Find Academic Supervisors

Steve MannView profile

Professor

• Wearable Computing
• Augmented Reality (AR)
• Digital Imaging
• +7 more

Prof. Steve Mann is a tenured full professor at the University of Toronto in the Department of Electrical and Computer Engineering , Faculty of Applied Science and Engineering. He is also the Director of the EyeTap Personal Imaging (ePi) Lab and the FL_UI_D Laboratory , while serving as Chief Scientist for both the Rotman School of Management's CD Lab and Meta . Education: PhD from MIT (1997) As the inventor of wearable computing , Mann's research spans augmented reality (EyeTap) , high dynamic range (HDR) imaging , comparametric equations , and humanistic intelligence (HI) . He pioneered inventrepreneurship education and developed the hydraulophone , an instrument based on absement theory. His recent work includes the 2025 IEEE Consumer Electronics Award and 2024 Lifeboat Foundation Guardian Award , recognizing contributions to wearable tech and humanity. Scientific achievements include over 200 publications , patents , and media exhibits at institutions like MoMA and the Smithsonian. Scientific Awards: 2025 IEEE Consumer Electronics Award 2024 Lifeboat Foundation Guardian Award 2004 Leonardo Award for Excellence Coram International Sustainable Design Award (First Place) Advising and Innovation: Co-founded over $1B in tech ventures with students, integrating invention and entrepreneurship into academia. His labs explore fluid-based musical instruments and privacy-enhancing wearables . Labs & Teams: Leads the ePi Lab and FL_UI_D Lab , focusing on wearable imaging, mediated reality, and reverse kinematics in fluidic musical systems.

Li QianView profile

Professor

• Quantum Photonics
• Quantum Communication
• Nonlinear Optics
• +3 more

Professor Li Qian is a faculty member in the Department of Electrical and Computer Engineering at the University of Toronto , where she leads experimental research in quantum photonics , quantum communication , and high-precision metrology . Her work bridges industrial innovation and academic exploration, with a focus on fiber-based quantum technologies and nonlinear optical devices . Education: BASc (honours), 1993 MASc, 1996 PhD, 2000 Her research in quantum entanglement includes developing room-temperature, fiber-integrated entangled photon sources for future quantum networks. In quantum communication , she advances measurement-device-independent QKD and twin-field QKD to enhance security and practicality. Her high-precision sensing work uses resonator-free spectral features for applications like ultra-narrow Brillouin dips and slow light generation . Recent publications highlight trends in quantum key distribution (QKD), machine learning for entanglement detection , and nonlinear fiber optics . Her group commercialized dispersion measurement technologies via startup Inometrix Inc. Scientific honors include: Fellow, Optica (2023) Canada Research Chair in Photonic Technologies (2006–2012) Premier’s Research Excellence Award (2004) University of Toronto Alumni Association Early Career Award (2003) Prof. Qian advises a diverse team of PhD and Master’s students , including Amita Gnanapandithan , Reem Mandil , and Alexander Greenwood . Her lab specializes in quantum optics , optical sensing , and telecom-integrated photonics .

David KnappView profile

Researcher

• Cell Biology
• Medical Genetics
• Synthetic Biology
• +5 more

David Knapp is a Principal Researcher at the Institute for Research in Immunology and Cancer (IRIC) within the University of Montreal . His research focuses on understanding the molecular basis of cell identity through single-cell analysis and synthetic genetic circuits, with applications in regenerative medicine and cancer therapy. Previously, he completed his PhD in Experimental Medicine at the University of British Columbia and a postdoctoral fellowship at the University of Oxford. Academic Role: Researcher, Department of Pathology and Cell Biology Research Unit: Cellular Engineering Research Unit Contact: david.knapp@umontreal.ca His work explores the attractor state model of cell identity, investigating transitions between stable molecular states regulated by genetic networks. This research has implications for cell reprogramming, oncogenesis, and therapeutic target identification. He employs technologies like single-cell sequencing and synthetic biology to manipulate and analyze cell fate. Recent publications highlight his expertise in hematopoietic stem cell dynamics , CRISPR optimization , and immune cell engineering . Articles span topics from Waddington-like landscapes to Cas9 guide RNA expression systems , reflecting his interdisciplinary approach. Scientific Awards and Scholarships: SEDA Learning Support Award (2019) CIHR Postdoctoral Fellowship (2016–2019) CIHR Canada Graduate Scholarship - Master’s (2011–2012) CIHR Transplantation Research Scholarship (2010–2011) David Knapp's research has been supported by grants from Canadian Institutes of Health Research (CIHR) and other national funding bodies. His laboratory at IRIC investigates molecular determinants of cell identity and collaborates with teams studying hematopoiesis, cancer signaling, and immunotherapies.

John Konstantine TsotsosView profile

Research Professor

• Computer Vision
• Visual Attention
• Active Vision Systems
• +5 more

John Konstantine Tsotsos is a Research Professor in the Department of Electrical Engineering and Computer Science at Lassonde School of Engineering, York University . He is a member of the Centre for Innovation in Computing and the Centre for Vision Research at York, as well as an Adjunct Professor in the Department of Ophthalmology and Vision Sciences at the Temerty Faculty of Medicine, University of Toronto . Education Ph.D. in Computer Science, University of Toronto (1980), titled A Framework for Visual Motion Understanding M.Sc. in Computer Science, University of Toronto (1976) B.A.Sc. (Honours) in Engineering Science (Computer Science Option), University of Toronto (1974) Dr. Tsotsos is a world leader in interdisciplinary vision science , spanning human and computational vision . His Selective Tuning theory revolutionized visual attention research, predicting novel aspects of top-down processing in perception. Contributions include computational complexity of vision , active perception systems , and medical image analysis . His work underpins advancements in robotic vision , gaze prediction , and abnormal gait detection . His scientific awards include the Sir John William Dawson Medal (2015) , CS-Can|Info-Can Lifetime Achievement Award (2020) , and fellowships in the Royal Society of Canada (2010) , IEEE (2018) , and Canadian Academy of Engineering (2024) . He held the NSERC Tier I Canada Research Chair in Computational Vision (2003–2024) and has been cited for 1000+ research publications . Dr. Tsotsos has advised over 200 trainees (Ph.D., M.Sc., and postdocs) and shaped vision science through founding the Computer Vision Research Group at the University of Toronto (1980) and directing the Centre for Innovation in Computing at York University (2014–2024) . His patents in touch-sensitive displays and face recognition (e.g., US Patent #6,118,433) demonstrate practical applications of his research.

Gregory HagenView profile

Associate Professor

• Artificial Intelligence Law
• Intellectual Property Law
• Information Security and Privacy Law
• +4 more

Gregory Hagen is an Associate Professor at the Faculty of Law, University of Calgary, specializing in intellectual property law, artificial intelligence law, information security, and biotechnology law. He has served as Associate Dean (Research) and Graduate Program Director from 2014-2019 and has taught at multiple international institutions including University of Ottawa, Western University, Duke University's Asia America Institute in Transnational Law at University of Hong Kong, and Peking University. Educational Background: PhD in Philosophy of Science, University of Western Ontario LLM (Law & Technology), University of Ottawa LLB, Dalhousie University MA in Philosophy, University of British Columbia BA in Philosophy, University of British Columbia Professor Hagen's research focuses on patent law and legal issues related to artificial intelligence, information security, privacy technologies, and biotechnology. His work spans Information Technology and Internet Law (including AI, blockchain, smart contracts, and cryptocurrency), Intellectual Property Law, Information Security and Privacy Law, Biotechnology Law, and Legal Theory and Philosophy. His interdisciplinary approach bridges legal frameworks with technological advancements, particularly focusing on how emerging technologies challenge traditional legal concepts and require innovative regulatory solutions. His publications reveal a consistent focus on the intersection of law and rapidly evolving technologies, with particular attention to intellectual property frameworks. Recent works emphasize AI-related legal challenges, blockchain applications, and the regulatory complexities of synthetic biology. His scholarship shows progression from traditional copyright and patent issues toward cutting-edge concerns in AI governance, misinformation challenges, and the legal implications of decentralized technologies. The breadth of his work demonstrates expertise across both theoretical legal philosophy and practical regulatory frameworks. Professor Hagen has taught courses including Ethical Lawyering, Graduate Seminar in Legal Research & Methodology, Intellectual Property, and Legal Theory: Artificial Intelligence. His teaching reflects his research interests, with specialized courses addressing the legal implications of emerging technologies. While specific grant information isn't provided in the available text, his extensive publication record spanning multiple disciplines suggests significant research activity and likely grant funding in technology law areas.

Sebastian FischmeisterView profile

Professor

• Embedded Systems
• Distributed Systems
• Formal Methods
• +8 more

Sebastian Fischmeister is a Professor and NSERC/Magna Industrial Research Chair in Automotive Software for Connected and Automated Vehicles at the Department of Electrical and Computer Engineering, University of Waterloo. His research focuses on systems at the intersection of software technology, distributed systems, and formal methods, with applications in automotive systems, avionics, and medical devices. He has pioneered frameworks for scalable location-based pervasive computing and verifiable real-time communication schedules, contributing to the ASTM F29.21 standard. Education: Dipl.-Ing. in Computer Science (Vienna University of Technology, 2000), Ph.D. in Computer Science (University of Salzburg, 2002) Research Themes: Real-time embedded systems, runtime monitoring, security analysis, data analytics for validation, and performance evaluation. Scientific Awards: APART Stipend (2005) Ontario Early Researcher Award (2014) Multiple best paper and tool awards He is an ACM Distinguished Speaker and actively participates in organizing conferences such as ESCAR, RTSS, DATE, and ICPE. His work includes significant contributions to anomaly detection, cybersecurity in automotive networks, and runtime verification techniques under unreliable conditions.

• Machine learning
• Computer vision
• Pattern recognition
• +7 more

Eric Granger is a Professor in the Department of Systems Engineering at École de technologie supérieure (ETS) in Montreal, Quebec, Canada. He holds a B.Sc.A. from UQAM, and M.Sc.A. and Ph.D. from Polytechnique Montréal. Dr. Granger leads research at the LIVIA – Imaging, Vision and Artificial Intelligence Laboratory and holds the Distech Controls Research Chair on Embedded Neural Networks in a Controller for Connected Buildings. His research spans intelligent and autonomous systems with applications in health technologies. Dr. Granger's expertise includes machine learning, computer vision, pattern recognition, deep models, multimodal information fusion, domain adaptation, weakly supervised learning, and adaptive intelligent systems. His specific applications focus on face analysis and recognition, biometrics, medical imaging, affective computing, computer security, and video surveillance. Analysis of his recent publications reveals a strong focus on person re-identification across different modalities (visible-infrared), weakly supervised object localization, depression detection from facial analysis, and medical image analysis. His work consistently addresses domain adaptation challenges and develops innovative neural network architectures for real-world applications in surveillance and healthcare. Dr. Granger has supervised numerous doctoral students across various research topics including adaptive anomaly detection, signature verification, face recognition, medical image segmentation, and domain adaptation. His research is supported by multiple grants and collaborations with industry partners like Distech Controls. He leads the LIVIA research laboratory which focuses on imaging, vision, and artificial intelligence applications. The lab works on projects involving embedded neural networks for connected buildings, video surveillance systems, medical imaging applications, and affective computing solutions.

• Computer Graphics
• Physically Based Animation
• Motion Capture
• +4 more

Paul G. Kry is an Associate Professor in the School of Computer Science at McGill University, where he leads the Computer Animation and Interaction Capture Laboratory. His research focuses on physically based animation, computer graphics, and human motor control, with applications in video games, movies, training simulations, ergonomics, and robotics. He teaches graduate and undergraduate courses including COMP 557 (Fundamentals of Computer Graphics) and COMP 559 (Fundamentals of Computer Animation). Dr. Kry's research interests center on computer graphics, physically based animation, skin deformations of articulated characters, motion capture, interaction, and physically based modeling of humans and animals. He investigates human and animal motor control (locomotion, grasping, manipulation) in combination with the physics of rigid objects, deformation, and contact. His work emphasizes the combination of real-world measurements, approximate models, and physically based simulation, with additional interests in machine learning, numerical methods, and audio. His recent publications demonstrate strong trends in physically based animation, with focus areas including adaptive simulation techniques, real-to-sim calibration, constraint-based physics, neural network applications in graphics, and motion control policies. His work spans both theoretical foundations and practical applications, often bridging the gap between computer graphics and robotics. BEST PAPER at Graphics Interface, 2023 BEST STUDENT PRESENTATION at ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, 2019 BEST PAPER at Computational Aesthetics / Expressive, 2016 Dr. Kry actively supervises numerous PhD and MSc students, with many graduates going on to positions at leading companies including Ubisoft, Google, Facebook, and Autodesk. He has served on program committees for major conferences including ACM SIGGRAPH, Symposium on Computer Animation, and Graphics Interface. His lab maintains specialized equipment including a 24-camera motion capture system, force plates, consumer DSLR cameras, high-speed cameras, data gloves, quadrotor robots, and various pressure sensors.

Benoit GosselinView profile

Professor

• Wireless Implantable Electronics
• Brain-Computer Interfaces
• CMOS Microelectronic Circuits
• +4 more

Benoit Gosselin , Professor at Université Laval's Department of Electrical and Computer Engineering and Canada Research Chair in Smart Biomedical Microsystems, specializes in wireless implantable electronics, brain-computer interfaces, and biomedical microsystems. He leads the Biomedical Microsystems Lab at CERVO Brain Research Centre. Education : Ph.D. in Electrical Engineering (École Polytechnique de Montréal, 2009), NSERC Postdoctoral Fellow (Georgia Institute of Technology, 2010) Research Focus : Development of wireless electro-optic platforms for neural monitoring, optogenetics, and closed-loop applications, with emphasis on CMOS circuits, energy harvesting, and multimodal biosensors. Recent Publications highlight advancements in implantable neural probes with embedded micropumps, ultra-compact UWB transmitters for neural implants, and wearable biosensors leveraging machine learning for gesture recognition and pain management. His work bridges microelectronics, neuroscience, and personalized healthcare. Scientific Awards : Fellow of the Canadian Academy of Engineering (2020) Génie Innovation Prize (Order of Engineers of Quebec, 2019) NSERC Brockhouse Canada Prize (2018) Collaborations with Doric Lenses Inc. led to commercialization of wireless optogenetics platforms. He serves as Associate Editor of IEEE Transactions on Biomedical Circuits and Systems and founded the IEEE CAS/EMB Quebec Chapter.

• Robotics
• Control Systems
• Automation
• +4 more

Alexandre Girard is an Associate Professor in the Department of Mechanical Engineering at the Faculty of Engineering, University of Sherbrooke, Canada. He joined the university in 2017 as an Assistant Professor and was promoted to Associate Professor in 2022. His academic journey includes a Ph.D. from MIT (2017), and Master's and Bachelor's degrees from Université de Sherbrooke (2013, 2010). His research spans robotics, control systems, and actuation technologies for applications in healthcare, industrial automation, and human augmentation. Educational background: Ph.D. in Mechanical Engineering, Massachusetts Institute of Technology (2017) M.A.Sc. in Mechanical Engineering, Université de Sherbrooke (2013) B.Eng. in Mechanical Engineering, Université de Sherbrooke (2010) Dr. Girard's research focuses on the art of controlling motion, from mechanical design to control laws and planning algorithms. His expertise includes robotics, automation, dynamics, machine learning, and the development of novel actuators (variable gear-ratio, magnetorheological, hydrostatic) for applications in wearable robotics, patient handling, and industrial systems. His work bridges theoretical innovation with practical implementation through industry partnerships. Analysis of his recent publications reveals strong emphasis on actuator design and control for robotics, particularly wearable and collaborative systems. Key trends include dimensionless analysis (Buckingham Pi theorem) for cross-system generalization, multi-system transfer learning, and multifunctional actuators addressing energy efficiency and task versatility in human-robot interaction. Scientific awards and distinctions: High Distinction in University Teaching (Major Design Project Team), University of Sherbrooke (2025) Teaching Award (Robotics Engineering Program Team), University of Sherbrooke (2022) Alexander Graham Bell Canada Graduate Scholarship (CGS D), NSERC (2015) Alexander Graham Bell Canada Graduate Scholarship (CGS M), NSERC (2011) 2nd Place at de Florez Design Competition, MIT Leonardo da Vinci Medal, Université de Sherbrooke As principal investigator, Dr. Girard has secured over $2 million in research funding from NSERC, FRQNT, CFI, and industry partners. Major projects include PRL+ ($1.65M, 2025-2031) for PhD readiness development, patient handling robotics with Arjo Canada ($230K, 2021-2026), and smart off-road vehicles with PROMPT-Québec ($39K, 2022-2025). He mentors graduate students in robotics and control systems through courses like Robot Kinematics (GRO640) and Control Systems (GRO501). He leads the Agile and Dexterous Motion Control Robotic Laboratory at the University of Sherbrooke, equipped with state-of-the-art facilities for actuator development and robotic testing. His team collaborates with the NSERC Canadian Robotics Network and industry partners including Arjo, Safran, and Kinova to translate research into healthcare solutions, construction automation, and power line inspection technologies.

Hyock Ju KwonView profile

Professor

• Artificial Intelligence
• Machine Learning
• Manufacturing Engineering
• +5 more

Hyock Ju Kwon is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo . Active in research and teaching, he focuses on integrating Artificial Intelligence (AI) with manufacturing practices and biomedical ultrasound techniques . Doctorate in Mechanical Engineering, University of Alberta (2007) Master's in Mechanical Engineering, University of Alberta (2003) Master's in Mechanical Engineering, KAIST (1988) Bachelor's in Mechanical and Design Engineering, Seoul National University (1985) His research spans AI and machine learning , with applications in manufacturing (robotic assembly, NDT, predictive maintenance) and biomedical fields (therapeutic ultrasound, tactile neuroimaging). He leads the AI for Manufacturing Laboratory , emphasizing digital twin and multi-physics modeling . The 15 most recent articles reflect trends in AI-driven manufacturing , ultrasound diagnostic/therapeutic systems , and robotic path planning . Keywords include machine learning , medical imaging , and fluid dynamics , with subfields like predictive maintenance , nanoparticle-enhanced therapy , and topological navigation . As a Sole-Supervisory Privilege Status (SSPS) holder, he supervises graduate students. Teaching includes courses like ME 212 - Dynamics and ME 526 - Fatigue and Fracture Analysis . The AI for Manufacturing Laboratory develops cutting-edge technologies for industrial AI , collaborating with Korean municipal governments on large-scale projects. Areas include robotic assembly , non-destructive testing , and machine condition monitoring .

Gennady PekhimenkoView profile

Associate Professor

• Computer Architecture
• Systems Research
• Applied Machine Learning
• +3 more

Dr. Gennady Pekhimenko is an Associate Professor in the Department of Computer Science and cross-appointed to the Electrical and Computer Engineering department at the University of Toronto. He leads the EcoSystem research group and serves as CEO/Co-Founder of CentML, with affiliations at CIFAR and Vector Institute. PhD in Computer Science from Carnegie Mellon University (2016) His research spans computer architecture, systems optimization, and applied machine learning, with a focus on memory hierarchy efficiency, hardware acceleration, and compiler design. Recent work emphasizes large language model training, GPU virtualization, and processing-in-memory systems. Key article trends include: 1) Memory optimization for transformers and sparse models (2024-2025), 2) GPU resource management (2022-2024), 3) Prompt programming languages (2025), and 4) Deep learning compilation frameworks (2021-2023). Major Awards: NVIDIA Graduate Fellowship, Microsoft Research PhD Fellowship, ISCA Hall of Fame, AWS/Google/VMware research grants Key Collaborations: Onur Mutlu (CMU), Todd Mowry (CMU), Vector Institute researchers

Arash Mahdavi-AmiriView profile

Assistant Professor

• Computer Graphics
• Geometric Modeling
• Digital Fabrication
• +3 more

Arash Mahdavi-Amiri is an Assistant Professor at the School of Computing Science, Simon Fraser University, and serves as the director of the Master of Science in Professional Computer Science program and research director at MARZ (Mahdavi-Amiri Research Lab). He is an associate editor of IEEE Transactions on Visualization and Computer Graphics and actively contributes to academic leadership as a technical paper chair for 3DV 2026 and program committee member for SIGGRAPH 2025 and SIGGRAPH Asia 2024 . Academic Roles: Assistant Professor (SFU), Director of MPCS (SFU), Director of Research (MARZ), Associate Editor (IEEE TVCG) Projects: Industrial and research initiatives in Computer Vision, Machine Learning, and Computational Fabrication Research Interests span Computer Graphics, Geometric Modeling, Digital Fabrication, Machine Learning, and Computer Vision. His work focuses on 3D generation, image processing, and diffusion models, with applications in generative AI, digital fabrication workflows, and geometric reasoning. Papers like Cora and pOps highlight his contributions to correspondence-aware image editing and photo-inspired diffusion operators. Scientific Awards include the NSERC Postdoctoral Fellowship, J.B. Hyne Research Innovation Award, Michael A. J. Sweeney Award, and a Teaching Excellence Award. His research has also led to patents in image processing and aging/de-aging technologies. NSERC Postdoctoral Fellowship J.B. Hyne Research Innovation Award Michael A. J. Sweeney Award Teaching Excellence Award Advising includes supervising PhD candidates (Jiayi Liu, Dingdong Yang, Maham Tanveer) and MSc students (Amirhossein Alimohammadi, Alireza Heidari), with alumni pursuing PhDs at SFU and UBC. Recent graduates include Mingrui Zhao and Mehdi Safaee, who successfully defended their MSc theses in 2024.

Bao Michael UyenView profile

Adjunct Professor

• Complex Systems
• Robotics
• Artificial Intelligence
• +7 more

Bao Michael Uyen is an Adjunct Professor at the University of Ottawa Faculty of Engineering (Department of Mechanical Engineering) and a Senior Scientist at Defence Research and Development Canada (DRDC) , a role he has held since 1993. He is also co-chair of NATO Modelling Simulation Group 186, leading research on multidimensional data farming. His affiliations span NORAD, US Space Command, NATO Centre for Maritime Research & Experimentation, and DRDC Atlantic. Education: PhD in Theoretical Particle Physics, McGill University (1993) BSc in Physics (summa cum laude), University of Ottawa (1988) BSc in Mathematics (summa cum laude), University of Ottawa (1988) Undergraduate studies at Caltech (2 years) Research Interests: Dr. Uyen's research lies at the intersection of complex systems, autonomous agents, and defense applications. He investigates how autonomous vehicles, human operators, and AI systems interact in high-stakes environments. His work spans robotics, AI, cybersecurity, machine learning, combinatorial optimization, stochastic processes, and discrete mathematics. These disciplines are applied to mine countermeasures, ballistic missile defense, multi-domain operations, and strategic deterrence. Research Trends: His recent publications reflect a strong focus on multi-domain defense modeling , AI-enhanced simulation , and autonomous systems . Themes include quantum game theory in deterrence, probabilistic modeling for mine detection, and data farming for strategic decision support. These works are often collaborative and NATO-linked, emphasizing real-world defense applications. Scientific Awards & Honors: Koopman Prize 2014 – Outstanding Military Operations Research (INFORMS) Third Prize, CORS Practice Competition 2006 – AUV Mine Countermeasures Deputy Minister Commendation Award – NORAD Sustainability Special Merit, CORS Practice Competition 2000 – Search & Rescue Modeling Gold Medal, University of Ottawa 1988 NSERC Postdoctoral Fellowship 1993–1995 Multiple NSERC and Ontario Graduate Scholarships Advising & Grants: Dr. Uyen has mentored numerous graduate students who now hold positions at institutions like Yale, IBM, and the University of Manitoba. He has secured over $6.7 million CAD in defense research funding, including a $5.6M collaborative project with uOttawa, UNB, and NRC focused on autonomous agent coordination. Labs & Teams: He leads research under the NATO Modelling Simulation Group 186 and collaborates with DRDC teams across Canada and internationally. His work integrates defense simulation, robotics, and AI, often involving interdisciplinary teams from academia, military, and government agencies.

Tommaso CesariView profile

Assistant Professor

• Online Learning
• Optimization Theory
• Bandit Algorithms
• +6 more

Tommaso Cesari is an Assistant Professor at the School of Electrical Engineering and Computer Science and cross-appointed with the Department of Mathematics and Statistics at the University of Ottawa. He holds a Ph.D. in Computer Science (with distinction) and Master’s/Bachelor’s degrees in Mathematics (summa cum laude) from the University of Milan. His research focuses on theoretical machine learning, online optimization, and algorithmic game theory with applications to digital markets and space operations. Education: Bachelor's Degree in Mathematics (summa cum laude), Università degli Studi di Milano (2011) Master's Degree in Mathematics (summa cum laude), Università degli Studi di Milano (2015) Ph.D. in Computer Science (with distinction), Università degli Studi di Milano (2020) Tommaso’s research spans online learning , regret minimization , and optimization under limited feedback . His work bridges machine learning , game theory , and stochastic optimization , with applications to bilateral trade , market microstructure , and spacecraft operations . His recent publications emphasize regret analysis in contextual brokerage, market making , and fair bilateral trade . He has contributed to top venues like COLT , NeurIPS , EC , and MOR , often collaborating with researchers such as Nicolò Cesa-Bianchi and François Bachoc. Tommaso currently teaches ITI 1121 — Introduction to Computing II and CSI 4145 — Machine Learning at the University of Ottawa. He is a member of the ELLIS society and serves as an editor for Springer's Machine Learning Journal .