently Jan co-founded a start-up company called Optemo that uses artificial intelligence to assist online shoppers by providing an example-centric product navigation solution.
"Discovering Conditions for Intermediate Reinforcement with Causal Models"
Irvin's undergraduate honors thesis dealt with accelerating reinforcement learning by automatically applying intermediate reward using causal models. His thesis received the Sun Microsystems Award for Excellence in Computer Sciences/Computer Engineering Research at the University of Texas undergraduate research forum. Irvin is currently studying reinforcement learning as a Ph.D. student in the computational cognitive neuroscience group at Princeton.
"Creation of a Fine Controlled Action for a Robot"
Job after UT: Graduate student at Carnegie Mellon University
Currently: Teacher in the Pittsburgh Public Schools (CAPA)
Ellie's undergraduate honors thesis focussed on enabling robots to perform action sequences that have low tolerance for error. After graduating, Ellie completed her M.S. in robotics and M.A.T. in secondary mathematics. She currently teaches math at the Pittsburgh performing arts school (CAPA) and hopes to introduce the joy of robotics to her students.
Ph.D. in Computer Science, Bar-Ilan University, Israel, 2009
Research Interests: multi-robot systems
Website: [ www.cs.utexas.edu/~agmon ]
Job after UT: Assistant professor at Bar-Ilan University in Israel
Currently: same
Noa's research is focused on various aspects of multi-robot systems, including multi-robot patrolling, robot navigation and multi-agent planning in adversarial environments. Her research uses tools from theoretical computer science for analyzing problems in practical multi-robot systems.
Representative publication from UT:
Ph.D. in Computer Science, University of Maryland, College Park, 2008
Research Interests: multiagent systems and artificial intelligent planning
Website: [ www.cs.utexas.edu/~chiu ]
Job after UT: Assistant professor at Ulsan National Institute of Science and Technology in Korea
Currently: same
Chiu worked mainly on the Autonomous Intersection Management project while at UT Austin as a post-doc. Before entering UT Austin, he worked on several research projects in Artificial Intelligence, including automated planning and error detection in multiagent systems. In his spare time, he enjoys hiking and watching movies.
Representative publication from UT:
- Enforcing Liveness in Autonomous Traffic Management. (AAAI, 2011)
Ph.D. in Computer Science, University of Newcastle, Australia, 2006
Research Interests: legged robotics, autonomous vehicles
Website: [ www.cs.utexas.edu/~mquinlan ]
Job after UT: Engineer at Clover in Mountain View, California
Currently: same
Michael researches various aspects of robotic systems, including motion, vision and localization. He currently teaches a class on Autonomous Vehicles and competes as part of the Austin Villa team at RoboCup using the Nao humanoid robots. In his spare time he enjoys basketball, cycling, running and soccer.
Representative publication from UT:
Ph.D. in Computer Science, University of Mainz, 2007
Research Interests: reinforcement learning, machine learning
Website: [ www.cs.utexas.edu/~tjung ]
Job after UT: Postdoc at University of Liege in Belgium
Currently: same
Tobias is interested in optimization and optimal decision-making: in particular how to act optimally when individual decisions have uncertain outcomes and far-reaching consequences. Knowing that his own abilities in this area are rather limited, he focuses his research on how these problems can be solved automatically and computationally. His thesis (nominated for the GI National Dissertation Prize) describes a novel and highly sample efficient online algorithm for reinforcement learning that is specifically aimed at learning in high-dimensional continuous state spaces. Some of his other work includes multivariate time series prediction, sensor evolution and curiosity-driven learning.
Representative publication from UT:
Ph.D. in Computer Science from UT Austin, 2008
Research Interests: developmental and cognitive robotics, autonomous vehicles, human robot interaction
Website: [ daneel.traclabs.com/~pbeeson/ ]
Job after UT: Senior Scientist at TRACLabs Inc.
Currently: same
Patrick is interested in the intersection of AI and robotics. This includes human-robot interaction, cognitive models for robotic navigation, and developmental robotics. He is currently working on a sensor-to-symbol cognitive architecture, which will enable modular robotic platforms to be used in a variety of domains with minimal software changes.
Representative publication from UT:
- Multiagent Interactions in Urban Driving. (JoPhA, 2008)
Ph.D. in Cognitive Science, University of California, San Diego, 2006
Research Interests: developmental robotics, human-robot interaction
Website: [ www.cs.arizona.edu/~ianfasel ]
Job after UT: Assistant Research Professor, CS, University of Arizona
Currently: Head of development, Machine Perception Technologies
Ian's research is on developmental robotics and human-robot interaction. The first topic seeks to answer: how can a (human or robot) baby discover basic low-level perceptual and motor concepts through prolonged autonomous interactions with the world? The second topic broadens this to include social concepts, such as emotions, gaze-following, and turn-taking, and incorporates both care-giving and explicit teaching into the developmental process as well. This work mostly involves application and development of machine learning methods to robots which must interact with objects and people in the world in real-time.
Representative publication from UT:
- A Task Specification Language for Bootstrap Learning (AAAI Symposium, 2009)
Ph.D. in Computer Science, Tulane University, 2006
Research Interests: multiagent systems and machine learning
Website: [ www.cs.usm.edu/~banerjee/ ]
Job after UT: Assistant Professor, DigiPen Institute of Technology
Currently: Assistant Professor in The University of Southern Mississippi
As a post-doc, Bikram worked on transfer learning methodology for challenging knowledge transfer tasks, such as general game playing. Currently, he is working on multiple projects funded by NASA and DHS, that exploit multi-agent systems technology to solve problems relating to rocket engine tests and large scale crowd simulation.
Representative publication from UT:
- General Game Learning Using Knowledge Transfer (IJCAI, 2007)
Ph.D. in Computer Science, Georgia Tech, 2005
Research Interests: planning and transfer learning
Job after UT: Fair Isaac Corporation
Currently: Google
Yaxin's Ph.D. research at Georgia Tech was on risk-sensitive planning. As a post-doc at UT Austin, Yaxin was key personnel on the Transfer Learning project. His research focussed on transfering value functions among related sequential decision making problems in order to speed up learning.
Representative publication from UT: